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Pelagatti L, Fabiani G, De Paris A, Lagomarsini A, Paolucci E, Pepe F, Villanti M, Todde F, Matteini S, Caldi F, Pini R, Innocenti F. 4C mortality score and COVID-19 mortality risk score: an analysis in four different age groups of an Italian population. Intern Emerg Med 2024; 19:1717-1725. [PMID: 38393501 DOI: 10.1007/s11739-024-03551-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 01/18/2024] [Indexed: 02/25/2024]
Abstract
To evaluate the prognostic stratification ability of 4C Mortality Score and COVID-19 Mortality Risk Score in different age groups. Retrospective study, including all patients, presented to the Emergency Department of the University Hospital Careggi, between February, 2020 and May, 2021, and admitted for SARS-CoV2. Patients were divided into four subgroups based on the quartiles of age distribution: patients < 57 years (G1, n = 546), 57-71 years (G2, n = 508), 72-81 years (G3, n = 552), and > 82 years (G4, n = 578). We calculated the 4C Mortality Score and COVID-19 Mortality Risk Score. The end-point was in-hospital mortality. In the whole population (age 68 ± 16 years), the mortality rate was 19% (n = 424), and increased with increasing age (G1: 4%, G2: 11%, G3: 22%, and G4: 39%, p < 0.001). Both scores were higher among non-survivors than survivors in all subgroups (4C-MS, G1: 6 [3-7] vs 3 [2-5]; G2: 10 [7-11] vs 7 [5-8]; G3: 11 [10-14] vs 10 [8-11]; G4: 13 [12-15] vs 11 [10-13], all p < 0.001; COVID-19 MRS, G1: 8 [7-9] vs 9 [9-11], G2: 10 [8-11] vs 11 [10-12]; G3: 11 [10-12] vs 12 [11-13]; G4: 11 [10-13] vs 13 [12-14], all p < 0.01). The ability of both scores to identify patients at higher risk of in-hospital mortality, was similar in different age groups (4C-MS: G1 0.77, G2 0.76, G3 0.68, G4 0.72; COVID-19 MRS: G1 0.67, G2 0.69, G3 0.69, G4 0.72, all p for comparisons between subgroups = NS). Both scores confirmed their good performance in predicting in-hospital mortality in all age groups, despite their different mortality rate.
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Affiliation(s)
- Lorenzo Pelagatti
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Italy
| | - Ginevra Fabiani
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Italy
| | - Anna De Paris
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Italy
| | - Alessia Lagomarsini
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Italy
| | - Elisa Paolucci
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Italy
| | - Francesco Pepe
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Italy
| | - Maurizio Villanti
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Italy
| | - Francesca Todde
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Italy
| | - Simona Matteini
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Italy
| | - Francesca Caldi
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Italy
| | - Riccardo Pini
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Italy
| | - Francesca Innocenti
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Italy.
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Liu X, Zhao Q, He X, Min J, Yao RSY, Chen Z, Ma J, Hu W, Huang J, Wan H, Guo Y, Zhou M. Clinical characteristics and microbial signatures in the lower airways of diabetic and nondiabetic patients with pneumonia. J Thorac Dis 2024; 16:5262-5273. [PMID: 39268134 PMCID: PMC11388247 DOI: 10.21037/jtd-24-490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 07/12/2024] [Indexed: 09/15/2024]
Abstract
Background The microbial signatures in diabetes with pneumonia and the risk factors of severe pneumonia (SP) in diabetic patients are not clear. Our study explored microbial signatures and the association between clinical characteristics and SP then constructed a risk model to find effective biomarkers for predicting pneumonia severity. Methods Our study was conducted among 273 patients with pneumonia diagnosed and treated in our hospital from January 2018 to May 2021. Bronchoalveolar lavage fluid (BALF) samples and clinical data were collected. Metagenomic sequencing was applied after extracting the DNA from samples. Appropriate statistical methods were used to compare the microbial signatures and clinical characteristics in patients with or without diabetes mellitus (DM). Results In total, sixty-one pneumonia patients with diabetes and 212 pneumonia patients without diabetes were included. Sixty-six differential microorganisms were found to be associated with SP in diabetic patients. Some microbes correlated with clinical indicators of SP. The prediction model for SP was established and the receiver operating characteristic (ROC) curve demonstrated its accuracy, with the sensitivity and specificity of 0.82 and 0.91, respectively. Conclusions Some microorganisms affect the severity of pneumonia. We identified the microbial signatures in the lower airways and the association between clinical characteristics and SP. The predictive model was more accurate in predicting SP by combining microbiological indicators and clinical characteristics, which might be beneficial to the early identification and management of patients with SP.
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Affiliation(s)
- Xuefei Liu
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qianqian Zhao
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | | | | | | | - Jinmin Ma
- PathoGenesis, BGI Genomics, Shenzhen, China
| | - Weiting Hu
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jingwen Huang
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huanying Wan
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yi Guo
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Min Zhou
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Lee SB, Kang JY, Chie EK, Bae YS. A novel deterioration prediction system for mild COVID-19 patients in Korea: a retrospective study. Sci Rep 2024; 14:20171. [PMID: 39215109 PMCID: PMC11364862 DOI: 10.1038/s41598-024-71033-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 08/23/2024] [Indexed: 09/04/2024] Open
Abstract
The ongoing coronavirus disease 2019 (COVID-19) pandemic presents serious public health threats. Omicron, the current most prevalent strain of COVID-19, has a low fatality rate and very high transmissibility, so the number of patients with mild symptoms of COVID-19 is rapidly increasing. This change of pandemic challenges medical systems worldwide in many aspects, including sharp increases in demands for hospital infrastructure, critical shortages in medical equipment, and medical staff. Predicting deterioration in mild patients could alleviate these problems. A novel scoring system was proposed for predicting the deterioration of patients whose condition may worsen rapidly and those who all still mild or asymptomatic. Retrospective cohorts of 954 and 2,035 patients that quarantined in the Residential Treatment Center were assembled for derivation and external validation of mild COVID-19, respectively. Deterioration was defined as transfer to a local hospital due to worsening condition of the patients during the 2-week isolation period. A total of 15 variables: sex, age, seven pre-existing conditions (diabetes, hypertension, cardiovascular disease, respiratory disease, liver disease, kidney disease, and organ transplant), and five vital signs (systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR), body temperature, and oxygen saturation (SpO2)) were collected. A scoring system was developed using seven variables (age, pulse rate, SpO2, SBP, DBP, temperature, and hypertension) with significant differences between the transfer and not transfer groups in logistic regression. The proposed system was compared with existing scoring systems that assess the severity of patient conditions. The performance of the proposed scoring system to predict deterioration in patients with mild COVID-19 showed an area under the receiver operating characteristic (AUC) of 0.868. This is a statistically significant improvement compared to the performance of the previous patient condition assessment scoring systems. During external validation, the proposed system showed the best and most robust predictive performance (AUC = 0.768; accuracy = 0.899). In conclusion, we proposed a novel scoring system for predicting patients with mild COVID-19 who will experience deterioration which could predict the deterioration of the patient's condition early with high predictive performance. Furthermore, because the scoring system does not require special calculations, it can be easily measured to predict the deterioration of a patients' condition. This system can be used as effective tool for early detection of deterioration in mild COVID-19 patients.
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Affiliation(s)
- Seung-Bo Lee
- Department of Medical Informatics, Keimyung University School of Medicine, Daegu, South Korea
| | - Jin-Yeong Kang
- Department of Medical Informatics, Keimyung University School of Medicine, Daegu, South Korea
- Department of Statistics and Data Science, Yonsei University, Seoul, South Korea
| | - Eui Kyu Chie
- Department of Radiation Oncology, Seoul National Univerisity College of Medicine, Seoul, South Korea
- Institute of Radiation Medicine, Medical Research Center, Seoul National Univerisity, Seoul, South Korea
| | - Ye Seul Bae
- Big Data Research Institute, Kangbuk Samsung Hospital Sungkyunkwan University School of Medicine, Seoul, South Korea.
- Department of Family Medicine, Kangbuk Samsung Hospital Sungkyunkwan University School of Medicine, Seoul, South Korea.
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Ni R, Zhong M, Xie M, Ding Z. Comparative analysis of prognostic scoring systems in predicting severity and outcomes of Omicron variant COVID-19 pneumonia. Front Med (Lausanne) 2024; 11:1419690. [PMID: 38957300 PMCID: PMC11217537 DOI: 10.3389/fmed.2024.1419690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Accepted: 06/06/2024] [Indexed: 07/04/2024] Open
Abstract
Background The global spread of Coronavirus Disease 2019 (COVID-19) underscores the urgent need for reliable methods to forecast the disease's severity and outcome, thereby facilitating timely interventions and reducing mortality rates. This study focuses on evaluating the clinical and laboratory profiles of patients with Omicron variant-induced COVID-19 pneumonia and assessing the efficacy of various scoring systems in prognosticating disease severity and mortality. Methods In this retrospective analysis, we examined the clinical records of 409 individuals diagnosed with Omicron variant COVID-19 pneumonia. We documented the Pneumonia Severity Index, CURB-65, and MuLBSTA scores within the first 24 h and analyzed the sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristic curve for each scoring system to ascertain their predictive accuracy for disease severity and fatality risk. Results The cohort's median age was 78 years, predominantly presenting with fever, cough, expectoration, fatigue, and gastrointestinal symptoms. Factors such as expectoration, fatigue, Glasgow Coma Scale score, lactate dehydrogenase levels, procalcitonin, creatinine levels, and co-occurrence of acute respiratory distress syndrome were identified as independent predictors of disease severity. Furthermore, age, oxygenation index, glucose levels, lactate dehydrogenase, and septic shock were independently associated with mortality. For severe disease prediction, the CURB-65, PSI, and MuLBSTA scores demonstrated sensitivities of 65.9%, 63.8%, and 79.7%, respectively, with specificities of 63.8%, 76.8%, and 60.9%, and AUROCs of 0.707, 0.750, and 0.728. To predict mortality risk, these scores at cutoffs of 1.5, 102.5, and 12.5 exhibited sensitivities of 83.3%, 96.3%, and 70.4%, specificities of 59.4%, 60.8%, and 65.4%, and AUROCs of 0.787, 0.850, and 0.736, respectively. Conclusion The study cohort predominantly comprised elderly individuals with pre-existing health conditions. Elevated lactate dehydrogenase emerged as a significant marker for both disease severity and prognosis, sputum production, gastrointestinal symptoms, GCS score, creatinine, PCT, and ARDS as independent predictors of disease severity, and age, oxygenation index, glucose levels, and septic shock as independent mortality predictors in COVID-19 pneumonia patients. Among the scoring systems evaluated, Pneumonia Severity Index demonstrated superior predictive capability for both disease severity and mortality, suggesting its utility in forecasting the clinical outcomes of Omicron variant COVID-19 pneumonia.
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Affiliation(s)
- Ruiqin Ni
- Graduate School, Bengbu Medical University, Bengbu, China
- Third Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Mingmei Zhong
- Third Affiliated Hospital of Anhui Medical University, Hefei, China
| | | | - Zhen Ding
- Third Affiliated Hospital of Anhui Medical University, Hefei, China
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Mendoza-Hernandez MA, Hernandez-Fuentes GA, Sanchez-Ramirez CA, Rojas-Larios F, Guzman-Esquivel J, Rodriguez-Sanchez IP, Martinez-Fierro ML, Cardenas-Rojas MI, De-Leon-Zaragoza L, Trujillo-Hernandez B, Fuentes-Murguia M, Ochoa-Díaz-López H, Sánchez-Meza K, Delgado-Enciso I. Time‑dependent ROC curve analysis to determine the predictive capacity of seven clinical scales for mortality in patients with COVID‑19: Study of a hospital cohort with very high mortality. Biomed Rep 2024; 20:100. [PMID: 38765855 PMCID: PMC11099607 DOI: 10.3892/br.2024.1788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 04/12/2024] [Indexed: 05/22/2024] Open
Abstract
Clinical data from hospital admissions are typically utilized to determine the prognostic capacity of Coronavirus disease 2019 (COVID-19) indices. However, as disease status and severity markers evolve over time, time-dependent receiver operating characteristic (ROC) curve analysis becomes more appropriate. The present analysis assessed predictive power for death at various time points throughout patient hospitalization. In a cohort study involving 515 hospitalized patients (General Hospital Number 1 of Mexican Social Security Institute, Colima, Mexico from February 2021 to December 2022) with COVID-19, seven severity indices [Pneumonia Severity Index (PSI) PaO2/FiO2 arterial oxygen pressure/fraction of inspired oxygen (Kirby index), the Critical Illness Risk Score (COVID-GRAM), the National Early Warning Score 2 (NEWS-2), the quick Sequential Organ Failure Assessment score (qSOFA), the Fibrosis-4 index (FIB-4) and the Viral Pneumonia Mortality Score (MuLBSTA were evaluated using time-dependent ROC curves. Clinical data were collected at admission and at 2, 4, 6 and 8 days into hospitalization. The study calculated the area under the curve (AUC), sensitivity, specificity, and predictive values for each index at these time points. Mortality was 43.9%. Throughout all time points, NEWS-2 demonstrated the highest predictive power for mortality, as indicated by its AUC values. PSI and COVID-GRAM followed, with predictive power increasing as hospitalization duration progressed. Additionally, NEWS-2 exhibited the highest sensitivity (>96% in all periods) but showed low specificity, which increased from 22.9% at admission to 58.1% by day 8. PSI displayed good predictive capacity from admission to day 6 and excellent predictive power at day 8 and its sensitivity remained >80% throughout all periods, with moderate specificity (70.6-77.3%). COVID-GRAM demonstrated good predictive capacity across all periods, with high sensitivity (84.2-87.3%) but low-to-moderate specificity (61.5-67.6%). The qSOFA index initially had poor predictive power upon admission but improved after 4 days. FIB-4 had a statistically significant predictive capacity in all periods (P=0.001), but with limited clinical value (AUC, 0.639-0.698), and with low sensitivity and specificity. MuLBSTA and IKIRBY exhibited low predictive power at admission and no power after 6 days. In conclusion, in COVID-19 patients with high mortality rates, NEWS-2 and PSI consistently exhibited predictive power for death during hospital stay, with PSI demonstrating the best balance between sensitivity and specificity.
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Affiliation(s)
- Martha A. Mendoza-Hernandez
- Department of Molecular Medicine, School of Medicine, University of Colima, Colima 28040, Mexico
- COVID Unit, General Hospital Number 1, Mexican Institute of Social Security, Villa de Alvarez, Colima 28984, Mexico
| | | | | | - Fabian Rojas-Larios
- Department of Molecular Medicine, School of Medicine, University of Colima, Colima 28040, Mexico
| | - Jose Guzman-Esquivel
- Clinical Epidemiology Research Unit, Mexican Institute of Social Security, Villa de Alvarez, Colima 28984, Mexico
| | - Iram P. Rodriguez-Sanchez
- Molecular and Structural Physiology Laboratory, School of Biological Sciences, Autonomous University of Nuevo Leon, San Nicolas de los Garza 66455, Mexico
| | - Margarita L. Martinez-Fierro
- Molecular Medicine Laboratory, Academic Unit of Human Medicine and Health Sciences, Autonomous University of Zacatecas, Zacatecas 98160, Mexico
| | - Martha I. Cardenas-Rojas
- Clinical Epidemiology Research Unit, Mexican Institute of Social Security, Villa de Alvarez, Colima 28984, Mexico
- Department of Research, Colima Cancerology State Institute, IMSS-Bienestar Colima, Colima 28085, Mexico
| | - Luis De-Leon-Zaragoza
- Department of Research, Colima Cancerology State Institute, IMSS-Bienestar Colima, Colima 28085, Mexico
| | | | - Mercedes Fuentes-Murguia
- Department of Molecular Medicine, School of Medicine, University of Colima, Colima 28040, Mexico
| | - Héctor Ochoa-Díaz-López
- Department of Health, El Colegio de La Frontera Sur, San Cristóbal de Las Casas, 29290 Chiapas, Mexico
| | - Karmina Sánchez-Meza
- Department of Molecular Medicine, School of Medicine, University of Colima, Colima 28040, Mexico
| | - Ivan Delgado-Enciso
- Department of Molecular Medicine, School of Medicine, University of Colima, Colima 28040, Mexico
- Department of Research, Colima Cancerology State Institute, IMSS-Bienestar Colima, Colima 28085, Mexico
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Chen X, Ma B, Yang Y, Zhang M, Xu F. Predicting the potentially exacerbation of severe viral pneumonia in hospital by MuLBSTA score joint CD4 + and CD8 +T cell counts: construction and verification of risk warning model. BMC Pulm Med 2024; 24:261. [PMID: 38811907 PMCID: PMC11137986 DOI: 10.1186/s12890-024-03073-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 05/22/2024] [Indexed: 05/31/2024] Open
Abstract
PURPOSE This study mainly focuses on the immune function and introduces CD4+, CD8+ T cells and their ratios based on the MuLBSTA score, a previous viral pneumonia mortality risk warning model, to construct an early warning model of severe viral pneumonia risk. METHODS A retrospective single-center observational study was operated from January 2021 to December 2022 at the People's Hospital of Liangjiang New Area, Chongqing, China. A total of 138 patients who met the criteria for viral pneumonia in hospital were selected and their data, including demographic data, comorbidities, laboratory results, CT scans, immunologic and pathogenic tests, treatment regimens, and clinical outcomes, were collected and statistically analyzed. RESULTS Forty-one patients (29.7%) developed severe or critical illness. A viral pneumonia severe risk warning model was successfully constructed, including eight parameters: age, bacterial coinfection, CD4+, CD4+/CD8+, multiple lung lobe infiltrations, smoking, hypertension, and hospital admission days. The risk score for severe illness in patients was set at 600 points. The model had good predictive performance (AUROC = 0.94397), better than the original MuLBSTA score (AUROC = 0.8241). CONCLUSION A warning system constructed based on immune function has a good warning effect on the risk of severe conversion in patients with viral pneumonia.
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Affiliation(s)
- Xi Chen
- Department of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, No.1 Youyi Road, Yuzhong District, Chongqing, 400016, China
- Department of Critical Care Medicine, People's Hospital of Chongqing Liangjiang New Area, Chongqing, 401120, China
| | - Bei Ma
- Department of Critical Care Medicine, People's Hospital of Chongqing Liangjiang New Area, Chongqing, 401120, China
| | - Yu Yang
- Department of Critical Care Medicine, People's Hospital of Chongqing Liangjiang New Area, Chongqing, 401120, China
| | - Mu Zhang
- Department of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, No.1 Youyi Road, Yuzhong District, Chongqing, 400016, China.
| | - Fang Xu
- Department of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, No.1 Youyi Road, Yuzhong District, Chongqing, 400016, China.
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Arutyunov GP, Tarlovskaya EI, Polyakov DS, Batluk TI, Arutyunov AG. Predicting outcomes of the acute phase of COVID-19. High sensitive prognostic model, based on the results of the international registry "analysis of chronic non-infectious diseases dynamics after COVID-19 infection in adult patients" (ACTIV). Heliyon 2024; 10:e28892. [PMID: 38596083 PMCID: PMC11002283 DOI: 10.1016/j.heliyon.2024.e28892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 03/26/2024] [Accepted: 03/26/2024] [Indexed: 04/11/2024] Open
Abstract
The aim of this study is to investigate the course of the acute period of COVID-19 and devise a prognostic scale for patients hospitalized. Materials and methods The ACTIV registry encompassed both male and female patients aged 18 years and above, who were diagnosed with COVID-19 and subsequently hospitalized. Between June 2020 and March 2021, a total of 9364 patients were enrolled across 26 medical centers in seven countries. Data collected during the patients' hospital stay were subjected to multivariate analysis within the R computational environment. A predictive mathematical model, utilizing the "Random Forest" machine learning algorithm, was established to assess the risk of reaching the endpoint (defined as in-hospital death from any cause). This model was constructed using a training subsample (70% of patients), and subsequently tested using a control subsample (30% of patients). Results Out of the 9364 hospitalized COVID-19 patients, 545 (5.8%) died. Multivariate analysis resulted in the selection of eleven variables for the final model: minimum oxygen saturation, glomerular filtration rate, age, hemoglobin level, lymphocyte percentage, white blood cell count, platelet count, aspartate aminotransferase, glucose, heart rate, and respiratory rate. Receiver operating characteristic analysis yielded an area under the curve of 89.2%, a sensitivity of 86.2%, and a specificity of 76.0%. Utilizing the final model, a predictive equation and nomogram (termed the ACTIV scale) were devised for estimating in-hospital mortality amongst COVID-19 patients. Conclusion The ACTIV scale provides a valuable tool for practicing clinicians to predict the risk of in-hospital death in patients hospitalized with COVID-19.
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Affiliation(s)
- Gregory P. Arutyunov
- Eurasian Association of Internal Medicine, Moscow, Russia
- Department of Propaedeutics of Internal Diseases (Pediatric School), Pirogov Russian National Research Medical University, Moscow, Russia
| | - Ekaterina I. Tarlovskaya
- Eurasian Association of Internal Medicine, Moscow, Russia
- Department of Therapy and Cardiology, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
| | - Dmitry S. Polyakov
- Department of Therapy and Cardiology, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
| | | | - Alexander G. Arutyunov
- Eurasian Association of Internal Medicine, Moscow, Russia
- Department of Cardiology and Internal Medicine, National Institute of Health named after Academician S. Avdalbekyan, Yerevan, Armenia
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Varaldo E, Rumbolo F, Prencipe N, Bioletto F, Settanni F, Mengozzi G, Grottoli S, Ghigo E, Brazzi L, Montrucchio G, Berton AM. Effectiveness of Copeptin, MR-proADM and MR-proANP in Predicting Adverse Outcomes, Alone and in Combination with Traditional Severity Scores, a Secondary Analysis in COVID-19 Patients Requiring Intensive Care Admission. J Clin Med 2024; 13:2019. [PMID: 38610784 PMCID: PMC11012433 DOI: 10.3390/jcm13072019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 03/26/2024] [Accepted: 03/28/2024] [Indexed: 04/14/2024] Open
Abstract
Objective: To investigate whether copeptin, MR-proADM and MR-proANP, alone or integrated with the SOFA, MuLBSTA and SAPS II scores, are capable of early recognition of COVID-19 ICU patients at increased risk of adverse outcomes. Methods: For this predefined secondary analysis of a larger cohort previously described, all consecutive COVID-19 adult patients admitted between March and December 2020 to the ICU of a referral, university hospital in Northern Italy were screened, and clinical severity scores were calculated upon admission. A blood sample for copeptin, MR-proADM and MR-proANP was collected within 48 h (T1), on day 3 (T3) and 7 (T7). Outcomes considered were ICU and in-hospital mortality, bacterial superinfection, recourse to renal replacement therapy (RRT) or veno-venous extracorporeal membrane oxygenation, need for invasive mechanical ventilation (IMV) and pronation. Results: Sixty-eight patients were enrolled, and in-hospital mortality was 69.1%. ICU mortality was predicted by MR-proANP measured at T1 (HR 1.005, 95% CI 1.001-1.010, p = 0.049), although significance was lost if the analysis was adjusted for procalcitonin and steroid treatment (p = 0.056). Non-survivors showed higher MR-proADM levels than survivors at all time points, and an increase in the ratio between values at baseline and at T7 > 4.9% resulted in a more than four-fold greater risk of in-hospital mortality (HR 4.417, p < 0.001). Finally, when considering patients with any reduction in glomerular filtration, an early copeptin level > 23.4 pmol/L correlated with a more than five-fold higher risk of requiring RRT during hospitalization (HR 5.305, p = 0.044). Conclusion: Timely evaluation of MR-proADM, MR-proANP and copeptin, as well as changes in the former over time, might predict mortality and other adverse outcomes in ICU patients suffering from severe COVID-19.
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Affiliation(s)
- Emanuele Varaldo
- Division of Endocrinology, Diabetology and Metabolism, Department of Medical Sciences, University of Turin, 10126 Turin, Italy
| | - Francesca Rumbolo
- Clinical Chemistry and Microbiology Laboratory, S. Croce and Carle Cuneo Hospital, 12100 Cuneo, Italy
| | - Nunzia Prencipe
- Division of Endocrinology, Diabetology and Metabolism, Department of Medical Sciences, University of Turin, 10126 Turin, Italy
| | - Fabio Bioletto
- Division of Endocrinology, Diabetology and Metabolism, Department of Medical Sciences, University of Turin, 10126 Turin, Italy
| | - Fabio Settanni
- Division of Clinical Biochemistry, Department of Laboratory Medicine, University of Turin, 10126 Turin, Italy
| | - Giulio Mengozzi
- Division of Clinical Biochemistry, Department of Laboratory Medicine, University of Turin, 10126 Turin, Italy
| | - Silvia Grottoli
- Division of Endocrinology, Diabetology and Metabolism, Department of Medical Sciences, University of Turin, 10126 Turin, Italy
| | - Ezio Ghigo
- Division of Endocrinology, Diabetology and Metabolism, Department of Medical Sciences, University of Turin, 10126 Turin, Italy
| | - Luca Brazzi
- Department of Surgical Sciences, University of Turin, 10126 Turin, Italy
- Anestesia e Rianimazione 1 U, Department of Anesthesia, Intensive Care and Emergency, Città della Salute e della Scienza Hospital, 10126 Turin, Italy
| | - Giorgia Montrucchio
- Department of Surgical Sciences, University of Turin, 10126 Turin, Italy
- Anestesia e Rianimazione 1 U, Department of Anesthesia, Intensive Care and Emergency, Città della Salute e della Scienza Hospital, 10126 Turin, Italy
| | - Alessandro Maria Berton
- Division of Endocrinology, Diabetology and Metabolism, Department of Medical Sciences, University of Turin, 10126 Turin, Italy
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9
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Xu X, Zhu X, Wang H, Liu X, Yang C, Liu L, Chen T, Cai L, Zhu H. Evaluation of the Prognostic Role of Neutrophil-Lymphocyte Ratio, C-Reactive Protein-Albumin Ratio, and Platelet-Lymphocyte Ratio in Patients with the Co-Presentation of Coronary Artery Disease and COVID-19. Infect Drug Resist 2024; 17:885-897. [PMID: 38468845 PMCID: PMC10926874 DOI: 10.2147/idr.s450318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Accepted: 02/27/2024] [Indexed: 03/13/2024] Open
Abstract
AIM The purpose of this study was to investigate the role of neutrophil-lymphocyte ratio (NLR), C-reactive protein-albumin ratio (CAR), and platelet-lymphocyte ratio (PLR) in the prognosis of patients with coronary artery disease (CAD) complicated with coronavirus disease 2019 (COVID-19). METHODS This study included 265 patients. A receiver operating characteristic (ROC) curve analysis was performed to preliminarily evaluate the predictive ability of NLR, CAR, and PLR for all-cause death. The primary outcome was all-cause death during hospitalization, while the secondary outcomes were cardiovascular death and respiratory failure death. The Cox proportional hazard model with adjusted covariates was used to analyze the cumulative risk of outcomes. We also conducted subgroup analyses based on the acute and chronic characteristics of CAD. Propensity score matching (PSM) was used to further evaluate the robustness of the primary outcome. RESULTS The ROC curve analysis results showed that the area under curve (AUC) values were 0.686 (95% CI 0.592-0.781, P<0.001) for NLR, 0.749 (95% CI 0.667-0.832, P<0.001) for CAR, and 0.571 (95% CI 0.455-0.687, P=0.232) for PLR. The Cox proportional hazard model showed that trends in NLR and PLR did not affect the risk of all-cause death (P=0.096 and P=0.544 for trend, respectively), but a higher CAR level corresponded to a higher risk of all-cause death (P<0.001 for trend). Similarly, The trends of NLR and PLR did not affect the risk of cardiovascular death and respiratory failure death, while a higher CAR level corresponded to a higher risk of cardiovascular death and respiratory failure death. The results of subgroup analyses and PSM were consistent with the total cohort. CONCLUSION In patients with CAD complicated with COVID-19, a higher CAR level corresponded to a higher risk of all-cause death, cardiovascular death, and respiratory failure death, while trends in NLR and PLR did not.
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Affiliation(s)
- Xiaoqun Xu
- Centre of Laboratory Medicine, Hangzhou Red Cross Hospital, Hangzhou, Zhejiang, People’s Republic of China
| | - Xinyu Zhu
- Zhejiang University School of Medicine, Hangzhou, Zhejiang, People’s Republic of China
| | - Hanxin Wang
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China
| | - Xiao Liu
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China
| | - Chao Yang
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China
| | - Libin Liu
- Centre of Laboratory Medicine, Hangzhou Red Cross Hospital, Hangzhou, Zhejiang, People’s Republic of China
| | - Tielong Chen
- Department of Cardiology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China
| | - Long Cai
- Centre of Laboratory Medicine, Hangzhou Red Cross Hospital, Hangzhou, Zhejiang, People’s Republic of China
| | - Houyong Zhu
- Department of Cardiology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China
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10
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Liao CH, Lai TY, Lin YY, Liao YC, Lai GM, Chu TH, Wu SY, Tsai WL, Whang-Peng J, Liu F, Chiou TJ, Yao CJ. Inhibition of Polyinosinic-Polycytidylic Acid-Induced Acute Pulmonary Inflammation and NF-κB Activation in Mice by a Banana Plant Extract. Int J Med Sci 2024; 21:107-122. [PMID: 38164360 PMCID: PMC10750330 DOI: 10.7150/ijms.88748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 10/17/2023] [Indexed: 01/03/2024] Open
Abstract
NF-κB activation is pivotal for the excess inflammation causing the critical condition and mortality of respiratory viral infection patients. This study was aimed to evaluate the effect of a banana plant extract (BPE) on suppressing NF-κB activity and acute lung inflammatory responses in mice induced by a synthetic double-stranded RNA viral mimetic, polyinosinic-polycytidylic acid (poly (I:C)). The inflammatory responses were analyzed by immunohistochemistry and HE stains and ELISA. The NF-κB activities were detected by immunohistochemistry in vivo and immunofluorescence and Western blot in vitro. Results showed that BPE significantly decreased influx of immune cells (neutrophils, lymphocytes, and total WBC), markedly suppressed the elevation of pro-inflammatory cytokines and chemokines (IL-6, RANTES, IFN-γ, MCP-1, keratinocyte-derived chemokine, and IL-17), and restored the diminished anti-inflammatory IL-10 in the bronchoalveolar lavage fluid (BALF) of poly (I:C)-stimulated mice. Accordingly, HE staining revealed that BPE treatment alleviated poly (I:C)-induced inflammatory cell infiltration and histopathologic changes in mice lungs. Moreover, immunohistochemical analysis showed that BPE reduced the pulmonary IL-6, CD11b (macrophage marker), and nuclear NF-κB p65 staining intensities, whilst restored that of IL-10 in poly (I:C)-stimulated mice. In vitro, BPE antagonized poly(I:C)-induced elevation of IL-6, nitric oxide, reactive oxygen species, NF-κB p65 signaling, and transient activation of p38 MAPK in human lung epithelial-like A549 cells. Taken together, BPE ameliorated viral mimic poly(I:C)-induced acute pulmonary inflammation in mice, evidenced by reduced inflammatory cell infiltration and regulation of both pro- and anti-inflammatory cytokines. The mechanism of action might closely associate with NF-κB signaling inhibition.
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Affiliation(s)
- Chien-Huang Liao
- Cancer Center, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
| | - Tung-Yuan Lai
- Department of Chinese Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 97002, Taiwan
- Traditional Chinese Medicine Cancer Center, Hualien Tzu Chi Hospital, Hualien 97002, Taiwan
| | - Yu-Ying Lin
- Cancer Center, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
| | - Yi-Chun Liao
- Institute of Biomedical Sciences, Academia Sinica, Taipei, 11529, Taiwan
| | - Gi-Ming Lai
- Cancer Center, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
- Division of Hematology and Medical Oncology, Department of Internal Medicine, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
| | - Tien-Hua Chu
- Chimera Bioscience Inc., No. 18 Siyuan St., Zhongzheng Dist., Taipei 10087, Taiwan
| | - Szu-Yao Wu
- Chimera Bioscience Inc., No. 18 Siyuan St., Zhongzheng Dist., Taipei 10087, Taiwan
| | - Wei-Lun Tsai
- Cancer Center, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
| | - Jacqueline Whang-Peng
- Cancer Center, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
- Division of Hematology and Medical Oncology, Department of Internal Medicine, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
| | - Frank Liu
- Department of Research and Development, Natural Well Technical Company, Guishan, Taoyuan 33377, Taiwan
| | - Tzeon-Jye Chiou
- Cancer Center, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
- Division of Hematology and Medical Oncology, Department of Internal Medicine, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
| | - Chih-Jung Yao
- Department of Medical Education and Research, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
- Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
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11
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Ishiguro T, Kobayashi Y, Shimizu Y, Uemura Y, Toriba R, Takata N, Ueda M, Shimizu Y. Prognostic factors of virus-associated pneumonia other than COVID-19 in adults. Respir Med 2024; 221:107497. [PMID: 38097142 DOI: 10.1016/j.rmed.2023.107497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 12/07/2023] [Accepted: 12/08/2023] [Indexed: 12/18/2023]
Abstract
OBJECTIVE To determine prognostic factors of virus-associated pneumonia other than coronavirus disease 2019. METHODS We retrospectively studied patients suffering from virus-associated community-acquired pneumonia, and who were admitted to Saitama Cardiovascular and Respiratory Center from 2002 to 2020. Prognostic factors were analyzed by univariable and multivariable regression analysis of patient demographics, laboratory data, chest imaging, severity on admission, and initial treatment. PATIENTS HIV-positive patients, those with non-resected lung cancer or receiving chemotherapy, and those with COVID-19 were excluded. Included were 363 patients diagnosed by nucleic acid amplification method, paired sera, and rapid diagnostic tests. RESULTS A CURB-65 score of ≥3 was significant by univariable analysis for 60-day mortality but was nonsignificant by multivariable analysis. The poor prognostic factors that were significant by multivariable analysis (p < 0.05) included immunosuppressive state due to systemic corticosteroid or immunosuppressant administration, acute kidney injury on admission, and corticosteroid administration initiated within 5 days or 5 days to 2 weeks from onset. CONCLUSION A CURB-65 score of ≥3, which is considered to indicate severe pneumonia, was of limited value for predicting mortality of virus-associated pneumonia. We showed patients' underlying diseases and complications to be independent factors of poor prognosis for 60-day mortality. Timing of the initiation of corticosteroid administration remains to be elucidated.
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Affiliation(s)
- Takashi Ishiguro
- Department of Respiratory Medicine, Saitama Cardiovascular and Respiratory Center, Japan.
| | - Yoichi Kobayashi
- Department of Respiratory Medicine, Saitama Cardiovascular and Respiratory Center, Japan
| | - Yosuke Shimizu
- Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan
| | - Yukari Uemura
- Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan
| | - Riho Toriba
- Pathology, Saitama Cardiovascular and Respiratory Center, Japan
| | - Naomi Takata
- Department of Radiology, Saitama Cardiovascular and Respiratory Center, Saitama, Japan
| | - Miyuki Ueda
- Department of Radiology, Saitama Cardiovascular and Respiratory Center, Saitama, Japan
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12
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Costa Mello VL, Americano do Basil PEA. Fully independent validation of eleven prognostic scores predicting progression to critically ill condition in hospitalized patients with COVID-19. Braz J Infect Dis 2024; 28:103721. [PMID: 38331391 PMCID: PMC10861835 DOI: 10.1016/j.bjid.2024.103721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 12/27/2023] [Accepted: 01/24/2024] [Indexed: 02/10/2024] Open
Abstract
INTRODUCTION COVID-19 remains an important threat to global health and maintains the challenge of COVID-19 hospital care. To assist decision making regarding COVID-19 hospital care many instruments to predict COVID-19 progression to critical condition were developed and validated. OBJECTIVE To validate eleven COVID-19 progression prediction scores for critically ill hospitalized patients in a Brazilian population. METHODOLOGY Observational study with retrospective follow-up, including 301 adults confirmed for COVID-19 sequentially. Participants were admitted to non-critical units for treatment of the disease, between January and April 2021 and between September 2021 and February 2022. Eleven prognostic scores were applied using demographic, clinical, laboratory and imaging data collected in the first 48 of the hospital admission. The outcomes of greatest interest were as originally defined for each score. The analysis plan was to apply the instruments, estimate the outcome probability reproducing the original development/validation of each score, then to estimate performance measures (discrimination and calibration) and decision thresholds for risk classification. RESULTS The overall outcome prevalence was 41.8 % on 301 participants. There was a greater risk of the occurrence of the outcomes in older and male patients, and a linear trend with increasing comorbidities. Most of the patients studied were not immunized against COVID-19. Presence of concomitant bacterial infection and consolidation on imaging increased the risk of outcomes. College of London COVID-19 severity score and the 4C Mortality Score were the only with reasonable discrimination (ROC AUC 0.647 and 0.798 respectively) and calibration. The risk groups (low, intermediate and high) for 4C score were updated with the following thresholds: 0.239 and 0.318 (https://pedrobrasil.shinyapps.io/INDWELL/). CONCLUSION The 4C score showed the best discrimination and calibration performance among the tested instruments. We suggest different limits for risk groups. 4C score use could improve decision making and early therapeutic management at hospital care.
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Affiliation(s)
- Vinicius Lins Costa Mello
- Instituto Nacional de Infectologia Evandro Chagas - Fundação Oswaldo Cruz, Rio de Janeiro, RJ, Brazil
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13
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Tang L, Ding H, Zeng Q, Zhou R, Liu B, Huang X. Engineered Nanovesicles Expressing Bispecific Single Chain Variable Fragments to Protect against SARS-CoV-2 Infection. ACS Biomater Sci Eng 2023; 9:6783-6796. [PMID: 37969099 DOI: 10.1021/acsbiomaterials.3c01108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2023]
Abstract
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in high morbidity and mortality rates worldwide. Although the epidemic has been controlled in many areas and numerous patients have been successfully treated, the risk of reinfection persists due to the low neutralizing antibody titers and weak immune response. To provide long-term immune protection for infected patients, novel bispecific CB6/dendritic cell (DC)-specific intercellular adhesion molecule 3-grabbing nonintegrin (SIGN) nanovesicles (NVs) were constructed to target both the SARS-CoV-2 spike protein (S) and the DC receptors for virus neutralization and immune activation. Herein, we designed NVs expressing both CB6 and DC-SIGN single chain variable fragments (scFvs) on the surface to block SARS-CoV-2 invasion and activate DC function. Monophosphoryl lipid A (MPLA) was loaded into the CB6/DC-SIGN NVs as an adjuvant to promote this process. The CB6/DC-SIGN NVs prevented a pseudovirus expressing the S protein from infecting the target cells expressing high levels of angiotensin-converting enzyme 2 in vitro. Additionally, CB6/DC-SIGN NVs admixed with S-expressing pseudoviruses activated the DCs, which was promoted by the adjuvant MPLA loaded in the NVs. Using a mouse model, we also confirmed that the CB6/DC-SIGN NVs effectively improved the neutralizing antibody titer and inhibited the growth of tumors expressing the S protein after 3 weeks of treatment. This potential NV-based treatment not only exerts a blocking effect by binding the S protein in the short term but may also provide patients with long-term protection against secondary infections.
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Affiliation(s)
- Lantian Tang
- Center for Infection and Immunity and Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong 519000, China
| | - Hanxi Ding
- Center for Infection and Immunity and Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong 519000, China
| | - Qi Zeng
- Cancer Center, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, Guangdong, China
| | - Renjie Zhou
- Department of Emergency, Xinqiao Hospital, Army Medical University, 400037 Chongqing, China
| | - Bo Liu
- Department of Emergency, Xinqiao Hospital, Army Medical University, 400037 Chongqing, China
| | - Xi Huang
- Center for Infection and Immunity and Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong 519000, China
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14
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Montrucchio G, Balzani E, Sales G, Bolla C, Sarda C, Della Selva A, Perotto M, Pomero F, Ravera E, Rumbolo F, Callegari T, Fanelli V, Mengozzi G, Brazzi L. Critical and non-critical coronavirus disease 2019 patients: which is the most predictive biomarker for disease severity and outcome?: A multicentre prospective cohort study comparing mid-regional pro-adrenomedullin, inflammatory and immunological patterns. EUROPEAN JOURNAL OF ANAESTHESIOLOGY AND INTENSIVE CARE 2023; 2:e0039. [PMID: 39916726 PMCID: PMC11798374 DOI: 10.1097/ea9.0000000000000039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/09/2025]
Abstract
BACKGROUND Severe acute respiratory syndrome-coronavirus-2 in coronavirus disease 2019 (COVID-19) patients leads to a wide range of clinical manifestations. The evaluation of mid-regional pro-adrenomedullin (MR-proADM) as a prognostic biomarker in noncritical wards (NON-ICU) and intensive care units (ICU), may have a potential in predicting disease severity and outcomes. OBJECTIVE To assess the difference in the prognostic power of MR-proADM in NON-ICU wards and in ICUs in a prospective multicentre cohort study. DESIGN From January to July 2021, all adult COVID-19 patients requiring admission for more than 48 h. SETTING One primary centre and two secondary centre hospitals. PATIENTS One hundred and twenty-three ICU and 77 NON-ICU patients. INTERVENTION MR-proADM, lymphocyte subpopulations and immunoglobulins were measured within 48 h and on days 3 and 7. A Log-rank test was used to compare survival curves, using a MR-proADM cut-off value of 1.5 nmol l-1. The predictive ability for mortality was compared using the area under the curve and 95% confidence interval (CI) of different receiver-operating characteristic curves. MAIN OUTCOME MEASURES The first 48 h MR-proADM values were significantly higher in the ICU group (median value 1.10 [IQR, 0.80 to 1.73] pg ml-1 vs. 0.90 [0.70 to 1.20] pg ml-1, P = 0.020), and statistically significant changes were observed over time for MR-proADM, CD3+, CD4+ and CD56+. In univariate analysis, MR-proADM was the only biomarker that significantly predicted mortality (P = 0.006). The logistic regression model showed an odds ratio for mortality equal to 1.83 (95% CI, 1.08 to 3.37) P = 0.035 for MR-proADM, 1.37 (1.15 to 1.68) P = 0.001 for MuLBSTA and 1.11 (1.05 to 1.18) P less than 0.001 for SAPS II. CONCLUSION MR-proADM admission values and trends over time appear to be a suitable marker of illness severity and a patient's risk of mortality in both ICU and NON-ICU settings. Lymphocyte subpopulation dysfunction seems to play a role in defining the severity of COVID-19 but is limited to ICU setting. TRIAL REGISTRATION on clinicaltrials.gov, NCT04873388 registered on March 2020.
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Affiliation(s)
- Giorgia Montrucchio
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Eleonora Balzani
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Gabriele Sales
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Cesare Bolla
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Cristina Sarda
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Andrea Della Selva
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Massimo Perotto
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Fulvio Pomero
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Enrico Ravera
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Francesca Rumbolo
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Tiziana Callegari
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Vito Fanelli
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Giulio Mengozzi
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
| | - Luca Brazzi
- From the Department of Surgical Sciences, University of Turin (GM, EB, GS, VF, lB), Department of Anaesthesia, Critical Care and Emergency - Città Della Salute e Della Scienza Hospital, Turin (GM, GS, VF, LB), Unit of Infectious Diseases, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (CB, CS), Department of Emergency, Anesthesia and Critical Care Medicine (ADS, ER), Department of Emergency Medicine (MP), Department of Internal Medicine, Michele e Pietro Ferrero Hospital, Verduno (FP), Clinical Biochemistry Laboratory, Città Della Salute e Della Scienza Hospital, Torino (FR, GM), Clinical Biochemistry Laboratory, ASO SS. Antonio e Biagio e Cesare Arrigo, Alessandria (TC) and Department of Medical Sciences, University of Turin, Torino, Italy (GM)
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15
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de Santos Castro PÁ, Martín-Rodríguez F, Arribas LTP, Sánchez DZ, Sanz-García A, Del Águila TGV, Izquierdo PG, de Santos Sánchez S, Del Pozo Vegas C. Head-to-head comparison of six warning scores to predict mortality and clinical impairment in COVID-19 patients in emergency department. Intern Emerg Med 2023; 18:2385-2395. [PMID: 37493862 DOI: 10.1007/s11739-023-03381-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 07/17/2023] [Indexed: 07/27/2023]
Abstract
The aim was to evaluate the ability of six risk scores (4C, CURB65, SEIMC, mCHOSEN, QuickCSI, and NEWS2) to predict the outcome of patients with COVID-19 during the sixth pandemic wave in Spain. A retrospective observational study was performed to review the electronic medical records in patients ≥ 18 years of age who consulted consecutively in an emergency department with COVID-19 diagnosis throughout 2 months during the sixth pandemic wave. Clinical-epidemiological variables, comorbidities, and their respective outcomes, such as 30-day in-hospital mortality and clinical deterioration risk (a combined outcome considering: mechanical ventilation, intensive care unit admission, and/or 30-day in-hospital mortality), were calculated. The area under the curve for each risk score was calculated, and the resulting curves were compared by the Delong test, concluding with a decision curve analysis. A total of 626 patients (median age 79 years; 49.8% female) fulfilled the inclusion criteria. Two hundred and ninety-three patients (46.8%) had two or more comorbidities. Clinical deterioration risk criteria were present in 10.1% (63 cases), with a 30-day in-hospital mortality rate of 6.2% (39 cases). Comparison of the results showed that score 4C presented the best results for both outcome variables, with areas under the curve for mortality and clinical deterioration risk of 0.931 (95% CI 0.904-0.957) and 0.871 (95% CI 0.833-0.910) (both p < 0.001). The 4C Mortality Score proved to be the best score for predicting mortality or clinical deterioration risk among patients with COVID-19 attended in the emergency department in the following 30 days.
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Affiliation(s)
- Pedro Ángel de Santos Castro
- Servicio de Urgencias, Hospital Clínico Universitario de Valladolid, Gerencia Regional de Salud de Castilla Y León (SACYL), Valladolid, Spain
| | - Francisco Martín-Rodríguez
- Facultad de Medicina, Centro de Simulación Clínica Avanzada, Universidad de Valladolid, Avda. Ramón Y Cajal, 7, 47003, Valladolid, Spain.
- Unidad Móvil de Emergencias Valladolid I, Gerencia de Emergencias Sanitarias, Gerencia Regional de Salud de Castilla Y León (SACYL), Valladolid, Spain.
| | - Leyre Teresa Pinilla Arribas
- Servicio de Urgencias, Hospital Clínico Universitario de Valladolid, Gerencia Regional de Salud de Castilla Y León (SACYL), Valladolid, Spain
| | - Daniel Zalama Sánchez
- Servicio de Urgencias, Hospital Clínico Universitario de Valladolid, Gerencia Regional de Salud de Castilla Y León (SACYL), Valladolid, Spain
| | - Ancor Sanz-García
- Facultad de Ciencias de La Salud, Universidad de Castilla La Mancha, Avda. Real Fábrica de Seda, s/n, 45600, Talavera de La Reina, Toledo, Spain.
| | - Tony Giancarlo Vásquez Del Águila
- Servicio de Urgencias, Hospital Clínico Universitario de Valladolid, Gerencia Regional de Salud de Castilla Y León (SACYL), Valladolid, Spain
| | - Pablo González Izquierdo
- Servicio de Urgencias, Hospital Clínico Universitario de Valladolid, Gerencia Regional de Salud de Castilla Y León (SACYL), Valladolid, Spain
| | - Sara de Santos Sánchez
- Facultad de Medicina, Centro de Simulación Clínica Avanzada, Universidad de Valladolid, Avda. Ramón Y Cajal, 7, 47003, Valladolid, Spain
| | - Carlos Del Pozo Vegas
- Servicio de Urgencias, Hospital Clínico Universitario de Valladolid, Gerencia Regional de Salud de Castilla Y León (SACYL), Valladolid, Spain
- Facultad de Medicina, Centro de Simulación Clínica Avanzada, Universidad de Valladolid, Avda. Ramón Y Cajal, 7, 47003, Valladolid, Spain
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16
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Zhu X, Tian F, Li Y, Lu Q, Long Q, Long X, Cao D. High Prevalence of Respiratory Co-Infections and Risk Factors in COVID-19 Patients at Hospital Admission During an Epidemic Peak in China. Infect Drug Resist 2023; 16:6781-6793. [PMID: 37904830 PMCID: PMC10613409 DOI: 10.2147/idr.s435143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 10/18/2023] [Indexed: 11/01/2023] Open
Abstract
BACKGROUND Recent research highlights the contribution of co-infections to elevated disease severity and mortality among COVID-19 patients. Given China's decision to ease epidemic prevention policies in December 2022, a comprehensive exploration of the risks and characteristics of co-infections with respiratory pathogens becomes imperative. METHODS We conducted a retrospective analysis of 716 COVID-19 patients admitted to a primary hospital in China. The detection of twelve respiratory pathogens was conducted using qPCR, and the potential risk factors were analyzed through Cox regression analysis. RESULTS Within this cohort, 76.82% of cases exhibited co-infection involving eleven distinct pathogens. Among these, bacterial co-infections were observed in 74% of cases, with Streptococcus pneumoniae and Haemophilus influenzae emerging as the most prevalent bacterial co-infection agents. Additionally, 15% of cases presented with viral co-infections, predominantly involving influenza A virus and respiratory syncytial virus. Nevertheless, our investigation suggested that there might be some inappropriate antibiotic use in treatments. Furthermore, risk analysis unveiled dyspnea, hypoproteinemia, low lymphocyte counts, and co-infection with Mycoplasma pneumoniae as prominent risk factors for COVID-19 inpatients. CONCLUSION Our findings underscore a significant occurrence of co-infections among COVID-19 patients during the epidemic, emphasizing the need for enhanced antibiotic stewardship. Effective management strategies should encompass respiratory status, nutritional aspects, and vigilance towards co-infections involving M. pneumoniae during COVID-19 treatment. This study underscores the significance of comprehensive management protocols to address the multifaceted challenges presented by co-infections in COVID-19 patients.
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Affiliation(s)
- Xiaoying Zhu
- Medical College, Guangxi University, Nanning, Guangxi, People’s Republic of China
- Clinical Pathological Diagnosis & Research Center, the Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, People’s Republic of China
| | - Fengqin Tian
- Clinical Pathological Diagnosis & Research Center, the Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, People’s Republic of China
| | - Yulei Li
- Clinical Pathological Diagnosis & Research Center, the Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, People’s Republic of China
| | - Qunfeng Lu
- School of Medical Laboratory Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi, People’s Republic of China
| | - Qinqin Long
- Clinical Pathological Diagnosis & Research Center, the Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, People’s Republic of China
| | - Xidai Long
- Medical College, Guangxi University, Nanning, Guangxi, People’s Republic of China
- Clinical Pathological Diagnosis & Research Center, the Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, People’s Republic of China
| | - Demin Cao
- Clinical Pathological Diagnosis & Research Center, the Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, People’s Republic of China
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Larios Serrato V, Meza B, Gonzalez-Torres C, Gaytan-Cervantes J, González Ibarra J, Santacruz Tinoco CE, Anguiano Hernández YM, Martínez Miguel B, Cázarez Cortazar A, Sarquiz Martínez B, Alvarado Yaah JE, Mendoza Pérez AR, Palma Herrera JJ, García Soto LM, Chávez Rojas AI, Bravo Mateos G, Samano Marquez G, Grajales Muñiz C, Torres J. Diversity, composition, and networking of saliva microbiota distinguish the severity of COVID-19 episodes as revealed by an analysis of 16S rRNA variable V1-V3 region sequences. mSystems 2023; 8:e0106222. [PMID: 37310423 PMCID: PMC10470033 DOI: 10.1128/msystems.01062-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 04/17/2023] [Indexed: 06/14/2023] Open
Abstract
Studies on the role of the oral microbiome in SARS-CoV-2 infection and severity of the disease are limited. We aimed to characterize the bacterial communities present in the saliva of patients with varied COVID-19 severity to learn if there are differences in the characteristics of the microbiome among the clinical groups. We included 31 asymptomatic subjects with no previous COVID-19 infection or vaccination; 176 patients with mild respiratory symptoms, positive or negative for SARS-CoV-2 infection; 57 patients that required hospitalization because of severe COVID-19 with oxygen saturation below 92%, and 18 fatal cases of COVID-19. Saliva samples collected before any treatment were tested for SARS-CoV-2 by PCR. Oral microbiota in saliva was studied by amplification and sequencing of the V1-V3 variable regions of 16S gene using an Illumina MiSeq platform. We found significant changes in diversity, composition, and networking in saliva microbiota of patients with COVID-19, as well as patterns associated with severity of disease. The presence or abundance of several commensal species and opportunistic pathogens were associated with each clinical stage. Patterns of networking were also found associated with severity of disease: a highly regulated bacterial community (normonetting) was found in healthy people whereas poorly regulated populations (disnetting) were characteristic of severe cases. Characterization of microbiota in saliva may offer important clues in the pathogenesis of COVID-19 and may also identify potential markers for prognosis in the severity of the disease. IMPORTANCE SARS-CoV-2 infection is the most severe pandemic of humankind in the last hundred years. The outcome of the infection ranges from asymptomatic or mild to severe and even fatal cases, but reasons for this remain unknown. Microbes normally colonizing the respiratory tract form communities that may mitigate the transmission, symptoms, and severity of viral infections, but very little is known on the role of these microbial communities in the severity of COVID-19. We aimed to characterize the bacterial communities in saliva of patients with different severity of COVID-19 disease, from mild to fatal cases. Our results revealed clear differences in the composition and in the nature of interactions (networking) of the bacterial species present in the different clinical groups and show community-patterns associated with disease severity. Characterization of the microbial communities in saliva may offer important clues to learn ways COVID-19 patients may suffer from different disease severities.
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Affiliation(s)
- Violeta Larios Serrato
- Departamento de Bioquímica, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México, Mexico
| | - Beatriz Meza
- Universidad Autónoma de Baja California Sur, La Paz, Baja California Sur, Mexico
- Centro de Investigaciones Biológicas del Noroeste SC, La Paz, Baja California Sur, Mexico
- Unidad de Investigación Médica en Enfermedades Infecciosas, UMAE Pediatría, Centro Médico Nacional SXXI, IMSS, Torreón, Mexico
| | | | - Javier Gaytan-Cervantes
- Laboratorio de Secuenciación, División de Desarrollo de la Investigación, IMSS, Torreón, Mexico
| | - Joaquín González Ibarra
- División de Desarrollo de la Investigación en Salud, Coordinación de Investigación en Salud, IMSS, Torreón, Mexico
| | - Clara Esperanza Santacruz Tinoco
- División de Laboratorios Especializados, Coordinación de Calidad de Insumos y Laboratorios Especializados, IMSS, Torreón, Mexico
| | - Yu-Mei Anguiano Hernández
- División de Laboratorios Especializados, Coordinación de Calidad de Insumos y Laboratorios Especializados, IMSS, Torreón, Mexico
| | - Bernardo Martínez Miguel
- División de Laboratorios Especializados, Coordinación de Calidad de Insumos y Laboratorios Especializados, IMSS, Torreón, Mexico
| | - Allison Cázarez Cortazar
- División de Laboratorios Especializados, Coordinación de Calidad de Insumos y Laboratorios Especializados, IMSS, Torreón, Mexico
| | - Brenda Sarquiz Martínez
- División de Laboratorios Especializados, Coordinación de Calidad de Insumos y Laboratorios Especializados, IMSS, Torreón, Mexico
| | - Julio Elias Alvarado Yaah
- División de Laboratorios Especializados, Coordinación de Calidad de Insumos y Laboratorios Especializados, IMSS, Torreón, Mexico
| | | | | | | | | | | | | | | | - Javier Torres
- Unidad de Investigación Médica en Enfermedades Infecciosas, UMAE Pediatría, Centro Médico Nacional SXXI, IMSS, Torreón, Mexico
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18
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Cong L, Chen C, Mao S, Han Z, Zhu Z, Li Y. Intestinal bacteria-a powerful weapon for fungal infections treatment. Front Cell Infect Microbiol 2023; 13:1187831. [PMID: 37333850 PMCID: PMC10272564 DOI: 10.3389/fcimb.2023.1187831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 05/22/2023] [Indexed: 06/20/2023] Open
Abstract
The morbidity and mortality of invasive fungal infections are rising gradually. In recent years, fungi have quietly evolved stronger defense capabilities and increased resistance to antibiotics, posing huge challenges to maintaining physical health. Therefore, developing new drugs and strategies to combat these invasive fungi is crucial. There are a large number of microorganisms in the intestinal tract of mammals, collectively referred to as intestinal microbiota. At the same time, these native microorganisms co-evolve with their hosts in symbiotic relationship. Recent researches have shown that some probiotics and intestinal symbiotic bacteria can inhibit the invasion and colonization of fungi. In this paper, we review the mechanism of some intestinal bacteria affecting the growth and invasion of fungi by targeting the virulence factors, quorum sensing system, secreting active metabolites or regulating the host anti-fungal immune response, so as to provide new strategies for resisting invasive fungal infection.
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Affiliation(s)
- Liu Cong
- School of Medical Technology, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Chaoqun Chen
- School of Medical Technology, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Shanshan Mao
- School of Medical Technology, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Zibing Han
- Department of Genetics, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Zuobin Zhu
- Department of Genetics, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Ying Li
- School of Medical Technology, Xuzhou Medical University, Xuzhou, Jiangsu, China
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19
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Lan C, Chen YC, Chang YI, Chuang PC. Impact of COVID-19 Outbreak on Influenza and Pneumococcal Vaccination Uptake: A Multi-Center Retrospective Study. Vaccines (Basel) 2023; 11:986. [PMID: 37243090 PMCID: PMC10223787 DOI: 10.3390/vaccines11050986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 05/10/2023] [Accepted: 05/11/2023] [Indexed: 05/28/2023] Open
Abstract
During the coronavirus disease 2019 (COVID-19) pandemic, global vaccination efforts declined due to the burden on health systems and community resistance to epidemic control measures. Influenza and pneumococcal vaccines have been recommended for vulnerable populations to prevent severe pneumonia. We investigated community response towards influenza and pneumococcal vaccines (pneumococcal conjugate vaccine and pneumococcal polysaccharide vaccine) after the COVID-19 outbreak in Taiwan. We retrospectively included adults who visited Chang Gung Memorial Hospital (CGMH) institutions for influenza or pneumococcal vaccination from January 2018 to December 2021. The first case of COVID-19 in Taiwan was detected in January 2020; therefore, in this study, hospitalized cases from January 2018 to December 2019 were defined as "before COVID-19 outbreak," and hospitalized cases from January 2020 to December 2021 were defined as "after COVID-19 outbreak". A total of 105,386 adults were enrolled in the study. An increase in influenza vaccination (n = 33,139 vs. n = 62,634) and pneumococcal vaccination (n = 3035 vs. n = 4260) were observed after the COVID-19 outbreak. In addition, there was an increased willingness to receive both influenza and pneumococcal vaccinations among women, adults without underlying disease and younger adults. The COVID-19 pandemic may have increased awareness of the importance of vaccination in Taiwan.
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Affiliation(s)
- Chieh Lan
- Department of Family Medicine, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung 83301, Taiwan;
| | - Yi-Chun Chen
- Division of Infectious Diseases, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung 83301, Taiwan;
| | - Ye-In Chang
- Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan;
| | - Po-Chun Chuang
- Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan;
- Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung 83301, Taiwan
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20
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Homberg T, Hernández PM, Pérez-Tapia SM, Jiménez-Martínez MC. [Validation of a symptom scale for COVID-19 patients in ambulatory care]. REVISTA MEDICA DEL INSTITUTO MEXICANO DEL SEGURO SOCIAL 2023; 61:348-355. [PMID: 37216678 PMCID: PMC10437239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 12/30/2022] [Indexed: 05/24/2023]
Abstract
Background A symptom scale can be useful for the standardization of clinical evaluations and follow-up of COVID-19 patients in ambultaroy care. Scale development should be accompanied by an assessment of its reliablility and validity. Objective To develop and measure the psychometric characteristics of a COVID-19 symptom scale to be answered by either healthcare personnel or adult patients in ambulatory care. Material and methods The scale was developed by an expert panel using the Delphi method. We evaluated inter-rater reliability, where we defined a good correlation if Spearman's Rho was ≥ 0.8; test-retest, where we defined a good correlation if Spearman's Rho was ≥ 0.7; factor analysis using principal component methodology; and discriminant validity using Mann-Whitney's U test. A p < 0.05 was considered statistically significant. Results We obtained an 8 symptom scale, each symptom is scored from 0-4, with a total minimum score of 0 and a maximum of 32 points. Inter-rater reliability was 0.995 (n = 31), test-retest showed correlation of 0.88 (n = 22), factor analysis detected 4 factors (n = 40) and discriminant capacity of healthy versus sick adults was significant (p < 0.0001, n = 60). Conclusions We obtained a reliable and valid Spanish (from Mexico) symptom scale for COVID-19 ambulatory care, answerable by patients and health care staff.
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Affiliation(s)
- Toni Homberg
- Instituto Politécnico Nacional, Escuela Nacional de Ciencias Biológicas, Unidad de Servicios Externos e Investigación Clínica. Ciudad de México, MéxicoInstituto Politécnico NacionalMéxico
| | - Pedro Martín Hernández
- Universidad Nacional Autónoma de México, Facultad de Ciencias, Departamento de Bioestadística. Ciudad de México, México Universidad Nacional Autónoma de MéxicoMéxico
| | - Sonia Mayra Pérez-Tapia
- Instituto Politécnico Nacional, Escuela Nacional de Ciencias Biológicas, Unidad de Innovación y Desarrollo en Bioterapéuticos. Ciudad de México, MéxicoInstituto Politécnico NacionalMéxico
| | - María C Jiménez-Martínez
- Universidad Nacional Autónoma de México, Facultad de Medicina, Departamento de Bioquímica. Ciudad de México, MéxicoUniversidad Nacional Autónoma de MéxicoMéxico
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Muzahid NH, Hussain MH, Huët MAL, Dwiyanto J, Su TT, Reidpath D, Mustapha F, Ayub Q, Tan HS, Rahman S. Molecular characterization and comparative genomic analysis of Acinetobacter baumannii isolated from the community and the hospital: an epidemiological study in Segamat, Malaysia. Microb Genom 2023; 9. [PMID: 37018035 PMCID: PMC10210948 DOI: 10.1099/mgen.0.000977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2023] Open
Abstract
Acinetobacter baumannii is a common cause of multidrug-resistant (MDR) nosocomial infections around the world. However, little is known about the persistence and dynamics of A. baumannii in a healthy community. This study investigated the role of the community as a prospective reservoir for A. baumannii and explored possible links between hospital and community isolates. A total of 12 independent A. baumannii strains were isolated from human faecal samples from the community in Segamat, Malaysia, in 2018 and 2019. Another 15 were obtained in 2020 from patients at the co-located tertiary public hospital. The antimicrobial resistance profile and biofilm formation ability were analysed, and the relatedness of community and hospital isolates was determined using whole-genome sequencing (WGS). Antibiotic profile analysis revealed that 12 out of 15 hospital isolates were MDR, but none of the community isolates were MDR. However, phylogenetic analysis based on single-nucleotide polymorphisms (SNPs) and a pangenome analysis of core genes showed clustering between four community and two hospital strains. Such clustering of strains from two different settings based on their genomes suggests that these strains could persist in both. WGS revealed 41 potential resistance genes on average in the hospital strains, but fewer (n=32) were detected in the community strains. In contrast, 68 virulence genes were commonly seen in strains from both sources. This study highlights the possible transmission threat to public health posed by virulent A. baumannii present in the gut of asymptomatic individuals in the community.
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Affiliation(s)
- Nazmul Hasan Muzahid
- School of Science, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia
| | - Md Hamed Hussain
- School of Science, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia
| | | | - Jacky Dwiyanto
- School of Science, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia
| | - Tin Tin Su
- South East Asia Community Observatory (SEACO) and Global Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Bandar Sunway, 47500, Subang Jaya, Selangor, Malaysia
| | - Daniel Reidpath
- South East Asia Community Observatory (SEACO) and Global Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Bandar Sunway, 47500, Subang Jaya, Selangor, Malaysia
| | - Faizah Mustapha
- Department of Pathology, Hospital Segamat, Jalan Genuang, Bandar Putra, 85000, Segamat, Johor, Malaysia
| | - Qasim Ayub
- School of Science, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia
- Monash University Malaysia Genomics Facility, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia
- Tropical Medicine and Biology Multidisciplinary Platform, Monash University Malaysia, Bandar Sunway, 47500, Subang Jaya, Selangor, Malaysia
| | - Hock Siew Tan
- School of Science, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia
- Tropical Medicine and Biology Multidisciplinary Platform, Monash University Malaysia, Bandar Sunway, 47500, Subang Jaya, Selangor, Malaysia
| | - Sadequr Rahman
- School of Science, Monash University Malaysia, 47500, Bandar Sunway, Selangor Darul Ehsan, Malaysia
- Tropical Medicine and Biology Multidisciplinary Platform, Monash University Malaysia, Bandar Sunway, 47500, Subang Jaya, Selangor, Malaysia
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22
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Christian GJ, Meenakumari R, Shanthimalar R, Sankar G, Ravichandran VM, Elansekaran S, Ramamurthy M, Srinivasan V, Rajalakshmi E, Boopathi K, Vennila K, Nijavizhi M, Shakthi Paargavi A, Aruldevi S, Priyanka S, Gajalakshmi G. Safety and efficacy of Siddha management as adjuvant care for COVID-19 patients admitted in a tertiary care hospital - An open-label, proof-of-concept Randomized Controlled Trial. J Ayurveda Integr Med 2023; 14:100706. [PMID: 37197717 PMCID: PMC10086104 DOI: 10.1016/j.jaim.2023.100706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 04/04/2023] [Accepted: 04/05/2023] [Indexed: 05/19/2023] Open
Abstract
Background COVID-19 resulted in loss of human lives owing to respiratory failure caused by dysregulated immune system. Though many treatments are evaluated, the most appropriate is yet to be established. Objective To determine the safety and efficacy of Siddha add-on therapy in COVID -19 in terms of accelerated recovery, reduced hospital stay & mortality and follow up assessment of post discharge status until 90 days as compared to the Standard Care management. Methods In a randomized, controlled, single-center, open-label trial conducted on 200 hospitalized COVID-19 patients, they were allocated equally to be treated with add-on Siddha regimen with Standard care or only Standard care. Standard care was in accordance to the Government norms. Recovery was defined as amelioration of symptoms, viral clearance and attaining SpO2 > 94% in room air indicating the derived score of zero on WHO clinical progression scale. The primary and secondary end points were accelerated recovery (≤ 7 days) and mortality comparison between the groups respectively. Also, disease duration, length of hospital stays and laboratory parameters were assessed for safety and efficacy. Patients were followed through for 90 days after admission. Results In this study the accelerated recovery was 59.0% and 27.0% in treatment and control groups (ITT analyses) (p < 0.001) respectively and Odds for it were four times higher in the treatment group (OR: 3.9; 95% CI: 1.9, 8.0). The estimated median time for recovery in the treatment group was 7 days (95% CI: 6.0, 8.0; p=0.003) and 10 days (95% CI: 8.7, 11.3) in control. Hazard ratio for death in control was 2.3 times that of treatment group. No adverse reactions or alarming laboratory values were observed in response to intervention. In Severe COVID treatment group (n=80), mortality was 15.0% and 39.5% in control (n=81). The COVID stage progression was 65% less in test group. Mortality during treatment and 90 days follow up in Severe COVID patients were 12 (15%) and 35 (43.2%) in treatment and control groups respectively. Conclusion The selected Siddha regimen when co-administered with Standard of Care have demonstrated that they can synergistically act to improve oxygenation status of patients, enhance the recovery rate from COVID-19 and reduce the mortality better when compared to administration of only Standard of Care. Clinical Trial Registry of India CTRI/2020/06/025768 Registered on: 09/06/2020.
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Affiliation(s)
| | - Ramasamy Meenakumari
- National Institute of Siddha, Tambaram Sanatorium, Chennai 47, Tamil Nadu, India
| | - Ramalingam Shanthimalar
- Government Chengalpattu Medical College Hospital, Directorate of Medical Education, Chengalpattu, Chennai, 603001, Tamil Nadu, India
| | - Ganesan Sankar
- Ezhil Siddha Hospital, Chengalpattu 603001, Tamil Nadu, India
| | - Vadugam Muthusamy Ravichandran
- SKM Siddha and Ayurveda Company (India) Private Limited, Saminathapuram Post, Modakkurichi, 638 104, Erode District, Tamil Nadu, India
| | | | - Murugan Ramamurthy
- National Institute of Siddha, Tambaram Sanatorium, Chennai 47, Tamil Nadu, India
| | | | | | - Kangusamy Boopathi
- ICMR-National Institute of Epidemiology, Ayapakkam, Chennai, Tamil Nadu, India
| | - Kesavan Vennila
- National Institute of Siddha, Tambaram Sanatorium, Chennai 47, Tamil Nadu, India
| | | | | | - Selvam Aruldevi
- National Institute of Siddha, Tambaram Sanatorium, Chennai 47, Tamil Nadu, India
| | - Sekaran Priyanka
- National Institute of Siddha, Tambaram Sanatorium, Chennai 47, Tamil Nadu, India
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Buyukaydin B, Karaaslan T, Uysal O. Evaluation of risk scores as predictors of mortality and hospital length of stay for older COVID-19 patients. Aging Med (Milton) 2023; 6:56-62. [PMID: 36911090 PMCID: PMC10000259 DOI: 10.1002/agm2.12238] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 12/12/2022] [Accepted: 12/20/2022] [Indexed: 01/12/2023] Open
Abstract
Objective This study was intended to research the sensitivity of the Charlson Comorbidity Index (CCI), COVID-GRAM, and MuLBSTA risk scores for hospital length of stay (LOS) and mortality in older patients hospitalized with coronavirus disease 2019 (COVID-19). Methods A total of 217 patients (119 women) were included in the study. The first clinical signs, comorbidities, laboratory and radiology findings, and hospital LOS were recorded for each patient. The CCI, COVID-GRAM, and MuLBSTA risk scores were calculated, and their sensitivities for hospital LOS and mortality were evaluated using receiver operating characteristic (ROC) curve analysis. Results Of the hospitalized patients, 59 (27.2%) were followed in the intensive care unit, and mortality developed in 44 (20.3%). The CCI positively correlated with COVID-GRAM and MuLBSTA scores (P < 0.001). COVID-GRAM and MuLBSTA results correlated with LOS and mortality (P < 0.001). According to the ROC curve analysis, the cutoff points for mortality were 5 for CCI, 169 for COVID-GRAM, and 9 for MuLBSTA. Conclusion Older patients with comorbidities are the major risk group for severe COVID-19. COVID-GRAM and MuLBSTA scores appear to be sensitive and reliable mortality indicators for these patients.
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Affiliation(s)
- Banu Buyukaydin
- Department of Internal MedicineBezmialem Vakif University School of MedicineIstanbulTurkey
| | - Tahsin Karaaslan
- Department of NephrologyIstanbul Medeniyet University School of MedicineIstanbulTurkey
| | - Omer Uysal
- Department of BiostatisticsIstanbul University Cerrahpasa School of MedicineIstanbulTurkey
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Lavrinenko A, Kolesnichenko S, Kadyrova I, Turmukhambetova A, Akhmaltdinova L, Klyuyev D. Bacterial Co-Infections and Antimicrobial Resistance in Patients Hospitalized with Suspected or Confirmed COVID-19 Pneumonia in Kazakhstan. Pathogens 2023; 12:pathogens12030370. [PMID: 36986292 PMCID: PMC10052929 DOI: 10.3390/pathogens12030370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/17/2023] [Accepted: 02/20/2023] [Indexed: 02/26/2023] Open
Abstract
Our study was carried out to characterize respiratory tract microbiota in patients with “COVID-like pneumonia” in Kazakhstan and analyze differences between COVID-19 positive and negative groups. Sputum samples were collected from hospitalized patients, ≥18 years old, in the three cities in Kazakhstan with the highest COVID-19 burden in July 2020. Isolates were identified by MALDI-TOF MS. Susceptibility testing was performed by disk diffusion. We used SPSS 26 and MedCalc 19 for statistical analysis. Among 209 patients with pneumonia, the median age was 62 years and 55% were male. RT-PCR-confirmed SARS-CoV-2 cases were found in 40% of patients, and 46% had a bacterial co-infection. Co-infection was not associated with SARS-CoV-2 RT-PCR test results, but antibiotic use was. The most frequent bacteria were Klebsiella pneumoniae (23%), Escherichia coli (12%), and Acinetobacter baumannii (11%). Notably, 68% of Klebsiella pneumoniae had phenotypic evidence of extended-spectrum beta-lactamases in disk diffusion assays, 87% of Acinetobacter baumannii exhibited resistance to beta-lactams, and >50% of E. coli strains had evidence of ESBL production and 64% were resistant to fluoroquinolones. Patients with a bacterial co-infection had a higher proportion of severe disease than those without a co-infection. The results reinforce the importance of using appropriate targeted antibiotics and effective infection control practices to prevent the spread of resistant nosocomial infections.
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Affiliation(s)
- Alyona Lavrinenko
- Research Laboratory, Karaganda Medical University, Karaganda 100008, Kazakhstan
| | - Svetlana Kolesnichenko
- Research Laboratory, Karaganda Medical University, Karaganda 100008, Kazakhstan
- Correspondence: ; Tel.: +7-702-599-0225
| | - Irina Kadyrova
- Research Laboratory, Karaganda Medical University, Karaganda 100008, Kazakhstan
| | - Anar Turmukhambetova
- Management Department, Karaganda Medical University, Karaganda 100008, Kazakhstan
| | | | - Dmitriy Klyuyev
- Research Laboratory, Karaganda Medical University, Karaganda 100008, Kazakhstan
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The Circulation of Common Respiratory Viruses and Their Co-infection with Severe Acute Respiratory Syndrome Coronavirus 2 Before and After Coronavirus Disease of 2019 Vaccination. Jundishapur J Microbiol 2023. [DOI: 10.5812/jjm-133326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2023] Open
Abstract
Background: Respiratory viruses play important roles in respiratory tract infections; they are the major cause of diseases such as the common cold, bronchiolitis, pneumonia, etc., in humans that circulate more often in the cold seasons. During the COVID-19 pandemic, many strict public health measures, such as hand hygiene, the use of face masks, social distancing, and quarantines, were implemented worldwide to control the pandemic. Besides controlling the COVID-19 pandemic, these introduced measures might change the spread of other common respiratory viruses. Moreover, with COVID-19 vaccination and reducing public health protocols, the circulation of other respiratory viruses probably increases in the community. Objectives: This study aims to explore changes in the circulation pattern of common respiratory viruses during the COVID-19 pandemic. Methods: In the present study, we evaluated the circulation of seven common respiratory viruses (influenza viruses A and B, rhinovirus, and seasonal human Coronaviruses (229E, NL63, OC43, and HKU1) and their co-infection with SARS-CoV-2 in suspected cases of COVID-19 in two time periods before and after COVID-19 vaccination. Clinical nasopharyngeal swabs of 400 suspected cases of COVID-19 were tested for SARS-CoV-2 and seven common respiratory viruses by reverse transcription real-time polymerase chain reaction. Results: Our results showed common respiratory viruses were detected only in 10% and 8% of SARS-CoV-2-positive samples before and after vaccination, respectively, in which there were not any significant differences between them (P-value = 0.14). Moreover, common viral respiratory infections were found only in 12% and 32% of SARS-CoV-2-negative specimens before and after vaccination, respectively, in which there was a significant difference between them (P-value = 0.041). Conclusions: Our data showed a low rate of co-infection of other respiratory viruses with SARS-CoV-2 at both durations, before and after COVID-19 vaccination. Moreover, the circulation of common respiratory viruses before the COVID-19 vaccination was lower, probably due to non-pharmaceutical interventions (NPI), while virus activity (especially influenza virus A) was significantly increased after COVID-19 vaccination with reducing strict public health measures.
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Pallarès N, Tebé C, Abelenda-Alonso G, Rombauts A, Oriol I, Simonetti AF, Rodríguez-Molinero A, Izquierdo E, Díaz-Brito V, Molist G, Gómez Melis G, Carratalà J, Videla S. Characteristics and Outcomes by Ceiling of Care of Subjects Hospitalized with COVID-19 During Four Waves of the Pandemic in a Metropolitan Area: A Multicenter Cohort Study. Infect Dis Ther 2023; 12:273-289. [PMID: 36495405 PMCID: PMC9736710 DOI: 10.1007/s40121-022-00705-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 09/26/2022] [Indexed: 12/14/2022] Open
Abstract
INTRODUCTION The profiles of patients with COVID-19 have been widely studied, but little is known about differences in baseline characteristics and in outcomes between subjects with a ceiling of care assigned at hospital admission and subjects without a ceiling of care. The aim of this study is to compare, by ceiling of care, clinical features and outcomes of hospitalized subjects during four waves of COVID-19 in a metropolitan area in Catalonia. METHODS Observational study conducted during the first (March-April 2020), second (October-November 2020), third (January-February 2021), and fourth wave (July-August 2021) of COVID-19 in five centers of Catalonia. All subjects were adults (> 18 years old) hospitalized with a proven SARS-CoV-2 infection and with therapeutic ceiling of care assessed by the attending physician at hospital admission. RESULTS A total of 5813 subjects were analyzed. Subjects with a ceiling of care were mainly older (difference in median age of 20 years), with more comorbidities (Charlson index 3 points higher) and with fewer clinical signs at baseline than patients without a ceiling of care. Some features of their clinical profiles changed among waves. There were differences in treatments received during hospital admission across waves, but not between subjects with and without a ceiling of care. Subjects with a ceiling of care had a death incidence more than four times the death incidence of subjects a without a ceiling of care (risk ratio (RR) ranging from 3.5 in the first wave to almost 6 in the third and fourth). Incidence of severe pneumonia and complications for subjects with a ceiling of care was around 1.5 times the incidence in subjects without a ceiling of care. DISCUSSION Analysis of hospitalized subjects with SARS-CoV-2 infection should be stratified according to therapeutic ceiling of care to avoid bias and outcome misestimation.
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Affiliation(s)
- Natàlia Pallarès
- grid.417656.7Biostatistics Unit of the Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Avinguda de la Granvia de l’Hospitalet, 199, 08908 Barcelona, Spain ,grid.5841.80000 0004 1937 0247Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Cristian Tebé
- grid.417656.7Biostatistics Unit of the Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Avinguda de la Granvia de l’Hospitalet, 199, 08908 Barcelona, Spain ,grid.5841.80000 0004 1937 0247Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Gabriela Abelenda-Alonso
- grid.411129.e0000 0000 8836 0780Department of Infectious Diseases, Bellvitge University Hospital, Barcelona, Spain ,grid.418284.30000 0004 0427 2257Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain
| | - Alexander Rombauts
- grid.411129.e0000 0000 8836 0780Department of Infectious Diseases, Bellvitge University Hospital, Barcelona, Spain ,grid.418284.30000 0004 0427 2257Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain
| | - Isabel Oriol
- grid.5841.80000 0004 1937 0247Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain ,grid.418284.30000 0004 0427 2257Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain ,Department of Internal Medicine, Consorci Sanitari Integral, Barcelona, Spain
| | - Antonella F. Simonetti
- grid.413448.e0000 0000 9314 1427CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain ,Department of Internal Medicine, Consorci Sanitari Alt Penedès Garraf, Barcelona, Spain
| | | | | | - Vicens Díaz-Brito
- grid.466982.70000 0004 1771 0789Department Infectious Diseases, Parc Sanitari Sant Joan de Deu, Sant Boi de Llobregat, Barcelona, Spain
| | - Gemma Molist
- grid.417656.7Biostatistics Unit of the Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Avinguda de la Granvia de l’Hospitalet, 199, 08908 Barcelona, Spain
| | - Guadalupe Gómez Melis
- grid.6835.80000 0004 1937 028XDepartment of Statistics and Operations Research, Universitat Politècnica de Catalunya/Barcelonatech, Barcelona, Spain
| | - Jordi Carratalà
- grid.5841.80000 0004 1937 0247Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain ,grid.411129.e0000 0000 8836 0780Department of Infectious Diseases, Bellvitge University Hospital, Barcelona, Spain ,grid.418284.30000 0004 0427 2257Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Sebastián Videla
- grid.411129.e0000 0000 8836 0780Department of Clinical Pharmacology, Bellvitge University Hospital, Barcelona, Spain ,grid.5841.80000 0004 1937 0247Department of Pathology and Experimental Therapeutics, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
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Wu X, Sun T, Cai Y, Zhai T, Liu Y, Gu S, Zhou Y, Zhan Q. Clinical characteristics and outcomes of immunocompromised patients with severe community-acquired pneumonia: A single-center retrospective cohort study. Front Public Health 2023; 11:1070581. [PMID: 36875372 PMCID: PMC9975557 DOI: 10.3389/fpubh.2023.1070581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Accepted: 01/25/2023] [Indexed: 02/17/2023] Open
Abstract
Background Immunocompromised patients with severe community-acquired pneumonia (SCAP) warrant special attention because they comprise a growing proportion of patients and tend to have poor clinical outcomes. The objective of this study was to compare the characteristics and outcomes of immunocompromised and immunocompetent patients with SCAP, and to investigate the risk factors for mortality in these patients. Methods We conducted retrospective observational cohort study of patients aged ≥18 years admitted to the intensive care unit (ICU) of an academic tertiary hospital with SCAP between January 2017 and December 2019 and compared the clinical characteristics and outcomes of immunocompromised and immunocompetent patients. Results Among the 393 patients, 119 (30.3%) were immunocompromised. Corticosteroid (51.2%) and immunosuppressive drug (23.5%) therapies were the most common causes. Compared to immunocompetent patients, immunocompromised patients had a higher frequency of polymicrobial infection (56.6 vs. 27.5%, P < 0.001), early mortality (within 7 days) (26.1 vs. 13.1%, P = 0.002), and ICU mortality (49.6 vs. 37.6%, P = 0.027). The pathogen distributions differed between immunocompromised and immunocompetent patients. Among immunocompromised patients, Pneumocystis jirovecii and cytomegalovirus were the most common pathogens. Immunocompromised status (OR: 2.043, 95% CI: 1.114-3.748, P = 0.021) was an independent risk factor for ICU mortality. Independent risk factors for ICU mortality in immunocompromised patients included age ≥ 65 years (odds ratio [OR]: 9.098, 95% confidence interval [CI]: 1.472-56.234, P = 0.018), SOFA score [OR: 1.338, 95% CI: 1.048-1.708, P = 0.019), lymphocyte count < 0.8 × 109/L (OR: 6.640, 95% CI: 1.463-30.141, P = 0.014), D-dimer level (OR: 1.160, 95% CI: 1.013-1.329, P = 0.032), FiO2 > 0.7 (OR: 10.228, 95% CI: 1.992-52.531, P = 0.005), and lactate level (OR: 4.849, 95% CI: 1.701-13.825, P = 0.003). Conclusions Immunocompromised patients with SCAP have distinct clinical characteristics and risk factors that should be considered in their clinical evaluation and management.
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Affiliation(s)
- Xiaojing Wu
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Ting Sun
- Capital Medical University, China-Japan Friendship School of Clinical Medicine, Beijing, China
| | - Ying Cai
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Tianshu Zhai
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Yijie Liu
- Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Sichao Gu
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Yun Zhou
- Department of Laboratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Qingyuan Zhan
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.,Capital Medical University, China-Japan Friendship School of Clinical Medicine, Beijing, China
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Montrucchio G, Sales G, Balzani E, Lombardo D, Giaccone A, Cantù G, D'Antonio G, Rumbolo F, Corcione S, Simonetti U, Bonetto C, Zanierato M, Fanelli V, Filippini C, Mengozzi G, Brazzi L. Effectiveness of mid-regional pro-adrenomedullin, compared to other biomarkers (including lymphocyte subpopulations and immunoglobulins), as a prognostic biomarker in COVID-19 critically ill patients: New evidence from a 15-month observational prospective study. Front Med (Lausanne) 2023; 10:1122367. [PMID: 37035317 PMCID: PMC10080079 DOI: 10.3389/fmed.2023.1122367] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 02/20/2023] [Indexed: 04/11/2023] Open
Abstract
Background Mid-regional pro-adrenomedullin (MR-proADM), an endothelium-related peptide, is a predictor of death and multi-organ failure in respiratory infections and sepsis and seems to be effective in identifying COVID-19 severe forms. The study aims to evaluate the effectiveness of MR-proADM in comparison to routine inflammatory biomarkers, lymphocyte subpopulations, and immunoglobulin (Ig) at an intensive care unit (ICU) admission and over time in predicting mortality in patients with severe COVID-19. Methods All adult patients with COVID-19 pneumonia admitted between March 2020 and June 2021 in the ICUs of a university hospital in Italy were enrolled. MR-proADM, lymphocyte subpopulations, Ig, and routine laboratory tests were measured within 48 h and on days 3 and 7. The log-rank test was used to compare survival curves with MR-proADM cutoff value of >1.5 nmol/L. Predictive ability was compared using the area under the curve (AUC) and 95% confidence interval (CI) of different receiver-operating characteristic curves. Results A total of 209 patients, with high clinical severity [SOFA 7, IQR 4-9; SAPS II 52, IQR 41-59; median viral pneumonia mortality score (MuLBSTA)-11, IQR 9-13] were enrolled. ICU and overall mortality were 55.5 and 60.8%, respectively. Procalcitonin, lactate dehydrogenase, D-dimer, the N-terminal prohormone of brain natriuretic peptide, myoglobin, troponin, neutrophil count, lymphocyte count, and natural killer lymphocyte count were significantly different between survivors and non-survivors, while lymphocyte subpopulations and Ig were not different in the two groups. MR-proADM was significantly higher in non-survivors (1.17 ± 0.73 vs. 2.31 ± 2.63, p < 0.0001). A value of >1.5 nmol/L was an independent risk factor for mortality at day 28 [odds ratio of 1.9 (95% CI: 1.220-3.060)] after adjusting for age, lactate at admission, SOFA, MuLBSTA, superinfections, cardiovascular disease, and respiratory disease. On days 3 and 7 of the ICU stay, the MR-proADM trend evaluated within 48 h of admission maintained a correlation with mortality (p < 0.0001). Compared to all other biomarkers considered, the MR-proADM value within 48 h had the best accuracy in predicting mortality at day 28 [AUC = 0.695 (95% CI: 0.624-0.759)]. Conclusion MR-proADM seems to be the best biomarker for the stratification of mortality risk in critically ill patients with COVID-19. The Ig levels and lymphocyte subpopulations (except for natural killers) seem not to be correlated with mortality. Larger, multicentric studies are needed to confirm these findings.
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Affiliation(s)
- Giorgia Montrucchio
- Department of Surgical Sciences, University of Turin, Turin, Italy
- Department of Anesthesia, Critical Care and Emergency, “Città della Salute e della Scienza” Hospital, Turin, Italy
- *Correspondence: Giorgia Montrucchio
| | - Gabriele Sales
- Department of Surgical Sciences, University of Turin, Turin, Italy
- Department of Anesthesia, Critical Care and Emergency, “Città della Salute e della Scienza” Hospital, Turin, Italy
| | - Eleonora Balzani
- Department of Surgical Sciences, University of Turin, Turin, Italy
| | - Davide Lombardo
- Department of Surgical Sciences, University of Turin, Turin, Italy
| | - Alice Giaccone
- Department of Surgical Sciences, University of Turin, Turin, Italy
| | - Giulia Cantù
- Department of Surgical Sciences, University of Turin, Turin, Italy
| | - Giulia D'Antonio
- Department of Surgical Sciences, University of Turin, Turin, Italy
| | - Francesca Rumbolo
- Clinical Biochemistry Laboratory, Department of Laboratory Medicine, “Città della Salute e della Scienza” Hospital, Turin, Italy
| | - Silvia Corcione
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Umberto Simonetti
- Department of Anesthesia, Critical Care and Emergency, “Città della Salute e della Scienza” Hospital, Turin, Italy
| | - Chiara Bonetto
- Department of Anesthesia, Critical Care and Emergency, “Città della Salute e della Scienza” Hospital, Turin, Italy
| | - Marinella Zanierato
- Department of Anesthesia, Critical Care and Emergency, “Città della Salute e della Scienza” Hospital, Turin, Italy
| | - Vito Fanelli
- Department of Surgical Sciences, University of Turin, Turin, Italy
- Department of Anesthesia, Critical Care and Emergency, “Città della Salute e della Scienza” Hospital, Turin, Italy
| | | | - Giulio Mengozzi
- Clinical Biochemistry Laboratory, Department of Laboratory Medicine, “Città della Salute e della Scienza” Hospital, Turin, Italy
| | - Luca Brazzi
- Department of Surgical Sciences, University of Turin, Turin, Italy
- Department of Anesthesia, Critical Care and Emergency, “Città della Salute e della Scienza” Hospital, Turin, Italy
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Yu J, Li H, Jia J, Huang Z, Liu S, Zheng Y, Mu S, Deng X, Zou X, Wang Y, Shang X, Cui D, Huang L, Feng X, Liu WJ, Cao B. Pandemic influenza A (H1N1) virus causes abortive infection of primary human T cells. Emerg Microbes Infect 2022; 11:1191-1204. [PMID: 35317717 PMCID: PMC9045768 DOI: 10.1080/22221751.2022.2056523] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 03/17/2022] [Indexed: 01/20/2023]
Abstract
Influenza A virus still represents a noticeable epidemic risk to international public health at present, despite the extensive use of vaccines and anti-viral drugs. In the fight against pathogens, the immune defence lines consisting of diverse lymphocytes are indispensable for humans. However, the role of virus infection of lymphocytes and subsequent abnormal immune cell death remains to be explored. Different T cell subpopulations have distinct characterizations and functions, and we reveal the high heterogeneity of susceptibility to viral infection and biological responses such as apoptosis in various CD4+ T and CD8+ T cell subsets through single-cell transcriptome analyses. Effector memory CD8+ T cells (CD8+ TEM) that mediate protective memory are identified as the most susceptible subset to pandemic influenza A virus infection among primary human T cells. Non-productive infection is established in CD8+ TEM and naïve CD8+ T cells, which indicate the mechanism of intracellular antiviral activities for inhibition of virus replication such as abnormal viral splicing efficiency, incomplete life cycles and up-regulation of interferon-stimulated genes in human T cells. These findings provide insights into understanding lymphopenia and the infectious mechanisms of pandemic influenza A virus and broad immune host-pathogen interactional atlas in primary human T cells.
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Affiliation(s)
- Jiapei Yu
- Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, People’s Republic of China
- Tsinghua University-Peking University Joint Centre for Life Sciences, Tsinghua University, Beijing, People’s Republic of China
| | - Hui Li
- Department of Pulmonary and Critical Care Medicine, Centre of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, People’s Republic of China
- Laboratory of Clinical Microbiology and Infectious Diseases, China-Japan Friendship Hospital, National Clinical Research Centre for Respiratory Medicine, Beijing, People’s Republic of China
- Institute of Respiratory Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
- Department of Pulmonary and Critical Care Medicine, Clinical Centre for Pulmonary Infections, Capital Medical University, Beijing, People’s Republic of China
| | - Ju Jia
- Department of Pulmonary and Critical Care Medicine, Centre of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, People’s Republic of China
- Institute of Respiratory Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Zhisheng Huang
- Department of Pulmonary and Critical Care Medicine, Centre of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, People’s Republic of China
- Institute of Respiratory Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Shuai Liu
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, People’s Republic of China
| | - Ying Zheng
- Department of Pulmonary and Critical Care Medicine, Centre of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, People’s Republic of China
- Department of Pulmonary and Critical Care Medicine, Clinical Centre for Pulmonary Infections, Capital Medical University, Beijing, People’s Republic of China
| | - Shengrui Mu
- Department of Pulmonary and Critical Care Medicine, Centre of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, People’s Republic of China
- Department of Pulmonary and Critical Care Medicine, Clinical Centre for Pulmonary Infections, Capital Medical University, Beijing, People’s Republic of China
| | - Xiaoyan Deng
- Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, People’s Republic of China
- Tsinghua University-Peking University Joint Centre for Life Sciences, Tsinghua University, Beijing, People’s Republic of China
| | - Xiaohui Zou
- Department of Pulmonary and Critical Care Medicine, Centre of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, People’s Republic of China
- Laboratory of Clinical Microbiology and Infectious Diseases, China-Japan Friendship Hospital, National Clinical Research Centre for Respiratory Medicine, Beijing, People’s Republic of China
| | - Yeming Wang
- Department of Pulmonary and Critical Care Medicine, Centre of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, People’s Republic of China
- Department of Pulmonary and Critical Care Medicine, Clinical Centre for Pulmonary Infections, Capital Medical University, Beijing, People’s Republic of China
| | - Xiao Shang
- Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, People’s Republic of China
- Tsinghua University-Peking University Joint Centre for Life Sciences, Tsinghua University, Beijing, People’s Republic of China
| | - Dan Cui
- Department of Pulmonary and Critical Care Medicine, Centre of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, People’s Republic of China
- Department of Respiratory Medicine, Harbin Medical University, Harbin, People’s Republic of China
| | - Lixue Huang
- Department of Pulmonary and Critical Care Medicine, Centre of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, People’s Republic of China
- Department of Pulmonary and Critical Care Medicine, Clinical Centre for Pulmonary Infections, Capital Medical University, Beijing, People’s Republic of China
| | - Xiaoxuan Feng
- Department of Respiratory Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
| | - William J. Liu
- NHC Key Laboratory of Biosafety, Chinese Centre for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, People’s Republic of China
| | - Bin Cao
- Tsinghua University-Peking University Joint Centre for Life Sciences, Tsinghua University, Beijing, People’s Republic of China
- Department of Pulmonary and Critical Care Medicine, Centre of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, People’s Republic of China
- Laboratory of Clinical Microbiology and Infectious Diseases, China-Japan Friendship Hospital, National Clinical Research Centre for Respiratory Medicine, Beijing, People’s Republic of China
- Institute of Respiratory Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
- Department of Pulmonary and Critical Care Medicine, Clinical Centre for Pulmonary Infections, Capital Medical University, Beijing, People’s Republic of China
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Yi X, Liu H, Zhu L, Wang D, Xie F, Shi L, Mei J, Jiang X, Zeng Q, Hu P, Li Y, Pang P, Liu J, Peng W, Bai HX, Liao W, Chen BT. Myosteatosis predicting risk of transition to severe COVID-19 infection. Clin Nutr 2022; 41:3007-3015. [PMID: 34147286 PMCID: PMC8180452 DOI: 10.1016/j.clnu.2021.05.031] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 05/23/2021] [Accepted: 05/28/2021] [Indexed: 01/27/2023]
Abstract
BACKGROUND About 10-20% of patients with Coronavirus disease 2019 (COVID-19) infection progressed to severe illness within a week or so after initially diagnosed as mild infection. Identification of this subgroup of patients was crucial for early aggressive intervention to improve survival. The purpose of this study was to evaluate whether computer tomography (CT) - derived measurements of body composition such as myosteatosis indicating fat deposition inside the muscles could be used to predict the risk of transition to severe illness in patients with initial diagnosis of mild COVID-19 infection. METHODS Patients with laboratory-confirmed COVID-19 infection presenting initially as having the mild common-subtype illness were retrospectively recruited between January 21, 2020 and February 19, 2020. CT-derived body composition measurements were obtained from the initial chest CT images at the level of the twelfth thoracic vertebra (T12) and were used to build models to predict the risk of transition. A myosteatosis nomogram was constructed using multivariate logistic regression incorporating both clinical variables and myosteatosis measurements. The performance of the prediction models was assessed by receiver operating characteristic (ROC) curve including the area under the curve (AUC). The performance of the nomogram was evaluated by discrimination, calibration curve, and decision curve. RESULTS A total of 234 patients were included in this study. Thirty-one of the enrolled patients transitioned to severe illness. Myosteatosis measurements including SM-RA (skeletal muscle radiation attenuation) and SMFI (skeletal muscle fat index) score fitted with SMFI, age and gender, were significantly associated with risk of transition for both the training and validation cohorts (P < 0.01). The nomogram combining the SM-RA, SMFI score and clinical model improved prediction for the transition risk with an AUC of 0.85 [95% CI, 0.75 to 0.95] for the training cohort and 0.84 [95% CI, 0.71 to 0.97] for the validation cohort, as compared to the nomogram of the clinical model with AUC of 0.75 and 0.74 for the training and validation cohorts respectively. Favorable clinical utility was observed using decision curve analysis. CONCLUSION We found CT-derived measurements of thoracic myosteatosis to be associated with higher risk of transition to severe illness in patients affected by COVID-19 who presented initially as having the mild common-subtype infection. Our study showed the relevance of skeletal muscle examination in the overall assessment of disease progression and prognosis of patients with COVID-19 infection.
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Affiliation(s)
- Xiaoping Yi
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, PR China
| | - Haipeng Liu
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, PR China
| | - Liping Zhu
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, PR China
| | - Dongcui Wang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, PR China
| | - Fangfang Xie
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, PR China
| | - Linbo Shi
- Department of Radiology, Yongzhou Central Hospital, Yongzhou, Hunan, 425006, PR China
| | - Ji Mei
- Department of Radiology, Changde Second People's Hospital, Changde, Hunan, 415001, PR China
| | - Xiaolong Jiang
- Department of Radiology, Affiliated Nan Hua Hospital, University of South China, Hengyang, Hunan, 421002, PR China
| | - Qiuhua Zeng
- Department of Radiology, Loudi Central Hospital, Loudi, Hunan, 417000, PR China
| | - Pingfeng Hu
- Department of Radiology, Chenzhou Second People's Hospital, Chenzhou, Hunan, 423000, PR China
| | - Yihui Li
- Department of Radiology, Zhuzhou Central Hospital, Zhuzhou, Hunan, 412002, PR China
| | | | - Jie Liu
- Department of Radiology, Affiliated Nan Hua Hospital, University of South China, Hengyang, Hunan, 421002, PR China
| | - Wanxiang Peng
- Department of Radiology, Zhuzhou Central Hospital, Zhuzhou, Hunan, 412002, PR China
| | - Harrison X. Bai
- Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI, 02903, USA
| | - Weihua Liao
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, PR China,Molecular Imaging Research Center of Central South University, Changsha, 410008, PR China,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, 410008, PR China,Corresponding author. Department of Radiology, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Changsha 410008, PR China. Fax: +011 86 731 84327438
| | - Bihong T. Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA, USA
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Liu KS, Mao XD, Ni W, Li TP. Laboratory detection of SARS-CoV-2: A review of the current literature and future perspectives. Heliyon 2022; 8:e10858. [PMID: 36212015 PMCID: PMC9527186 DOI: 10.1016/j.heliyon.2022.e10858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 05/16/2022] [Accepted: 09/26/2022] [Indexed: 11/06/2022] Open
Abstract
Nowadays, coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), whose infectivity is awfully strong, has been a major global threat to the public health. Since lung is the major target of SARS-CoV-2, the infection can lead to respiratory distress syndrome (RDS), multiple organ failure (MOF), and even death. The studies on viral structure and infection mechanism have found that angiotensin-converting enzyme 2 (ACE2), a pivotal enzyme affecting the organ-targeting in the RAS system, is the receptor of the SARS-CoV-2 virus. Currently, the detection of SARSCoV-2 is mainly achieved using open plate real-time reverse-transcription polymerase chain reaction (RT-PCR). While open plate method has some limitations, such as a high false-negative rate, cumbersome manual operation, aerosol pollution and leakage risks. Therefore, a convenient method to rapidly detect SARS-CoV-2 virus is urgently and extremely required for timely epidemic control with the limited resources. In this review, the current real-time methods and principles for novel coronavirus detection are summarized, with the aim to provide a reference for real-time screening of coronavirus in areas with insufficient detection capacity and inadequate medical resources. The development and establishment of a rapid, simple, sensitive and specific system to detect SARS-CoV-2 is of vital importance for distinct diagnosis and effective treatment of the virus, especially in the flu season.
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Affiliation(s)
- Kang-Sheng Liu
- Department of Clinical Laboratory, Women's Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing 210029, China
| | - Xiao-Dong Mao
- Department of Endocrinology, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210028, China,Key Laboratory of TCM Syndrome & Treatment of Yingbing of State Administration of Traditional Chinese Medicine, Jiangsu Province Academy of Traditional Chinese Medicine, Nanjing 210028, China
| | - Wenjing Ni
- Department of Endocrinology, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210028, China,Key Laboratory of TCM Syndrome & Treatment of Yingbing of State Administration of Traditional Chinese Medicine, Jiangsu Province Academy of Traditional Chinese Medicine, Nanjing 210028, China
| | - Tai-Ping Li
- Department of Neuro-Psychiatric Institute, The Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, China,Corresponding author.
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Innocenti F, De Paris A, Lagomarsini A, Pelagatti L, Casalini L, Gianno A, Montuori M, Bernardini P, Caldi F, Tassinari I, Pini R. Stratification of patients admitted for SARS-CoV2 infection: prognostic scores in the first and second wave of the pandemic. Intern Emerg Med 2022; 17:2093-2101. [PMID: 35733074 PMCID: PMC9216296 DOI: 10.1007/s11739-022-03016-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 05/23/2022] [Indexed: 01/08/2023]
Abstract
To test the prognostic performance of different scores, both specifically designed for patients with COVID-19 and generic, in predicting in-hospital mortality and the need for mechanical ventilation (MV). We retrospectively collected clinical data of patients admitted to the Emergency Department of the University Hospital AOU Careggi, Florence, Italy, between February 2020 and January 2021, with a confirmed infection by SARS-CoV2. We calculated the following scores: Sequential Organ Failure Assessment (SOFA) score, CALL score, 4C Mortality score, QUICK score, CURB-65 and MuLBSTA score. The end-points were in-hospital mortality and the need for MV. We included 1208 patients, mean age 60 ± 17 years, 57% male sex. Compared to survivors, non-survivors showed significantly higher values of all the prognostic scores (4C: 13 [10-15] vs 8 [4-10]; CALL: 11 [10-12] vs 9 [7-11]; QUICK: 4 [1-6] vs 0 [0-3]; SOFA: 5 [4-6] vs 4 [4-5]; CURB: 2 [1-3] vs 1 [0-1]; MuLBSTA: 11 [9-13] vs 9 [7-11], all p < 0.001). Discriminative ability evaluated by the Receiver Operating Curve analysis showed the following values of the Area under the Curve: 0.83 for 4C, 0.74 for CALL, 0.70 for QUICK, 0.68 for SOFA, 0.76 for CURB and 0.64 for MuLBSTA. The mortality rate significantly increased in increasing quartiles of 4C and CALL score (respectively, 2, 8, 24 and 54% for the 4C score and 1, 17, 33 and 68% for the CALL score, both p < 0.001). 4C and CALL score allowed an early and good prognostic stratification of patients admitted for pneumonia induced by SARS-CoV2.
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Affiliation(s)
- F Innocenti
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Firenze, Italy.
| | - A De Paris
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Firenze, Italy
| | - A Lagomarsini
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Firenze, Italy
| | - L Pelagatti
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Firenze, Italy
| | - L Casalini
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Firenze, Italy
| | - A Gianno
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Firenze, Italy
| | - M Montuori
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Firenze, Italy
| | - P Bernardini
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Firenze, Italy
| | - F Caldi
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Firenze, Italy
| | - I Tassinari
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Firenze, Italy
| | - R Pini
- High-Dependency Unit, Department of Clinical and Experimental Medicine, Careggi University Hospital, Lg. Brambilla 3, 50134, Florence, Firenze, Italy
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Albani V, Welsh CE, Brown H, Matthews FE, Bambra C. Explaining the deprivation gap in COVID-19 mortality rates: A decomposition analysis of geographical inequalities in England. Soc Sci Med 2022; 311:115319. [PMID: 36088725 PMCID: PMC9441468 DOI: 10.1016/j.socscimed.2022.115319] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 05/31/2022] [Accepted: 08/25/2022] [Indexed: 12/02/2022]
Abstract
One of the most consistent and worrying features of the COVID-19 pandemic globally has been the disproportionate burden of the epidemic in the most deprived areas. Most of the literature so far though has focused on estimating the extent of these inequalities. There has been much less attention paid to exploring the main pathways underpinning them. In this study, we employ the syndemic pandemic theoretical framework and apply novel decomposition methods to investigate the proportion of the COVID-19 mortality gap by area-level deprivation in England during the first wave of the pandemic (January to July 2020) was accounted for by pre-existing inequalities in the compositional and contextual characteristics of place. We use a decomposition approach to explicitly quantify the independent contribution of four inequalities pathways (vulnerability, susceptibility, exposure and transmission) in explaining the more severe COVID-19 outcomes in the most deprived local authorities compared to the rest. We find that inequalities in transmission (73%) and in vulnerability (49%) factors explained the highest proportion of mortality by deprivation. Our results suggest that public health agencies need to develop short- and long-term strategies to alleviate these underlying inequalities in order to alleviate the more severe impacts on the most vulnerable communities.
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Affiliation(s)
- Viviana Albani
- Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, UK
| | - Claire E Welsh
- Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, UK
| | - Heather Brown
- Department of Health Research, Faculty of Health and Medicine, Lancaster University, UK
| | - Fiona E Matthews
- Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, UK
| | - Clare Bambra
- Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, UK.
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Clinical features of 162 fatal cases of COVID-19: a multi-center retrospective study. EMERGENCY AND CRITICAL CARE MEDICINE 2022. [PMID: 37521814 PMCID: PMC9555552 DOI: 10.1097/ec9.0000000000000026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Background The coronavirus disease 2019 (COVID-19) has affected approximately 2 million individuals worldwide; however, data regarding fatal cases have been limited. Objective To report the clinical features of 162 fatal cases of COVID-19 from 5 hospitals in Wuhan between December 30, 2019 and March 12, 2020. Methods The demographic data, signs and symptoms, clinical course, comorbidities, laboratory findings, computed tomographic (CT) scans, treatments, and complications of the patients with fatal cases were retrieved from electronic medical records. Results The median patient age was 69.5 (interquartile range: 63.0–77.25) years, and 80% of the patients were over 61 years. A total of 112 (69.1%) patients were men. Hypertension (45.1%) was the most common comorbidity, while 59 (36.4%) patients had no comorbidity. At admission, 131 (81.9%) patients had severe or critical COVID-19, whereas 39 (18.1%) patients with hypertension or chronic lung disease had moderate COVID-19. In total, 126 (77.8%) patients received antiviral treatment, while 132(81.5%) patients received glucocorticoid treatment. A total of 116 (71.6%) patients were admitted to the intensive care unit (ICU), and 137 (85.1%) patients received mechanical ventilation. Most patients received mechanical ventilation before ICU admission. Approximately 93.2% of the patients developed respiratory failure or acute respiratory distress syndrome. There were no significant differences in the inhospital survival time among the hospitals (P=0.14). Conclusion Young patients with moderate COVID-19 without comorbidity at admission could also develop fatal outcomes. The in-hospital survival time of the fatal cases was similar among the hospitals of different levels in Wuhan.
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Evaluating the ability of the NLHA2 and artificial neural network models to predict COVID-19 severity, and comparing them with the four existing scoring systems. Microb Pathog 2022; 171:105735. [PMID: 36007846 PMCID: PMC9395227 DOI: 10.1016/j.micpath.2022.105735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 08/04/2022] [Accepted: 08/18/2022] [Indexed: 01/08/2023]
Abstract
To improve the identification and subsequent intervention of COVID-19 patients at risk for ICU admission, we constructed COVID-19 severity prediction models using logistic regression and artificial neural network (ANN) analysis and compared them with the four existing scoring systems (PSI, CURB-65, SMARTCOP, and MuLBSTA). In this prospective multi-center study, 296 patients with COVID-19 pneumonia were enrolled and split into the General-Ward-Care group (N = 238) and the ICU-Admission group (N = 58). The PSI model (AUC = 0.861) had the best results among the existing four scoring systems, followed by SMARTCOP (AUC = 0.770), motified-MuLBSTA (AUC = 0.761), and CURB-65 (AUC = 0.712). Data from 197 patients (training set) were analyzed for modeling. The beta coefficients from logistic regression were used to develop a severity prediction model and risk score calculator. The final model (NLHA2) included five covariates (consumes alcohol, neutrophil count, lymphocyte count, hemoglobin, and AKP). The NLHA2 model (training: AUC = 0.959; testing: AUC = 0.857) had similar results to the PSI model, but with fewer variable items. ANN analysis was used to build another complex model, which had higher accuracy (training: AUC = 1.000; testing: AUC = 0.907). Discrimination and calibration were further verified through bootstrapping (2000 replicates), Hosmer-Lemeshow goodness of fit testing, and Brier score calculation. In conclusion, the PSI model is the best existing system for predicting ICU admission among COVID-19 patients, while two newly-designed models (NLHA2 and ANN) performed better than PSI, and will provide a new approach for the development of prognostic evaluation system in a novel respiratory viral epidemic.
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MuLBSTA skorunun SARS-CoV-2 pnömonili hospitalize hastalarda kritik klinik sonuçları öngörmedeki prediktif değerinin incelenmesi. ANADOLU KLINIĞI TIP BILIMLERI DERGISI 2022. [DOI: 10.21673/anadoluklin.1132734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Giriş:MuLBSTA (Multilobar infiltrasyon, Lenfositopeni, Bakteriyel koenfeksiyon, Sigara öyküsü, hiperTansiyon ve Yaş> 65) skoru, viral pnömonisi olan hastaları beklenen mortaliteye göre sınıflandırmak için kullanılan bir klinik tahmin kuralıdır. Hastanede yatan Sars-Cov-2 hastalarında kötü klinik sonuçlar için MuLBSTA'nın prediktif performansını PSI, CURB-65 ve qSOFA ile karşılaştırdık.
Metot:Bu çalışma 11 Mart 2020 ile 31 Mayıs 2020 tarihleri arasında üçüncü basamak bir üniversite hastanesinde yatan Sars-Cov-2'li hastalar üzerinde geriye dönük yapıldı. SARS-Cov-2 testi pozitif çıkan 900 hastadan 271'i çalışmaya dahil edildi. Tüm hastalarda 30 günlük mortalite, YBÜ ihtiyacı, mekanik ventilasyon gereksinimi ve ARDS gelişimini değerlendirmek için MuLBSTA, PSI, CURB65 ve qSOFA skoru kullanıldı. 30 günlük mortalite için prognostik faktörler de analiz edildi.
Bulgular:Hastanede yatan 271 hastanın 150'si (%55.3) erkekti. Ortalama yaş 54.2 ± 15.4 yıldı. 30 günlük ölüm oranı %10,7 idi. Çalışmaya dahil edilen hastalardan; 39 hasta (%14,3) yoğun bakıma yatırıldı, 32 hasta (%11,8) mekanik ventilatör desteği aldı ve 23 hasta (%8,4) ARDS tanısı aldı. Mortaliteyi tahmin etmede MuLBSTA, PSI, CURB-65 ve qSOFA skorlarının alıcı işletim karakteristik eğrisi altında kalan alan(AUROC) değerleri sırasıyla 0.877 (%95 CI 0.832 0.914), 0.853 (%95 CI 0.806-0.893), 0.769 (95% CI 0,714-0,817) ve 0,769 (95% CI 0,715-0,818). MuLBSTA puanı, diğer tahmin puanlarına kıyasla daha yüksek bir AUROC değeri gösterdi. MuLBSTA ve PSI skorları, YBÜ ihtiyacı, mekanik ventilasyon gereksinimive ARDS gelişimi olan hastaları belirlemede CURB-65 ve qSOFA skorlarından daha iyi performans gösterdi.
Sonuç:MuLBSTA skoru, hastanede yatan Sars-Cov-2 hastalarında kötü klinik sonuçları tahmin etmek için etkili bir araçtır. Kullanımını doğrulamak için daha fazla çalışmaya ihtiyaç vardır.
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George R, Mehta AA, Paul T, Sathyapalan DT, Haridas N, Kunoor A, Ravindran GC. Validation of MuLBSTA score to derive modified MuLB score as mortality risk prediction in COVID-19 infection. PLOS GLOBAL PUBLIC HEALTH 2022; 2:e0000511. [PMID: 36962449 PMCID: PMC10021136 DOI: 10.1371/journal.pgph.0000511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 06/13/2022] [Indexed: 11/18/2022]
Abstract
COVID-19pandemic was started in December 2019. It has variable presentation from mild sore throat to severe respiratory distress. It is important to identify individuals who are likely to worsen. The Research question is how to identify patients with COVID-19 who are at high risk and to predict patient outcome based on a risk stratification model? We evaluated 251 patients with COVID-19 in this prospective inception study. We used a multi-variable Cox proportional hazards model to identify the independent prognostic risk factors and created a risk score model on the basis of available MuLBSTA score. The model was validated in an independent group of patients from October2020 to December 2021. We developed a combined risk score, the MuLBA score that included the following values and scores: Multi lobar infiltrates (negative0.254, 2), lymphopenia (lymphocytes of <0.8x109 /L, negative0.18,2), bacterial co- infection (negative, 0.306,3). In our MuLB scoring system, score of >8 was associated with high risk of mortality and <5 was at mild risk of mortality (P < 0.001). The interpretation was that The MuLB risk score model could help to predict survival in patients with severe COVID-19 infection and to guide further clinical research on risk-based treatment.
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Affiliation(s)
- Richie George
- Department of Respiratory Medicine, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India
| | - Asmita A. Mehta
- Department of Respiratory Medicine, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India
| | - Tisa Paul
- Department of Respiratory Medicine, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India
| | - Dipu T. Sathyapalan
- Division of infectious Diseases, Department of Internal Medicine, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India
| | - Nithya Haridas
- Department of Respiratory Medicine, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India
| | - Akhilesh Kunoor
- Department of Respiratory Medicine, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India
| | - Greeshma C. Ravindran
- Department of Biostatistics, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India
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Elshennawy NM, Ibrahim DM, Sarhan AM, Arafa M. Deep-Risk: Deep Learning-Based Mortality Risk Predictive Models for COVID-19. Diagnostics (Basel) 2022; 12:1847. [PMID: 36010198 PMCID: PMC9406405 DOI: 10.3390/diagnostics12081847] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 07/22/2022] [Accepted: 07/26/2022] [Indexed: 11/16/2022] Open
Abstract
The SARS-CoV-2 virus has proliferated around the world and caused panic to all people as it claimed many lives. Since COVID-19 is highly contagious and spreads quickly, an early diagnosis is essential. Identifying the COVID-19 patients' mortality risk factors is essential for reducing this risk among infected individuals. For the timely examination of large datasets, new computing approaches must be created. Many machine learning (ML) techniques have been developed to predict the mortality risk factors and severity for COVID-19 patients. Contrary to expectations, deep learning approaches as well as ML algorithms have not been widely applied in predicting the mortality and severity from COVID-19. Furthermore, the accuracy achieved by ML algorithms is less than the anticipated values. In this work, three supervised deep learning predictive models are utilized to predict the mortality risk and severity for COVID-19 patients. The first one, which we refer to as CV-CNN, is built using a convolutional neural network (CNN); it is trained using a clinical dataset of 12,020 patients and is based on the 10-fold cross-validation (CV) approach for training and validation. The second predictive model, which we refer to as CV-LSTM + CNN, is developed by combining the long short-term memory (LSTM) approach with a CNN model. It is also trained using the clinical dataset based on the 10-fold CV approach for training and validation. The first two predictive models use the clinical dataset in its original CSV form. The last one, which we refer to as IMG-CNN, is a CNN model and is trained alternatively using the converted images of the clinical dataset, where each image corresponds to a data row from the original clinical dataset. The experimental results revealed that the IMG-CNN predictive model outperforms the other two with an average accuracy of 94.14%, a precision of 100%, a recall of 91.0%, a specificity of 100%, an F1-score of 95.3%, an AUC of 93.6%, and a loss of 0.22.
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Affiliation(s)
- Nada M. Elshennawy
- Department of Computers and Control Engineering, Faculty of Engineering, Tanta University, Tanta 31733, Egypt; (D.M.I.); (A.M.S.); (M.A.)
| | - Dina M. Ibrahim
- Department of Computers and Control Engineering, Faculty of Engineering, Tanta University, Tanta 31733, Egypt; (D.M.I.); (A.M.S.); (M.A.)
- Department of Information Technology, College of Computer, Qassim University, Buraydah 51452, Saudi Arabia
| | - Amany M. Sarhan
- Department of Computers and Control Engineering, Faculty of Engineering, Tanta University, Tanta 31733, Egypt; (D.M.I.); (A.M.S.); (M.A.)
| | - Mohamed Arafa
- Department of Computers and Control Engineering, Faculty of Engineering, Tanta University, Tanta 31733, Egypt; (D.M.I.); (A.M.S.); (M.A.)
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Mortality Predictors in Severe SARS-CoV-2 Infection. Medicina (B Aires) 2022; 58:medicina58070945. [PMID: 35888664 PMCID: PMC9324408 DOI: 10.3390/medicina58070945] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/12/2022] [Accepted: 07/14/2022] [Indexed: 12/20/2022] Open
Abstract
Background and Objectives: The severe forms of SARS-CoV-2 pneumonia are associated with acute hypoxic respiratory failure and high mortality rates, raising significant challenges for the medical community. The objective of this paper is to present the importance of early quantitative evaluation of radiological changes in SARS-CoV-2 pneumonia, including an alternative way to evaluate lung involvement using normal density clusters. Based on these elements we have developed a more accurate new predictive score which includes quantitative radiological parameters. The current evolution models used in the evaluation of severe cases of COVID-19 only include qualitative or semi-quantitative evaluations of pulmonary lesions which lead to a less accurate prognosis and assessment of pulmonary involvement. Materials and Methods: We performed a retrospective observational cohort study that included 100 adult patients admitted with confirmed severe COVID-19. The patients were divided into two groups: group A (76 survivors) and group B (24 non-survivors). All patients were evaluated by CT scan upon admission in to the hospital. Results: We found a low percentage of normal lung densities, PaO2/FiO2 ratio, lymphocytes, platelets, hemoglobin and serum albumin associated with higher mortality; a high percentage of interstitial lesions, oxygen flow, FiO2, Neutrophils/lymphocytes ratio, lactate dehydrogenase, creatine kinase MB, myoglobin, and serum creatinine were also associated with higher mortality. The most accurate regression model included the predictors of age, lymphocytes, PaO2/FiO2 ratio, percent of lung involvement, lactate dehydrogenase, serum albumin, D-dimers, oxygen flow, and myoglobin. Based on these parameters we developed a new score (COV-Score). Conclusions: Quantitative assessment of lung lesions improves the prediction algorithms compared to the semi-quantitative parameters. The cluster evaluation algorithm increases the non-survivor and overall prediction accuracy.COV-Score represents a viable alternative to current prediction scores, demonstrating improved sensitivity and specificity in predicting mortality at the time of admission.
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Santos AP, Gonçalves LC, Oliveira ACC, Queiroz PHP, Ito CRM, Santos MO, Carneiro LC. Bacterial Co-Infection in Patients with COVID-19 Hospitalized (ICU and Not ICU): Review and Meta-Analysis. Antibiotics (Basel) 2022; 11:antibiotics11070894. [PMID: 35884147 PMCID: PMC9312179 DOI: 10.3390/antibiotics11070894] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 06/14/2022] [Accepted: 06/22/2022] [Indexed: 01/27/2023] Open
Abstract
The prevalence of patients hospitalized in ICUs with COVID-19 and co-infected by pathogenic bacteria is relevant in this study, considering the integrality of treatment. This systematic review assesses the prevalence of co-infection in patients admitted to ICUs with SARS-CoV-2 infection, using the PRISMA guidelines. We examined the results of the PubMed, Embase, and SciELO databases, searching for published English literature from December 2019 to December 2021. A total of 542 rec ords were identified, but only 38 were eligible and, and of these only 10 were included. The tabulated studies represented a sample group of 1394 co-infected patients. In total, 35%/138 of the patients were co-infected with Enterobacter spp., 27% (17/63) were co-infected with methicillin-sensitive Staphylococ cus aureus, 21% (84/404) were co-infected with Klebsiella spp., 16% (47/678) of patients were co-infected with coagulase-negative Staphylococcus, 13% (10/80) co-infected with Escherichia coli (ESBL), and 3% (30/1030) of patients were co-infected with Pseudomonas aeruginosa. The most common co-infections were related to blood flow; although in the urinary and respiratory tracts of patients Streptococcus pneumoniae was found in 57% (12/21) of patients, coagulase negative Staphylococcus in 44% (7/16) of patients, and Escherichia coli was found in 37% (11/29) of patients. The present research demonstrated that co-infections caused by bacteria in patients with COVID-19 are a concern.
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Affiliation(s)
- Adailton P. Santos
- Medicine College, Federal University of Goiás, 235 Street, Goiânia 74690-900, Brazil; (A.P.S.); (L.C.G.); (A.C.C.O.); (P.H.P.Q.); (M.O.S.)
| | - Lucas C. Gonçalves
- Medicine College, Federal University of Goiás, 235 Street, Goiânia 74690-900, Brazil; (A.P.S.); (L.C.G.); (A.C.C.O.); (P.H.P.Q.); (M.O.S.)
| | - Ana C. C. Oliveira
- Medicine College, Federal University of Goiás, 235 Street, Goiânia 74690-900, Brazil; (A.P.S.); (L.C.G.); (A.C.C.O.); (P.H.P.Q.); (M.O.S.)
| | - Pedro H. P. Queiroz
- Medicine College, Federal University of Goiás, 235 Street, Goiânia 74690-900, Brazil; (A.P.S.); (L.C.G.); (A.C.C.O.); (P.H.P.Q.); (M.O.S.)
| | - Célia R. M. Ito
- Institute of Tropical Pathology and Public Health, Federal University of Goiás, 235 Street, Goiânia 74605-050, Brazil;
| | - Mônica O. Santos
- Medicine College, Federal University of Goiás, 235 Street, Goiânia 74690-900, Brazil; (A.P.S.); (L.C.G.); (A.C.C.O.); (P.H.P.Q.); (M.O.S.)
| | - Lilian C. Carneiro
- Institute of Tropical Pathology and Public Health, Federal University of Goiás, 235 Street, Goiânia 74605-050, Brazil;
- Correspondence: ; Tel.: +55-(62)-32096528
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Álvarez‐Troncoso J, Ramos‐Ruperto L, Fernández‐Cidón P, Trigo‐Esteban E, Tung‐Chen Y, Busca‐Arenzana C, Quintana‐Díaz M, Buño‐Soto A, Arnalich‐Fernández F, Fernández‐Capitán C. Screening Protocol and Prevalence of Venous Thromboembolic Disease in Hospitalized Patients With COVID-19. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2022; 41:1689-1698. [PMID: 34694032 PMCID: PMC8661624 DOI: 10.1002/jum.15850] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 09/04/2021] [Accepted: 09/20/2021] [Indexed: 05/18/2023]
Abstract
BACKGROUND SARS-CoV-2 disease (COVID-19) induces endothelial damage and sustained hypoxia and facilitates immobilization as factors of hypercoagulability. OBJECTIVES The objective of our study was to assess the prevalence of venous thromboembolic disease (VTD) in COVID-19 patients and the usefulness of VTD screening based on age-adjusted D-dimer and point-of-care ultrasound (POCUS). PATIENTS/METHODS We conducted a single cohort, prospective observational study in 102 consecutive hospitalized patients. RESULTS A total of 102 POCUS and 39 pulmonary computed tomography angiography (PCTA) were performed diagnosing 27 VTD (26.5%): 17 deep vein thrombosis (DVT) (16.6% positive POCUS) and 18 pulmonary embolism (PE) (46.2% positive PCTA). COVID-19 patients with VTD were older (P < .030), had higher D-dimer (P < .001), higher International Society on Thrombosis and Hemostasis score (P < .001), and higher mortality (P = .025). However, there were no differences in inflammatory laboratory parameters neither in the cytokine storm syndrome (CSS) development. The ROC curve for D-dimer showed an AUC of 0.91. We have evidenced that patients with D-dimer between 2000 and 6000 ng/mL could benefit from a screening strategy with POCUS given the high sensitivity and specificity of the test. Furthermore, patients with D-dimer ≥6000 ng/mL should undergo POCUS and PCTA to rule out DVT and PE, respectively. CONCLUSIONS In our cohort, 26.5% of the patients presented VTD. Screening strategy based on age-adjusted D-dimer and POCUS proved high sensitivity and specificity. Future trials focused on screening strategies are necessary to early detect the presence of DVT and PE and determine thromboprophylaxis strategies in patients with COVID-19.
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Affiliation(s)
| | | | | | | | - Yale Tung‐Chen
- Department of Emergency MedicineHospital Universitario La PazMadridSpain
| | | | | | - Antonio Buño‐Soto
- Department of Clinical AnalysisHospital Universitario La PazMadridSpain
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Frutos MC, Origlia J, Gallo Vaulet ML, Venuta ME, García MG, Armitano R, Cipolla L, Madariaga MJ, Cuffini C, Cadario ME. SARS-CoV-2 and Chlamydia pneumoniae co-infection: A review of the literature. Rev Argent Microbiol 2022; 54:247-257. [PMID: 35931565 PMCID: PMC9189145 DOI: 10.1016/j.ram.2022.05.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 02/10/2022] [Accepted: 05/02/2022] [Indexed: 01/08/2023] Open
Abstract
Bacterial co-pathogens are commonly identified in viral respiratory infections and are important causes of morbid-mortality. The prevalence of Chlamydia (C.) pneumoniae infection in patients infected with SARS-CoV-2 has not been sufficiently studied. The objective of the present review was to describe the prevalence of C. pneumoniae in patients with coronavirus disease 2019 (COVID-19). A search in MEDLINE and Google Scholar databases for English language literature published between January 2020 and August 2021 was performed. Studies evaluating patients with confirmed COVID-19 and reporting the simultaneous detection of C. pneumoniae were included. Eleven articles were included in the systematic review (5 case cross-sectional studies and 6 retrospective studies). A total of 18 450 patients were included in the eleven studies. The detection of laboratory-confirmed C. pneumoniae infection varied between 1.78 and 71.4% of the total number of co-infections. The median age of patients ranged from 35 to 71 years old and 65% were male. Most of the studies reported one or more pre-existing comorbidities and the majority of the patients presented with fever, cough and dyspnea. Lymphopenia and eosinopenia were described in COVID-19 co-infected patients. The main chest CT scan showed a ground glass density shadow, consolidation and bilateral pneumonia. Most patients received empirical antibiotics. Bacterial co-infection was not associated with increased ICU admission and mortality. Despite frequent prescription of broad-spectrum empirical antimicrobials in patients with coronavirus 2-associated respiratory infections, there is a paucity of data to support the association with respiratory bacterial co-infection. Prospective evidence generation to support the development of an antimicrobial policy and appropriate stewardship interventions specific for the COVID-19 pandemic are urgently required.
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Affiliation(s)
- María Celia Frutos
- Instituto de Virología, Dr. J.M. Vanella, Facultad de Ciencias Médicas - Universidad Nacional de Córdoba, Córdoba, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina.
| | - Javier Origlia
- Cátedra de Patología de Aves y Pilíferos, Facultad de Ciencias Veterinarias, Universidad Nacional de La Plata, La Plata, Argentina
| | - María Lucia Gallo Vaulet
- Universidad de Buenos Aires, Facultad de Farmacia y Bioquímica, Departamento de Bioquímica Clínica, Cátedra de Microbiología Clínica, Inmunología y Virología Clínica, Argentina
| | - María Elena Venuta
- Servicio de Microbiología, Hospital de Pediatría Prof. Dr. Juan P. Garrahan, Buenos Aires, Argentina
| | - Miriam Gabriela García
- Laboratorio de Virología y Biología Molecular, Hospital Interzonal General Agudos Pedro Fiorito, Buenos Aires, Argentina
| | - Rita Armitano
- Departamento de Bacteriología, INEI-ANLIS Dr. Carlos G Malbrán, Ciudad Autónoma de Buenos Aires, Argentina
| | - Lucía Cipolla
- Departamento de Bacteriología, INEI-ANLIS Dr. Carlos G Malbrán, Ciudad Autónoma de Buenos Aires, Argentina
| | - María Julia Madariaga
- Sección Serología y Pruebas Biológicas, Instituto de Zoonosis Luis Pasteur, Ciudad Autónoma de Buenos Aires, Argentina
| | - Cecilia Cuffini
- Instituto de Virología, Dr. J.M. Vanella, Facultad de Ciencias Médicas - Universidad Nacional de Córdoba, Córdoba, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina
| | - María Estela Cadario
- Departamento de Bacteriología, INEI-ANLIS Dr. Carlos G Malbrán, Ciudad Autónoma de Buenos Aires, Argentina
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Novel Thiadiazole-Based Molecules as Promising Inhibitors of Black Fungi and Pathogenic Bacteria: In Vitro Antimicrobial Evaluation and Molecular Docking Studies. Molecules 2022; 27:molecules27113613. [PMID: 35684551 PMCID: PMC9182183 DOI: 10.3390/molecules27113613] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 05/29/2022] [Accepted: 06/02/2022] [Indexed: 02/01/2023] Open
Abstract
Novel 1,3,4-thiadiazole derivatives were synthesized through the reaction of methyl 2-(4-hydroxy-3-methoxybenzylidene) hydrazine-1-carbodithioate and the appropriate hydrazonoyl halides in the presence of a few drops of diisopropylethylamine. The chemical structure of the newly fabricated compounds was inferred from their microanalytical and spectral data. With the increase in microbial diseases, fungi remain a devastating threat to human health because of the resistance of microorganisms to antifungal drugs. COVID-19-associated pulmonary aspergillosis (CAPA) and COVID-19-associated mucormycosis (CAM) have higher mortality rates in many populations. The present study aimed to find new antifungal agents using the disc diffusion method, and minimal inhibitory concentration (MIC) values were estimated by the microdilution assay. An in vitro experiment of six synthesized chemical compounds exhibited antifungal activity against Rhizopus oryzae; compounds with an imidazole moiety, such as the compound 7, were documented to have energetic antibacterial, antifungal properties. As a result of these findings, this research suggests that the synthesized compounds could be an excellent choice for controlling black fungus diseases. Furthermore, a molecular docking study was achieved on the synthesized compounds, of which compounds 2, 6, and 7 showed the best interactions with the selected protein targets.
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Kashani NR, Azadbakht J, Ehteram H, Kashani HH, Rajabi-Moghadam H, Ahmad E, Nikzad H, Hosseini ES. Molecular and Clinical Investigation of COVID-19: From Pathogenesis and Immune Responses to Novel Diagnosis and Treatment. Front Mol Biosci 2022; 9:770775. [PMID: 35664675 PMCID: PMC9161360 DOI: 10.3389/fmolb.2022.770775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Accepted: 04/04/2022] [Indexed: 01/08/2023] Open
Abstract
The coronavirus-related severe acute respiratory syndrome (SARS-CoV) in 2002/2003, the Middle East respiratory syndrome (MERS-CoV) in 2012/2013, and especially the current 2019/2021 severe acute respiratory syndrome-2 (SARS-CoV-2) negatively affected the national health systems worldwide. Different SARS-CoV-2 variants, including Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and recently Omicron (B.1.1.529), have emerged resulting from the high rate of genetic recombination and S1-RBD/S2 mutation/deletion in the spike protein that has an impact on the virus activity. Furthermore, genetic variability in certain genes involved in the immune system might impact the level of SARS-CoV-2 recognition and immune response against the virus among different populations. Understanding the molecular mechanism and function of SARS-CoV-2 variants and their different epidemiological outcomes is a key step for effective COVID-19 treatment strategies, including antiviral drug development and vaccine designs, which can immunize people with genetic variabilities against various strains of SARS-CoV-2. In this review, we center our focus on the recent and up-to-date knowledge on SARS-CoV-2 (Alpha to Omicron) origin and evolution, structure, genetic diversity, route of transmission, pathogenesis, new diagnostic, and treatment strategies, as well as the psychological and economic impact of COVID-19 pandemic on individuals and their lives around the world.
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Affiliation(s)
- Narjes Riahi Kashani
- Anatomical Sciences Research Center, Institute for Basic Sciences, Kashan University of Medical Sciences, Kashan, Iran
- Gametogenesis Research Center, Kashan University of Medical Sciences, Kashan, Iran
| | - Javid Azadbakht
- Department of Radiology, Faculty of Medicine, Kashan University of Medical Sciences, Kashan, Iran
| | - Hassan Ehteram
- Department of Pathology, School of Medicine, Kashan University of Medical Sciences, Kashan, Iran
| | - Hamed Haddad Kashani
- Anatomical Sciences Research Center, Institute for Basic Sciences, Kashan University of Medical Sciences, Kashan, Iran
- Gametogenesis Research Center, Kashan University of Medical Sciences, Kashan, Iran
| | - Hassan Rajabi-Moghadam
- Department of Cardiovascular Medicine, Kashan University of Medical Sciences, Kashan, Iran
| | - Ejaz Ahmad
- Department of Pathology, Michigan Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Hossein Nikzad
- Anatomical Sciences Research Center, Institute for Basic Sciences, Kashan University of Medical Sciences, Kashan, Iran
- Gametogenesis Research Center, Kashan University of Medical Sciences, Kashan, Iran
| | - Elahe Seyed Hosseini
- Anatomical Sciences Research Center, Institute for Basic Sciences, Kashan University of Medical Sciences, Kashan, Iran
- Gametogenesis Research Center, Kashan University of Medical Sciences, Kashan, Iran
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Sutkowska E, Marciniak DM, Sutkowska K, Biernat K, Mazurek J, Kuciel N. The impact of lockdown caused by the COVID-19 pandemic on glycemic control in patients with diabetes. Endocrine 2022; 76:273-281. [PMID: 35072900 PMCID: PMC8784589 DOI: 10.1007/s12020-022-02985-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 01/12/2022] [Indexed: 12/20/2022]
Abstract
PURPOSE The aim the study was to assess the impact of the lockdown due to COVID-19 on diabetes control. METHODS The HbA1c value from a pre-lockdown visit (V1) from patients with diabetes was compared to the lockdown visit one (V2) after 3-5 months of its duration. Additional information on how the HbA1c changed and which variables can modify HbA1c during lockdown was also studied. RESULTS Records from 65 patients (type 2 diabetes -96,9%) were eligible and revealed that: HbA1c was at the target in 60% of the patients at V2 compared to 40% at V1; HbA1c decreased and normalized in 19, but worsened in 4 participants during the lockdown. No impact on HbA1c of: sex, age, diabetes duration, therapy type and modification before the pandemic, abandonment of the treatment, previous problems with glycemic control, or change in body weight and physical activity during the lockdown, was found. The previous macrovascular complications were the only variable that affected the increase in HbA1c (p = 0.0072), OR = 5.33. CONCLUSIONS The COVID-19 pandemic has not revealed worsened glycemic control in patients with type 2 diabetes, in general. The patients with macrovascular complications turned out to be at risk of the harmful impact of the restrictions on the HbA1c.
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Affiliation(s)
- Edyta Sutkowska
- Faculty of Medicine, Department and Division of Medical Rehabilitation, Wroclaw Medical University, Wroclaw, Poland.
| | - Dominik M Marciniak
- Department of Drugs Form Technology, Wroclaw Medical University, Wroclaw, Poland
| | | | - Karolina Biernat
- Faculty of Medicine, Department and Division of Medical Rehabilitation, Wroclaw Medical University, Wroclaw, Poland
| | - Justyna Mazurek
- Faculty of Medicine, Department and Division of Medical Rehabilitation, Wroclaw Medical University, Wroclaw, Poland
| | - Natalia Kuciel
- Faculty of Medicine, Department and Division of Medical Rehabilitation, Wroclaw Medical University, Wroclaw, Poland
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Esmailian M, Vakili Z, Nasr-Esfahani M, Heydari F, Masoumi B. D-dimer Levels in Predicting Severity of Infection and Outcome in Patients with COVID-19. TANAFFOS 2022; 21:419-433. [PMID: 37583776 PMCID: PMC10423863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 06/07/2022] [Indexed: 08/17/2023]
Abstract
COVID-19 disease began to spread all around the world in December 2019 until now; and in the early stage it may be related to high D-dimer level that indicates coagulation pathways and thrombosis activation that can be affected by some underlying diseases including diabetes, stroke, cancer, and pregnancy and it also can be associated with Chronic obstructive pulmonary disease (COPD). The aim of this article was to analyze D-dimer levels in COVID-19 patients, as D-dimer level is one of the measures to detect the severity and outcomes of COVID-19. According to the results of this study, there is a higher level of D-dimer as well as concentrations of fibrinogen in the disease onset and it seems that the poor prognosis is linked to a 3 to 4-fold increase in D-dimer levels. It is also shown that 76% of the patients with ≥1 D-dimer measurement, had elevated D-dimer and were more likely to have critical illness than those with normal D-dimer. There was an increase in the rates of adverse outcomes with higher D-dimer of more than 2000 ng/mL and it is associated with the highest risk of death at 47%, thrombotic event at 37.8%, and critical illness at 66%. It also found that diabetes and COPD had the strongest association with death in COVID-19. So, it is necessary to measure the D-dimer levels and parameters of coagulation from the beginning as well as pay attention to comorbidities that can help control and management of COVID-19 disease.
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Affiliation(s)
- Mehrdad Esmailian
- Department of Emergency Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Zohreh Vakili
- Department of Emergency Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | | | - Farhad Heydari
- Department of Emergency Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Babak Masoumi
- Department of Emergency Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
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Preti C, Biza R, Novelli L, Ghirardi A, Conti C, Galimberti C, Della Bella L, Memaj I, Di Marco F, Cosentini R. Usefulness of CURB-65, pneumonia severity index and MULBSTA in predicting COVID-19 mortality. Monaldi Arch Chest Dis 2022; 92. [DOI: 10.4081/monaldi.2022.2054] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 02/14/2022] [Indexed: 12/24/2022] Open
Abstract
The aim of our study is to evaluate the accuracy of CURB-65 and Pneumonia Severity Index (PSI), the most widely used scores for community acquired pneumonia, and MuLBSTA, a viral pneumonia score, in predicting 28-day mortality in Coronavirus Disease 2019 (COVID-19) pneumonia.We retrospectively collected clinical data of consecutive patients with laboratory-confirmed COVID-19 pneumonia admitted at Papa Giovanni XXIII Hospital from February 23rd to March 14th, 2020. We calculated at Emergency Department (ED) presentation CURB-65, PSI and MuLBSTA and we compared their performances in discriminating between survivors and non-survivors at 28 days. Among 431 hospitalized patients, the majority presented with hypoxic respiratory failure: median (interquartile range, IQR) PaO2/FiO2 ratio at admission was 228.6 (142.0-278.1). In the first 24 hours, 111 (27%) patients were administered low-flow oxygen cannula, 50 (12%) Venturi Mask, 95 (23%) non-rebreather mask, 106 (26%) non-invasive ventilation, 12 (3%) mechanical ventilation and 41 (9%) were not administered oxygen therapy. Mortality rate at 28-day was 35% (150/431). Between survivors and non-survivors, median (IQR) scores were, respectively, 1.0 (1.0-2.0) and 2.0 (2.0-3.0) for CURB-65 (p<0.001); 90.5 (76.0-105.5) and 115.0 (100.0-129.0) for PSI (p<0.001); 7.0 (5.0-10.0) and 11.0 (9.0-13.0) for MuLBSTA (p<0.001). Areas under the receiver operating characteristic curve (AUCs) for each score were, respectively, 0.725 (0.662-0.787), 0.776 (0.693-0.859) and 0.743 (0.680-0.806) (p>0,05). PSI and MuLBSTA did not show a better performance when compared to CURB-65. Although CURB-65, PSI and MuLBSTA scores are useful tools to discriminate between survivors and non-survivors in COVID-19 pneumonia, their diagnostic accuracy in discriminating 28-day mortality in COVID-19 pneumonia is moderate, as confirmed by AUCs <0.80, and there is a potential underestimation of disease severity in the low-risk classes. For this reason, they should not be recommended in ED to decide between inpatient and outpatient management in patients affected by COVID-19 pneumonia.
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Mao XD, Li T, Xu Z, Liu K. Pathogenesis of COVID-19 and the quality control of nucleic acid detection. Biochem Biophys Res Commun 2022; 591:137-142. [PMID: 33581843 PMCID: PMC7833324 DOI: 10.1016/j.bbrc.2020.12.094] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 12/28/2020] [Indexed: 01/08/2023]
Abstract
The new coronavirus pneumonia (COVID-19) epidemic spread rapidly throughout the world. Considering the strong infectivity and clustering of COVID-19, early detection of infectious cases is of great significance to control the epidemic. Nucleic acid testing (NAT) plays an important role in rapid laboratory diagnosis, treatment assessment, epidemic prevention and control of COVID-19. However, since COVID-19 is caused by a new emerging virus and NAT for COVID-19 has not been clinically applied before, false negative results inconsistent with clinical diagnosis have appeared in clinical practice. Therefore, it is urgent to improve the sensitivity of NAT for COVID-19. This study aimed to summarize the current situation and prospect of NAT based on the latest findings on COVID-19 infection. Also, the quality control of sample collection was discussed. Hopefully, this study could help to improve the effectiveness of NAT for COVID-19.
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Affiliation(s)
- Xiao-Dong Mao
- Department of Endocrinology, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210028, China
| | - Taiping Li
- Department of Neuro-Psychiatric Institute, Nanjing Medical University Affiliated Brain Hospital, Nanjing, Jiangsu, 210029, China
| | - Zhirong Xu
- Department of Clinical Laboratory, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, China
| | - Kangsheng Liu
- Department of Clinical Laboratory, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, Jiangsu, 210029, China,Corresponding author
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Mohamed RAE, Abdelsalam EM, Maghraby HM, Al Jedaani HS, Rakha EB, Hussain K, Sultan I. Performance features and mortality prediction of the 4C Score early in COVID-19 infection: a retrospective study in Saudi Arabia. J Investig Med 2022; 70:421-427. [PMID: 34836890 PMCID: PMC8635889 DOI: 10.1136/jim-2021-001940] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/18/2021] [Indexed: 01/28/2023]
Abstract
The ISARIC4C consortium developed and internally validated the 4C Score for prediction of mortality only in hospitalized patients. We aimed to assess the validity of the 4C Score in mortality prediction of patients with COVID-19 who had been home isolated or hospitalized.This retrospective cross-sectional study was performed after the first wave of COVID-19. Data of all PCR-positive COVID-19 patients who had been discharged, hospitalized, or died were retrospectively analyzed. Patients were classified into four risk groups according to the 4C Mortality Score. A total of (506) patients were classified as follows: low (57.1%), intermediate (27.9%), high (13%), and very high (2%) risk groups. Clinical, radiological, and laboratory data were significantly more severe in the high and very high-risk groups compared with other groups (p<0.001 for all). Mortality rate was correctly estimated by the model with 71% sensitivity, 88.6% specificity, and area under the curve of 0.9. The mortality rate was underestimated among the very high-risk group (66.2% vs 90%). The odds of mortality were significantly greater in the presence of hypoxia (OR 2.6, 95% CI 1.5 to 4.6, p<0.001) and high respiratory rate (OR 5.3, 95% CI 1.6 to 17.9, p<0.007), C reactive protein (CRP) (OR 3.5, 95% CI 1.8 to 6.8, p<0.001), and blood urea nitrogen (BUN) (OR 1.9, 95% CI 1.3 to 3.1, p<0.002). Other components of the model had non-significant predictions. In conclusion, the 4C Mortality Score has good sensitivity and specificity in early risk stratification and mortality prediction of patient with COVID-19. Within the model, only hypoxia, tachypnea, high BUN, and CRP were the independent mortality predictors with the possibility of overlooking other important predictors.
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Affiliation(s)
- Rehab Abd Elfattah Mohamed
- Internal Medicine Department, Faculty of Medicine for Girls, Al-Azhar University, Cairo, Egypt
- Internal Medicine Department, Ibn Sina National College for Medical Studies, Jeddah, Saudi Arabia
| | - Eman Mahmoud Abdelsalam
- Internal Medicine Department, Faculty of Medicine for Girls, Al-Azhar University, Cairo, Egypt
| | - Hend Maghraby Maghraby
- Internal Medicine Department, Faculty of Medicine for Girls, Al-Azhar University, Cairo, Egypt
| | - Huda Shali Al Jedaani
- Obs/Gyn Department, Ibn Sina National College for Medical Studies, Jeddah, Saudi Arabia
| | - Ehab Badran Rakha
- Clinical Pathology Department, Mansoura University, Faculty of Medicine, Mansoura, Egypt
| | - Khamrunissa Hussain
- Quality Department, Ibn Sina National College for Medical Studies, Jeddah, Saudi Arabia
| | - Intessar Sultan
- Internal Medicine Department, Ibn Sina National College for Medical Studies, Jeddah, Saudi Arabia
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Thakur CK, Batra P, Vinayaraj EV, Sreenath K, Rathor N, Singh UB, Bhatia R, Aravindan A, Wig N, Guleria R, Chaudhry R. Scrub typhus in two COVID-19 patients: a diagnostic dilemma. Future Microbiol 2022; 17:161-167. [PMID: 35044234 PMCID: PMC8787614 DOI: 10.2217/fmb-2021-0163] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
The authors describe a case series of co-infection with COVID-19 and scrub typhus in two Indian patients. Clinical features like fever, cough, dyspnea and altered sensorium were common in both patients. Case 1 had lymphopenia, elevated IL-6 and history of hypertension, while case 2 had leukocytosis and an increased liver enzymes. Both patients had hypoalbuminemia and required admission to the intensive care unit; one of them succumbed to acute respiratory distress syndrome further complicated by multiple organ dysfunction syndrome. Seasonal tropical infections in COVID-19 patients in endemic settings may lead to significant morbidity and mortality. Therefore, high clinical suspicion and an early diagnosis for co-infections among COVID-19 patients are essential for better patient management.
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Affiliation(s)
- Chandan Kumar Thakur
- Department of Microbiology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
| | - Priyam Batra
- Department of Microbiology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
| | - EV Vinayaraj
- Department of Microbiology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
| | - K Sreenath
- Department of Microbiology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
| | - Nisha Rathor
- Department of Microbiology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
| | - Urvashi B Singh
- Department of Microbiology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
| | - Ridhima Bhatia
- Department of Anesthesiology, Pain Medicine & Critical Care, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
| | - Ajisha Aravindan
- Department of Anesthesiology, Pain Medicine & Critical Care, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
| | - Naveet Wig
- Department of Medicine, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
| | - Randeep Guleria
- Department of Pulmonary, Critical Care & Sleep Medicine, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
| | - Rama Chaudhry
- Department of Microbiology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
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