The Spanish Society of Pulmonology and Thoracic Surgery created a registry for hospitalised patients with COVID-19 and the different types of respiratory support used (RECOVID). Objectives. To describe the profile of hospitalised patients with COVID-19, comorbidities, respiratory support treatments and setting. In addition, we aimed to identify varying profiles of patients according to outcomes and the complexity of respiratory support needed.

Multicentre, observational study in 49 Spanish hospitals. A protocol collected demographic data, comorbidities, respiratory support, treatment setting and 1-year follow-up. Patients were described using either frequency and percentages or median and interquartile range, as appropriate. A cluster analysis made it possible to identify different types of profile among the patients.

In total, 2148 of 2454 hospitalised patients (87.5%) received care in the conventional ward, whilst 126 in IRCU and 180 in ICU. In IRCU, 30% required high-flow nasal oxygen whilst 25%, non-invasive mechanical ventilation and 17%, mechanical ventilation. Four clusters of patients were identified. Two clusters were more likely to require IRCU/ICU admission, although primarily Cluster 2: Cluster (C) 1 consisted of patients without comorbidities and C2, those with comorbidities. Both presented higher inflammatory levels and lower lymphocyte count and SpO2/FiO2; however, C2 showed worse values. Two different clusters identified patients requiring less complex respiratory support. C3 presented higher comorbidities and elevated lymphocyte count, SpO2/FiO2 and low C-reactive protein (CRP). C4 included those without comorbidities except for arterial hypertension, lymphopenia and an intermediate CRP. In-hospital mortality and subsequent 1-year mortality were greater for C2 (28.6% and 7.1%) and C1 (11.1%, 8.3%) than for C4 (3.3%, 1.8%) and C3 (0%, 0%).

The cluster analysis identified four clinical phenotypes requiring distinct types of respiratory support, with great differences present per characteristics and outcomes.

NETosis, the process through which neutrophils release neutrophil extracellular traps (NETs), has emerged as a crucial mechanism in host defense and the pathogenesis of autoimmune responses. During the SARS-CoV-2 pandemic, this process received significant attention due to the central role of neutrophil recruitment and activation in infection control. However, elevated neutrophil levels and dysregulated NET formation have been linked to coagulopathy and endothelial damage, correlating with disease severity and poor prognosis in COVID-19. Moreover, it is known that SARS-CoV-2 can induce persistent low-grade systemic inflammation, known as long COVID, although the underlying causes remain unclear. It has been increasingly acknowledged that excessive NETosis and NET generation contribute to further pathophysiological abnormalities following SARS-CoV-2 infection. This review provides an updated overview of the role of NETosis in autoimmune diseases, but also the relationship between COVID-19 and long COVID with autoimmunity (e.g., latent and overt autoimmunity, molecular mimicry, epitope spreading) and NETosis (e.g., immune responses, NET markers). Finally, we discuss potential therapeutic strategies targeting dysregulated NETosis to mitigate the severe complications of COVID-19 and long COVID.

Anticoagulants have an important role in the prevention of cardiovascular disorders. Costus speciosus (Costaceae) is a medicinal herb used to treat COVID-19-induced thrombosis. The purpose of this study was to assess the anticoagulant activity of various C. speciosus aqueous (CSAE), ethanol (SCEE), and methanol (CSME) extracts in vivo and in vitro utilizing thrombin time (TT), activated partial thromboplastin time (aPTT), and prothrombin time (PT). Different concentrations of the three extracts were used to evaluate the anticoagulation effects in vitro. In the in vivo assay, male Sprague Dawley rats were used to test the CSME as in vivo anticoagulants. Three groups of rats included the control group and the groups that received CSME daily at a low (200 mg/kg) or high dose (400 mg/kg b.w) for 2 weeks. The molecular docking of the major bioactive constituents of the methanolic extract against the binding site of the thrombin inhibitor complex was evaluated. The HPLC detected 13, 10 and 11 polyphenols in the methanolic, ethanolic and aqueous extracts, respectively. The in vitro results showed that all the studied extracts had anticoagulant activity and increased aPTT, TT, and PT time. The in vivo experiment supported the in vitro results and demonstrated that CSME greatly prolonged the anticoagulant characteristics when compared to the negative control. Both findings suggested that these extracts have significant anticoagulant activity, with CSME being more effective and potentially useful in pharmaceutical applications as a natural anticoagulant medication.

This study aimed to implement a multi-state risk prediction model to predict the progression of COVID-19 cases among hospitalized patients in Kurdistan province by analyzing hospital care data.

This retrospective analysis consisted of data from 17,286 patients admitted to hospitals with COVID-19 from March 23, 2019, to December 19, 2021, in various areas in the Kurdistan province. A multi-state prediction model was used to show that each transition is predicted by a different set of variables. These variables include underlying diseases (like diabetes, hypertension, etc.) and sociodemographic information (like sex and age). Model aims to predict the likelihood of recovery, the need for critical care intervention (e.g., transfer to isolation units or the ICU), or exits from the hospitalization course. We performed the statistical analysis using R software and the mstate package.

Of the hospitalized patients studied, 5.6% died of the disease, 6.6% were admitted to ICUs, and 38.72% were treated in isolation units. Mortality rates in general wards, isolation units, and the ICU were 3.48%, 4.56%, and 26.6%, respectively. Significant predictors for ICU admission include age over 60 years (HR: 1.46, 95% CI 1.37-1.55), kidney-related conditions (HR: 2.19, 95% CI 1.65-2.91), cardiovascular diseases (HR: 1.68, 95% CI 1.46-1.94), lung disease (HR: 1.89,‏95% CI 1.43-2.05), and cancer (HR: 2.46,‏95% CI 1.77-3.41). The likelihood of in-hospital death is significantly increased by age over 60 years (HR: 2.40, 95% CI 2.09-2.76), diabetes (HR: 1.97, 95% CI 1.45-2.68), high blood pressure (HR: 2.30, 95% CI 1.78-2.97), and history of heart disease (HR: 3.01, 95% CI 2.29-3.95).

The model helps the provider and policymakers to make an informed decision depending on patient management and resource allocation within the health care systems.

Traditional Chinese medicine has been recognized for its significant role in treating acute lung injury (ALI) due to its distinct therapeutic advantages. Liang-Ge-San (LGS), a formulation from the ancient "Taiping Huimin Hejiju Fang", is believed to possess beneficial effects for treating ALI. However, LGS's precise mechanisms and efficacy in addressing viral ALI remain inadequately explored.

To evaluate LGS's therapeutic effects and underlying mechanisms in treating viral-induced ALI.

The protective effects of LGS were examined in a Polyinosinic-polycytidylic acid [Poly(I:C)]-induced ALI model using real-time quantitative PCR, enzyme-linked immunosorbent assay, and histopathological analysis. A bioinformatics approach combined with network pharmacology was utilized to ascertain the key targets of LGS in viral pneumonia. The pharmacodynamic mechanisms of LGS in viral ALI were further validated through immunofluorescence, overexpression, short hairpin RNA, chromatin immunoprecipitation, and target agonist assays.

LGS administration resulted in a reduction of IL-1β, IL-6, and TNF-α levels, along with a decrease in macrophage infiltration, pulmonary damage, and pneumonedema following the Poly(I:C) challenge. Bioinformatics and network pharmacology analyses suggested that Farnesyl X receptor (FXR) and angiotensin converting enzyme 2 (ACE2) are potential therapeutic targets for LGS in viral pneumonia. Further experiments revealed that LGS suppressed the expression of FXR, ACE2, and NF-κB-p65 in Poly(I:C)-infected cells. Notably, overexpression of FXR counteracted the repressive effects of LGS, while ACE2 expression remained unchanged in FXR-knockdown RAW264.7 cells upon treatment with Poly(I:C) or LGS. Additionally, LGS inhibited the interaction between FXR and ACE2 transcriptional promoters. In vivo, LGS attenuated the Poly(I:C)-induced upregulation of FXR, ACE2, IL-1β, IL-6, and TNF-α in ALI zebrafish and mice models, effects that could be reversed by chenodeoxycholic acid (CDCA), an FXR agonist. Moreover, LGS markedly alleviated weight loss, improved survival rates, reduced lung index, diminished viral load, and inhibited lung pathological changes in H1N1-PR8-induced ALI mice. IL-1β, IL-6, TNF-α, INF-γ, FXR, ACE2, small heterodimer partner, and NF-κB-p65 levels were markedly reduced by LGS, with these effects being reversed by CDCA.

This investigation provides the first evidence that FXR/ACE2 signaling is pivotal in acute respiratory viral infections, while LGS demonstrates antiviral activity against viral-induced ALI. LGS inhibits ACE2 expression induced by viral infection via FXR inhibition and modulates the cytokine storm, thus alleviating viral ALI. These findings suggest that LGS may be a promising treatment strategy for treating viral ALI.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to a significant burden on global healthcare systems. COVID-19-induced acute kidney injury (AKI) is among one of the complications, that has emerged as a critical and frequent condition in COVID-19 patients. This AKI among COVID-19 patients is associated with poor outcomes, and high mortality rates, especially in those with severe AKI or requiring renal replacement therapy. COVID-19-induced AKI represents a significant complication with complex pathophysiology and multifactorial risk factors. Indeed, several pathophysiological mechanisms, including direct viral invasion of renal cells, systemic inflammation, endothelial and thrombotic abnormalities as well as nephrotoxic drugs and rhabdomyolysis are believed to underlie this condition. Moreover, histopathological and immunohistopathological findings commonly observed in postmortem studies include acute tubular necrosis, glomerular injury, and the presence of viral particles within renal tissue and urine. Identified risk factors for developing AKI vary among studies, depending on regions, underlying conditions, and the severity of the disease. Moreover, histopathological and immunohistopathological findings commonly observed in postmortem studies include show acute tubular necrosis, glomerular injury, and viral particles within renal tissue and urine. While, identified risk factors for developing AKI vary among studies, according to regions, underlying conditions, and the gravity of the disease. This narrative review aims to synthesize current knowledge on the incidence, pathophysiology, risk factors, histopathology, and outcomes of AKI induced by COVID-19.

The goal of this scoping review was to review some of the challenges hospitals faced in dealing with the shortage of ventilators during the COVID-19 pandemic and the solutions they were able to implement or suggested. By highlighting these problems and solutions, we hope this review can catalyze further discussions about how to better prepare for future pandemics and medical supply shortages.

A comprehensive search strategy using identifying key words was applied to several different databases to procure relevant literature.

Four thousand two hundred fifty-nine studies were found in the initial search. Inclusion and exclusion criteria were created and applied to screen studies. Included studies focused on the supply and distribution of ventilators during the COVID-19 pandemic. In the case where reviewers disagreed about whether a study should be included, a third reviewer acted as a tie-breaker.

Thirty-three studies were included for final data extraction. Two independent reviewers collected various data points from these studies, including the main challenges discussed by the authors, the level of ventilator shortage being addressed, whether ventilator sharing was discussed, and the limitations of the study.

A third reviewer compared the collected data and decided on the results.

Some of the common solutions for the ventilator shortage discussed included augmenting overall ventilator supply through increased production, transporting ventilators between hospitals, ventilator sharing, designing new ventilators, and repurposing other resources to help address shortages of supplies.

It has been suggested that the use of statin pills beforehand could potentially influence the outcomes when individuals are hospitalized with COVID-19. In this study, we investigated how the prior use of statin medication could influence the COVID-19 severity parameters. In this retrospective cohort study, we categorized COVID-19 patients into 2 groups: statin users and non-users. Then, various data including age, gender, the patient's need for ventilation support, the lowest oxygen blood saturation level, the length of hospitalization, receiving remdesivir treatment, and their COVID-19 vaccination status were collected. Out of 168 patients, 62 had taken statin medication before being admitted. Using statins decreased the patient's need for ventilation support, length of hospitalization, ventilation duration, and oxygen saturation level (P < .001). Interaction effect analysis showed that receiving remdesivir statically affected the length of hospitalization, ventilation duration, and oxygen saturation level but did not significantly affect the association between statins and needing to ventilator. The use of statin pills before COVID-19 admission reduced the requirement for ventilator support.

While SARS-CoV-2 vaccines have shown strong efficacy, the continued emergence of new viral variants raises concerns about the ongoing and future public health impact of COVID-19, especially in locations with suboptimal vaccination uptake. We investigated viral and host factors, including vaccination status, that were associated with SARS-CoV-2 disease severity in a setting with low vaccination rates. We analyzed clinical and demographic data from 1,957 individuals in the state of Georgia, USA, coupled with viral genome sequencing from 1,185 samples. We found no specific mutations associated with disease severity. Compared to those who were unvaccinated, vaccinated individuals experienced less severe SARS-CoV-2 disease, and the effect was similar for both variants. Vaccination within the prior 3-9 months was associated with decreased odds of moderate disease, severe disease, and death. Older age and underlying health conditions, especially immunosuppression and renal disease, were associated with increased disease severity. Overall, this study provides insights into the impact of vaccination status, variants/mutations, and clinical factors on disease severity in SARS-CoV-2 infection when vaccination rates are low. Understanding these associations will help refine and reinforce messaging around the crucial importance of vaccination in mitigating the severity of SARS-CoV-2 disease.

The study looks into the condition of elderly Covid-19 patients regarding the kind of attention they received during the pandemic given the scarcity of medical resouces in the countries mentioned in this investigation. In this case, we apply the bioethical principle of justice on the age-based criteria in determining which patient must receive treatment The argument is that the same is a form of discimination against the elderly.

The purpose of this study is to emphasize that the age-based criteria in deciding whether to treat elderly Covid-19 patients or not is violative of the bioethical principle of justice since it discriminates against them.

This study uses the interpretive method. The authors analyzed the literature and the arguments pertaining to the issue of ageism at the height of the Covid-19 Pandemic. We mentioned the countries where the issue of prioritization was a big concern. The qualitative analysis in this paper is meant to respond to such medical dilemma.

In our analysis, we determined that when age is used as a criterion, it violates the bioethical principle of justice. The principle is meant to ensure that physicians are fair in dealing with patients. Using age in deciding whether a life is worth saving or not is a prejudice against old people who require care and attention.

Medical doctors must treat patients equally and without bias. The challenge, however, is that due to the unprecedented nature of the pandemic, a triage is put in place to be able to manage the overwhelming influx of Covid-19 patients. Some age-based medical treatment criteria that recommend age-based cutoffs for specific treatments are morally untenable. This is because the same is bereft of any acceptable justification that warrants the judgment that the elderly must have less priority when medical resources are scarce.

In conclusion, doctors must not discriminate patients on the basis of age. All lives are equal in moral worth. We argue that governments must promulgate non-discriminatory policies when it comes to medical treatment during a global public health emergency.

The outbreak of COVID-19 pandemic has caused substantial health loss worldwide, and the long-term sequelae of COVID, resulting from repeated coronavirus infection, have emerged as a new public health concern. We report the widespread presence of abnormal metallomic profiles in the sera of patients who have recovered from SARS-CoV-2 coronavirus infection, even after 6 months post-discharge from hospital. We measured the concentrations of Fe, Cu, Zn, Se, Cr, Mn, Ba, Ni, Pb, Ag, As, Cd, Co, and V in the sera of 25 recovered participants and 38 healthy controls in the cross-sectional study. Higher concentrations of Cu, Ag, As, Ba, Cd, Ni, Pb, Cr and V were observed in the recovered participants, whereas lower concentrations of Fe and Se were obtained in these participants. Except for Zn, Mn, and Co, all other elements showed significant differences (p < 0.05) between the two groups, with variations dependent on age and gender. Further correlation analysis between metallome and metabolome indicated that SARS-CoV-2 infection continues to disrupt metallic homeostasis and affect metabolic processes, such as lipid metabolism and cell respiration, as well as the functions of certain organs (e.g., liver, kidney, and heart), even after 6 months recovery. Our findings provide novel insights into the potential long-term effect of COVID-19 on the human body from a new perspective of metallomics.

This study was conducted to assess the effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on dental healthcare workers (DHCWs) during the pandemic. Due to frequent exposure to aerosol-generating procedures, DHCWs are at an increased risk of a SARS-CoV-2 infection, increasing their mortality risk. Therefore, this retrospective study aimed to ascertain the mortality of DHCWs attributable to SARS-CoV-2 infection from databases in the public domain during the pandemic.

The data were obtained from three public-domain online databases: Medscape, FNOMCeO, and X. All collected data from March 2020 to May 2024 were merged into a tabulated format. An analysis was conducted on the data collectively and through a subgroup analysis based on the country, detailed profession, age, gender, and date of death.

During the SARS-CoV-2 pandemic, 100 DHCWs were deceased. The DHCWs in the study were employed in 14 countries, with the United States (40%) and Italy (34%) listing the highest percentages of deaths of these workers. Dentists constituted 79% of the total DHCWs. The gender distribution among the deceased was 85 (85%) men and 15 (15%) women. The age of 57 deceased DHCWs was known, resulting in a mean age of 58 years (ranging from 28 to 88). The DHCWs at ages 60 to 70 years (49%) exhibited the highest mortality rate from SARS-CoV-2. The date of death was known for 73 DHCWs, who were deceased between March 2020 and February 2023.

During the global pandemic, DHCWs worked in the context of general practice. The DHCWs adhered to infection prevention protocols according to standard guidelines and incorporated new adjunctive measures, especially for the pandemic, including adopting coronavirus disease 2019 guidelines for oral healthcare. These measures provided satisfactory protection, with less than 0.006% mortality of the estimated DHCWs worldwide.

To evaluate previous diabetes and hyperglycemia in post-COVID-19 mortality.

We evaluated patients with diabetes (previous diabetes and use of medication and random glucose ≥ 200 mg/dl and HbA1C ≥ 6.5 % or 48 mmol/mol) and patients without diabetes with hyperglycemia 1 year before COVID-19. Hazard ratios (HR) and 95 % confidence intervals, 95 %CI were calculated for all-cause mortality (1-week to 1-year) among those with diabetes (only), diabetes with comorbidities (hypertension, chronic kidney disease-CKD), and patients without diabetes but with hyperglycemia (≥ 100 ≥ 110 and ≥ 126 mg/dl).

Of 455 patients, 30.1 % had diabetes. Diabetes only had a high mortality risk in 7 days (HR: 6.24; 95 %CI: 1.03-37.77). Diabetes with hypertension and CKD were associated with increased mortality risks from 1-week (HR: 7.98; 95 %CI, 1.03-61.70) to 1-year (HR: 2.27; 95 %CI: 1.03-4.99) after COVID-19. Among those without diabetes, FBG ≥ 110 and ≥ 126 mg/dl were associated with more than double the risk of dying in 1-year after COVID-19 infection [1-year HR: 2.80 (95 %CI: 1.10 - 7.22) and 1-year HR: 2.54 (95 %CI:1.10-5.88), respectively].

Diabetes associated with other comorbidities had the highest risks of all-cause mortality in the short and long-term, hyperglycemia was a long-term marker of poor prognostic after COVID-19 infection.

While the association between COVID-19 and acute kidney injury (AKI) is well documented, the impact of COVID-19 on the development of advanced chronic kidney disease (CKD) remains unclear, particularly in patients without initial AKI. Using the TriNetX healthcare database, we conducted a matched cohort study comparing 141,587 COVID-19 and 141,587 influenza patients. We excluded patients with AKI within one month of infection and matched groups on demographics, comorbidities, and baseline laboratory values. The primary outcome was the incidence of advanced CKD (stages 3-5) at the 12-month follow-up. COVID-19 patients showed higher 12-month risks of advanced CKD (hazard ratio [HR]:2.02, 95% confidence interval [CI]:1.69-2.42, p < 0.0001), AKI (HR 3.04, 95%CI:2.61-3.55, p < 0.0001), and estimated glomerular filtration rate < 60 mL/min/1.73 m2 (HR:3.01, 95%CI:2.74-3.30, p < 0.0001) compared to influenza patients. Subgroup analyses showed consistently elevated risks across sexes and in patients over 45 years, while younger patients did not demonstrate an increased risk of advanced CKD at the 12-month follow-up. Diabetes mellitus and hypertension have emerged as the strongest predictors of advanced CKD development. In conclusion, COVID-19 is associated with an increased risk of long-term renal dysfunction compared with influenza, suggesting the need for extended monitoring of kidney function in high-risk populations.

In kidney transplant recipients (KTRs), immune monitoring of peripheral lymphocyte subsets (PLS) reflects the real immune status and aids in the diagnosis of the occurrence and development of infectious diseases, including COVID-19. Exploring the PLS of COVID-19 pneumonia in KTRs is important.

In this study, a total of 103 KTRs were divided into mild pneumonia (MP) and severe pneumonia (SP) groups, as well as a stable group. The clinical information and PLS data were assessed via t or Mann-Whitney test and receiver operating curve analysis. Logistic regression was employed to identify the risk factors, and Spearman's correlation analysis was used to identify correlations.

Lymphopenia is a common manifestation of COVID-19 in KTRs, and it is positively related to the severity of COVID-19 pneumonia. The CD3 + T-cell count had the highest AUC between the MP and the SP. Multiple PLS measures were found to be independent risk factors for COVID-19 pneumonia progression in KTRs.

This study revealed a robust correlation between PLS and severe COVID-19 pneumonia progression in KTRs. PLS monitoring could facilitate real-time diagnosis and therapy for infection, as well as timely and precisive adjustment of immunosuppression instructions, for KTRs with COVID-19.

Within the intricate tapestry of the global SARS-CoV-2 pandemic, this study delves into the intricate interplay of clinical data to elucidate prognostic factors associated with complications in patients concomitantly afflicted with hematological disorders and SARS-CoV-2. An exhaustive analysis of 71 individuals, spanning the period from November 2022 to March 2023, aims to unveil distinctive clinical characteristics and explicate the nuanced determinants steering the trajectory of the disease. The updated findings reveal a multi-faceted correlation, underscoring the complex interplay of clinical parameters. Among individuals with hematological disorders, anomalously elevated ferritin levels are closely associated with the development of SARS-CoV-2 pneumonia, while interferon-γ is intricately linked to the severity of SARS-CoV-2. Conversely, elevated ferritin levels, increased D-dimer and fibrin degradation products, along with significantly elevated iron levels, manifest a significant association with patient mortality. Intriguingly, those in patients in complete hematologic remission confront an augmented risk of developing SARS-CoV-2 pneumonia, while those abstaining from anti-tumor treatments exhibit mitigated case severity. This study unveils the intricate interplay of clinical factors impacting the prognosis of SARS-CoV-2 complications in individuals with hematological disorders. The cognizance of aberrant interferon-γ activation and nuanced associations with ferritin, iron levels, and coagulation markers contributes to a more holistic comprehension of the prognostic landscape.

Rapid dissemination of Klebsiella pneumoniae carbapenemase (KPC) is a leading cause of treatment failure, significantly increasing morbidity and mortality rates among inpatients, particularly in the intensive care unit (ICU). This study aimed to detect the occurrence of carbapenemase- and carbapenem-resistant-encoding genes in K. pneumoniae isolates from COVID-19 positive and negative patients, and to assess their impact on patient outcomes. A prospective analysis was conducted at a tertiary care hospital in Saudi Arabia, collecting 97 carbapenem-resistant K. pneumoniae (CRKP) isolates from patients with COVID-19 during 2020-2021. Isolates were obtained from various clinical specimens. Antimicrobial susceptibility assays were performed using the Automated Vitek-2 system, and data were analyzed using IBM SPSS Statistics. The predominant carbapenemases identified were Oxacillinase-48 (OXA-48), followed by KPC and New Delhi metallo-β-lactamase (NDM), with Imipenemase (IMP) and Verona integron-encoded metallo-β-lactamase (VIM) being the least prevalent. COVID-19 did not significantly affect the distribution of these genes (P>0.05); however, COVID-19 status and age over 60 years significantly impacted the outcomes of CRKP patients. Other factors such as gender, total ICU or ward stay, and comorbidities did not significantly affect CRKP infection outcomes. The most common carbapenem-resistant genes identified were blaKPC, blaNDM, and blaOXA-48; however, they were not significantly associated with increased mortality.

Coronavirus disease 2019 (COVID-19) survivors are concerned about the likelihood of developing further diseases. This study examines the global trends in scientific research on diabetes associated with COVID-19 from several perspectives. Bibliometric analyses are used to undertake a scientific review of the literature. The Web of Science Core Collection (WoSCC) database was used to acquire bibliographic information on diabetes related to COVID-19 from Jan 2020 to Dec. 2023. The visual map was built via advanced CiteSpace 6.2.R6. 7,348 papers were found. Khunti Kamlesh and Rizzo-Manfredi are the most well-known high-yield authors in this area, and the top ten authors collaborate extensively. Most of these papers came from universities. Harvard Medical School has the most publications, followed by Wuhan University and Huazhong University of Science and Technology. China and the United States are the countries with the most publications. Angiotensin-converting enzymes, chronic disease, intensive care unit, viral infection, and gestational diabetes mellitus were scored 0-11, 2, 3, and 4, respectively. Zhou et al.'s work on this topic, which appeared in the prominent medical journal The Lancet, was cited 1,366 times, highlighting its importance. "clinical characteristics," "diabetes mellitus," "metabolic syndrome," and "angiotensin-converting enzyme" were used as keywords for reference co-citation and clustering data identify. Over the last four years, related investigations have focused primarily on observing clinical aspects. This report is important for developing treatment strategies, directing future research, and guiding clinical practice.

In 2021, vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were developed and the Omicron variant emerged. This study compared the characteristics, treatments, and mortality of patients with coronavirus disease 2019 (COVID-19) between 2022 and 2020-2021, using administrative claims data linked including vaccine records in a Japanese city. Patients who underwent COVID-19 antigen or polymerase chain reaction tests and were diagnosed with COVID-19 were identified. Patient characteristics, treatments, and mortality were compared between 2022 and 2020-2021 among those diagnosed with COVID-19. We identified 26,262 patients with COVID-19. The mortality in 2022 was lower than that in 2020-2021 (0.6% vs. 1.7%; P < 0.01). Patients in 2022 were significantly less likely to receive oxygen therapy, high-flow nasal oxygenation, mechanical ventilation, steroids, and tocilizumab than those in 2020-2021. Among the deceased, the proportion of those aged ≥65 years was significantly higher in 2022 than in 2020-2021 (98.4% vs. 88.6%). The logistic regression analysis indicated, older age, male sex, and ≥3 comorbidities were associated with higher mortality, whereas ≥3 vaccinations were associated with lower mortality. Patients with COVID-19 in 2022 were less likely to require respiratory care or succumb to the disease. Older patients were more likely to die in 2022 than in 2020-2021.

Background/Objectives: The coronavirus disease 2019 (COVID-19) pandemic has significantly affected global health, economies, and societies, necessitating a deeper understanding of the factors influencing its spread and severity. Methods: This study employed text network analysis to examine relationships among various risk factors associated with severe COVID-19. Analyzing a dataset of published studies from January 2020 to December 2021, this study identifies key determinants, including age, hypertension, and pre-existing health conditions, while uncovering their interconnections. Results: The analysis reveals five thematic clusters: biomedical, occupational, demographic, behavioral, and complication-related factors. Temporal trend analysis reveals distinct shifts in research focus over time. In early 2020, studies primarily addressed immediate clinical characteristics and acute complications of COVID-19. By mid-2021, research increasingly emphasized long COVID, highlighting its prolonged symptoms and impact on quality of life. Concurrently, vaccine efficacy became a dominant topic, with studies assessing protection rates against emerging viral variants, such as Alpha, Delta, and Omicron. This evolving landscape underscores the dynamic nature of COVID-19 research and the adaptation of public health strategies accordingly. Conclusions: These findings offer valuable insights for targeted public health interventions, emphasizing the need for tailored strategies to mitigate severe outcomes in high-risk groups. This study demonstrates the potential of text network analysis as a robust tool for synthesizing complex datasets and informing evidence-based decision-making in pandemic preparedness and response.

Severe fever with thrombocytopenia syndrome (SFTS) is a fatal tick-borne infectious disease that lacks effective treatments. Dynamic analysis that reflects changes in the SFTS patient's condition is needed. This study aimed to evaluate the time-dependent predictive performance of key biomarkers using a time-dependent Cox regression model. A retrospective multicenter cohort study was conducted on 440 SFTS patients hospitalized in South Korea between 2013 and 2024. Time-dependent Cox regression and time-dependent receiver operating characteristic (ROC) analyses were applied to assess the prognostic value of Blood Urea Nitrogen (BUN), Prothrombin Time (PT), and Activated Partial Thromboplastin Time (aPTT). Missing data were handled using multiple imputation. aPTT consistently demonstrated high predictive accuracy (AUC > 0.90) throughout the disease course, indicating its sustained role in coagulopathy. PT exhibited strong early-stage predictive power (AUC = 0.86 on day 2) but declined over time, reflecting its utility for early monitoring. BUN showed a progressive increase in predictive performance (AUC = 0.70 on day 2 to AUC = 0.78 on day 8), supporting its relevance in later stages of disease progression. Non-survivors exhibited significantly higher levels of BUN, PT, and aPTT compared to survivors. This study demonstrates the utility of time-dependent analysis for evaluating dynamic biomarker changes in SFTS patients. aPTT is a robust predictor throughout the disease course, while PT is valuable for early-stage assessment and BUN for later-stage management. These findings suggest the importance of integrating dynamic biomarker monitoring into clinical decision-making to improve prognosis in SFTS patients.

The clinical spectrum of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is broad; it can range from asymptomatic cases to mild upper respiratory tract illness, respiratory failure, and severe multiorgan failure resulting in death. Therefore, it is important to identify the clinical course of the disease and the factors associated with mortality.

The aim of this study is to identify the risk factors associated with the severity of the disease, intensive care unit admission, and mortality in COVID-19 patients.

A total of 1075 patients with clinical and radiological findings compatible with COVID-19 pneumonia and positive SARS-CoV-2 PCR were selected and retrospectively screened. All included patients were classified according to the 7th edition of the 2019 Coronavirus Disease Guidelines published by the National Health Commission of China.

It was observed that elevated white blood count (WBC) increased the severity of COVID-19 by 3.26 times and the risk of intensive care unit (ICU) admission by 3.47 times. Patients with high D-dimer levels had a 91% increased risk, and those with high fibrinogen levels had a 2.08 times higher risk of severe disease. High C-reactive protein (CRP) values were found to increase disease severity by 6.89 times, mortality by 12.84 times, and ICU admission by 3.37 times.

Identifying the factors associated with disease severity, ICU admission, and mortality in COVID-19 patients could help reduce disability and mortality rates in pandemics.

A multiplexed microarray chip (Immuno-μSARS2) aiming at providing information on the prognosis of the COVID-19 has been developed. The diagnostic technology records information related to the profile of the immunological response of patients infected by the SARS-CoV-2 virus. The diagnostic technology delivers information on the avidity of the sera against 28 different peptide epitopes and 7 proteins printed on a 25 mm2 area of a glass slide. The peptide epitopes (12-15 mer) derived from structural proteins (Spike and Nucleocapsid) have been rationally designed, synthesized, and used to develop Immuno-μSARS2 as a multiplexed and high-throughput fluorescent microarray platform. The analysis of 755 human serum samples (321 from PCR+ patients; 288 from PCR- patients; 115 from prepandemic individuals and classified as hospitalized, admitted to intensive-care unit (ICU), and exitus) from three independent cohorts has shown that the chips perform with a 98% specificity and 91% sensitivity identifying RT-PCR+ patients. Computational analysis utilized to correlate the immunological signatures of the samples analyzed indicate significant prediction rates against exitus conditions with 82% accuracy, ICU admissions with 80% accuracy, and 73% accuracy over hospitalization requirement compared to asymptomatic patients' fingerprints. The miniaturized microarray chip allows simultaneous determination of 96 samples (24 samples/slide) in 90 min and requires only 10 μL of sera. The diagnostic approach presented for the first time here could have a great value in assisting clinicians in decision-making based on the information provided by the Immuno-μSARS2 regarding progression of the disease and could be easily implemented in diagnostics of other infectious diseases.

Severe fever with thrombocytopenia syndrome (SFTS) has a high mortality rate and is easily misdiagnosed as hemorrhagic fever with renal syndrome (HFRS), particularly in resource-limited rural areas where early diagnosis remains challenging. This study used routine laboratory parameters, epidemiology and clinical manifestations to develop a model for the early diagnosis of SFTS and identify fatal risk factors, ultimately reducing mortality of SFTS.

This retrospective cohort study included 141 SFTS and 141 HFRS patients. Of these, 94 patients with SFTS were allocated to the model cohort for mortality risk identification by using multivariable Cox regression analysis. Sensitivity, specificity, and predictive values were calculated from validation cohort to assess the clinical values. Then, we analyzed 62 SFTS and 113 HFRS using multivariable logistic regression to identify SFTS. Receiver operating characteristic (ROC) curve analysis was used to evaluate their diagnostic value.

Multivariate Cox regression analysis showed that blood urea nitrogen (BUN) ≥10.22mmol/L activated partial thromboplastin time (APTT) ≥58.05s and D-dimer ≥4.68mg/L were the risk factors for death in SFTS. This combined indicators had an area under the curve (AUC) of 0.91 (95% CI: 0.847-0.973), with a sensitivity and specificity of 86%, respectively. Any indicator was achieved the cutoff, and sensitivity and specificity in the validation group were 93% and 54%. Multivariable logistic regression showed that age (OR: 1.10) and initial laboratory indicators including WBC (OR: 0.48), Cr (OR: 0.86), CK (OR: 1.01), and APTT (OR: 1.09) can be used to identify SFTS from HFRS. This model achieved an AUC value of 0.97 (95% CI: 0.977-0.999) and 0.98 (95% CI: 0.958-1.000) in validation cohort.

In resource-limited rural hospitals, the integration of routine laboratory parameters with epidemiology and clinical manifestations demonstrates enhanced sensitivity for early SFTS identification and mortality risk stratification to reduce mortality rate.

Epidemiological investigations consistently demonstrate an overrepresentation of the elderly in COVID-19 hospitalizations and fatalities, making the advanced age as a major predictor of disease severity. Despite this, a comprehensive understanding of the cellular and molecular mechanisms explaining how old age represents a major risk factor remain elusive. To investigate this, we compared SARS-CoV-2 infection outcomes in young adults (2 months) and geriatric (15-22 months) mice. Both groups of K18-ACE2 mice were intranasally infected with 500 TCID50 of SARS-CoV-2 Delta variant with analyses performed on days 3, 5, and 7 post-infection (DPI). Analyses included pulmonary cytokines, lung RNA-seq, viral loads, lipidomic profiles, and histological assessments, with a concurrent evaluation of the percentage of mice reaching humane endpoints. The findings unveiled notable differences, with aged mice exhibiting impaired viral clearance, reduced survival, and failure to recover weight loss due to infection. RNA-seq data suggested greater lung damage and reduced respiratory function in infected aged mice. Additionally, elderly-infected mice exhibited a deficient antiviral response characterized by reduced Th1-associated mediators (IFNγ, CCL2, CCL3, CXCL9) and diminished number of macrophages, NK cells, and T cells. Furthermore, mass-spectrometry analysis of the lung lipidome indicated altered expression of several lipids with immunomodulatory and pro-resolution effects in aged mice such as Resolvin, HOTrEs, and NeuroP, but also DiHOMEs-related ARDS. These findings indicate that aging affects antiviral immunity, leading to prolonged infection, greater lung damage, and poorer clinical outcomes. This underscores the potential efficacy of immunomodulatory treatments for elderly subjects experiencing symptoms of severe COVID-19.

Background/Objectives: Mortality from COVID-19 in intensive care units (ICUs) was not clearly reported in many regions during the first wave. We aimed to assess the characteristics and outcomes of ICU patients with COVID-19 in Saudi Arabia. Methods: This was a secondary data analysis of the Convalescent Plasma Trial. All patients who were recruited from King Fahad Hospital of the University (KFHU) in the Eastern Region of Saudi Arabia between 13 March 2020 and 13 September 2020 were included. Characteristics and outcomes, differences in characteristics and outcomes between Saudi and non-Saudi populations, and predictors of mortality were assessed. Results: The KFHU recruited 185 ICU patients with COVID-19. Of those, 90 (48.6%) were Saudi, and 95 (51.4%) were non-Saudi. The overall mean age was 56.7 years, and 71.9% were males. Compared with Saudis, non-Saudis were younger, with a mean age of 54.4 years, were more likely to be males (81.1%), and had a higher median respiratory rate (28.0 breaths/min vs. 24.0), a lower percentage of blood-oxygen saturation (86.0% vs. 91.0%), and higher median levels of ferritin per µg/L (820 vs. 550). The overall mortality rate was 33.0% (n = 61). The mortality rate in non-Saudis (42.1%) was higher than that in Saudis (23.3%). The variables associated with increased mortality included non-Saudi status (odds ratio [OR] 2.66; 95% CI: 1.05, 6.72), ferritin (OR 1.01; 95% CI: 1.00, 1.02), and intubation (OR 8.55; 95% CI: 2.92, 24.97). Conclusions: Since the mortality rate in non-Saudis was greater than that in Saudis, more efforts should be made to improve social determinants of health across non-Saudis in our region.

The relationships between air pollution, genetic susceptibility, and COVID-19-related outcomes, as well as the potential interplays between air pollution and genetic susceptibility, remain largely unexplored. The Cox proportional hazards model was used to assess associations between long-term exposure to air pollutants and the risk of COVID-19 outcomes (infection, hospitalization, and death) in a COVID-19-naive cohort (n = 458,396). Additionally, associations between air pollutants and the risk of COVID-19 severity (hospitalization and death) were evaluated in a COVID-19 infection cohort (n = 110,216). Furthermore, this study investigated the role of host genetic susceptibility in the relationships between exposure to air pollutants and the development of COVID-19-related outcomes. Long-term exposure to air pollutants was significantly associated with an increased risk of COVID-19-related outcomes in the COVID-19 naive cohort. Similarly, in COVID-19 infection cohort, hazard ratios (HRs) for COVID-19 hospital admission were 1.23 (1.19, 1.27) for PM2.5 and 1.22 (1.17, 1.26) for PM10, whereas HRs for COVID-19 death were 1.28 (1.18, 1.39) for PM2.5 and 1.25 (1.16, 1.36) for PM10. Notably, significant interactions were found between PM2.5/PM10 and genetic susceptibility in COVID-19 death. In COVID-19 infection cohort, participants with both high genetic risk and high air pollutants exposure had 1.86- to 1.97-fold and 1.91- to 2.14-fold higher risk of COVID-19 hospitalization and death compared to those with both low genetic risk and low air pollutants exposure. Exposure to air pollution is significantly associated with an increased burden of severe COVID-19, and air pollution-gene interactions may play a crucial role in the development of COVID-19-related outcomes.

Nanoemulsions, which are characterized by their nanometer-scale droplets, have gained significant attention in different fields, such as medicine, food, cosmetics, and agriculture, because of their unique properties. With an increasing number of countries engaging in research on nanoemulsions, interest in their properties, preparation methods, and applications has increased. Hence, tracing the relevant research on nanoemulsions published in the past ten years on a global scale, by conducting data mining and visualization analysis on a sufficiently large text dataset through bibliometrics, sorting out and summarizing certain indicators, the development history, research status and research hotspots in the field of nanoemulsions can be clearly revealed, providing reference value and significance for subsequent research. This bibliometric review examines the research landscape of nanoemulsions from 2013-2023 via the SCI-E and SSCI databases, providing insights into the current status, hotspots, and future trends of this field. To offer a comprehensive overview, this analysis includes publication counts, author keywords, institutional contributions, research areas, prolific authors, highly cited papers and hot research papers. The findings reveal that China led in nanoemulsions research, followed by USA, India, and Brazil, with the University of Massachusetts emerging as a key player with the highest average number of citations per article (ACPP) and h-index. Food Chemistry, Pharmaceutics, and the Journal of Drug Delivery Science and Technology are among the top journals publishing in this area. Chemistry, pharmacology, and pharmacy emerged as the primary research domains, with McClements DJ as the most prolific and influential author. In keyword analysis, essential oil nanoemulsions are currently the main preparation direction, and various characteristics of nanoemulsions, such as their bioavailability, stability, biocompatibility, and antioxidant and antibacterial properties, have also been studied extensively. Research hotspots are focused mostly on the development of new applications and technologies for nanoemulsions.

The rapid spread of COVID-19 have overwhelmed health systems, especially in the care of chronic disease such as tuberculosis and diabetes. The objective of the study was to analyze the magnitude and relevance of tuberculosis-diabetes and diabetes-COVID-19 comorbidities in spatial risk areas and their factors associated with unfavorable outcomes in the Brazilian population between 2020 and 2022. An ecological study was carried out in Brazilian municipalities. The population was composed by cases of tuberculosis-diabetes and diabetes-COVID-19 comorbidities, registered in the Influenza Epidemiological Surveillance Information System (SIVEP-GRIPE) and in DATASUS from 2020 to 2022. The Scan Statistics technique was used to identify spatial risk clusters. Binary logistic regression was then employed to understand the relationship between outcomes and comorbidities, considering clinical and sociodemographic variables. A total of 24,750 cases of tuberculosis-diabetes comorbidity were identified, which consisted of an incidence of 3.2 cases per 100,000 inhabitants. Risk clusters were identified in the Central-West and North regions. 303,210 cases of diabetes- COVID-19 comorbidity were identified, resulting in an incidence of 0.4 cases per 100,000 inhabitants. São Paulo-SP, Rio de Janeiro-RJ and Belo Horizonte-MG were the municipalities with the highest spatial risk of illness. The analysis of the spatial risk areas revealed distinct patterns in the geographic distribution of comorbidities. Based on the findings, it is concluded that comorbidities between tuberculosis and diabetes, as well as between COVID-19 and diabetes, represent significant challenges for public health in Brazil, deserving attention from health authorities and the scientific community.

Remdesivir (RDV) and nirmatrelvir/ritonavir (NMVr) are among the most widely used antivirals in the treatment of COVID-19, aiming to reduce disease severity and progression. Adverse neuropsychiatric effects, such as anxiety, sleep disturbances, and movement disorders, have emerged as significant concerns associated with these treatments. To better understand the safety profiles of RDV and NMVr, this study performs a pharmacovigilance analysis of individual case safety reports (ICSRs) from the EudraVigilance (EV) database. Objectives: This study evaluates the risk of neuropsychiatric adverse events associated with RDV and NMVr. Comparisons with other antiviral drugs, including darunavir, sofosbuvir, ribavirin, tenofovir, ritonavir, and sotrovimab, are also performed to develop a comprehensive understanding of the safety profiles. Methods: A retrospective analysis of ICSRs submitted to EV until 7 July 2024, with data extraction on 12 July 2024, was conducted. Demographic characteristics (age, sex, geographic region, and reporter type) and case severity were included in the descriptive analysis. Disproportionality analysis using reporting odds ratio (ROR) and 95% confidence intervals (CI) was performed to compare adverse drug reaction (ADRs) frequencies across 27 system organ classes (SOCs), with emphasis on "Nervous system disorders" and "Psychiatric disorders. Results: The total number of ICSRs was significantly higher for NMVr (n = 8078) compared to RDV (n = 3934). Nervous system disorders accounted for 3.07% of the total RDV reports and for 17.31% of NMVr reports, while psychiatric disorders represented 0.92% of the total ADRs reported for RDV (n = 60) and 3.61% for NMVr (n = 672). On the other hand, RDV showed a significantly lower frequency of reporting headache compared to NMVr (ROR: 0.1057; 95% CI: 0.0676-0.1653). Conclusions: NMVr presents a higher risk of neuropsychiatric ADRs than RDV, underscoring the need for enhanced monitoring, particularly in patients with preexisting central nervous system (CNS) conditions. These findings contribute to optimizing antiviral safety and informing clinical decision making.

The global impact of SARS-CoV-2 and its associated coronavirus disease (COVID-19) has necessitated urgent characterization of prognostic biomarkers. This study aimed to delineate the epidemiological and clinical predictors of mortality among hospitalized COVID-19 patients.

A retrospective cohort study was conducted on 123 patients with laboratory-confirmed COVID-19 admitted to Huoshenshan Hospital (Wuhan, China) from 1 February 2020 to 30 April 2020. Kaplan-Meier curve and multivariate Cox regression were used to assess the independent factors with survival time. Statistical significance was set at a p-value of <0.05.

The cohort exhibited a mortality rate of 49.6% (61/123), with the critical clinical type (HR = 7.970, p = 0.009), leukocytosis (HR = 3.408, p = 0.006), and lymphopenia (HR = 0.817, p = 0.038) emerging as independent predictors of reduced survival. Critical-type patients demonstrated significantly elevated inflammatory markers (neutrophils: 10.41 ± 6.23 × 109/L; CRP: 104.47 ± 29.18 mg/L) and coagulopathy (D-dimer: 5.21 ± 2.34 μg/ml) compared to non-critical cases. Deceased patients exhibited pronounced metabolic derangements, including hyperglycemia (9.81 ± 2.07 mmol/L) and hepatic dysfunction (ALP: 174.03 ± 30.13 U/L).

We revealed the epidemiological and clinical features of different clinical types of SARS-CoV-2 as summarized in this paper. We found that critical type, leukocyte, and lymphocyte are risk factors that affect survival time, which could be an early and helpful marker to improve management of COVID-19 patients.

The global pandemic of novel coronavirus pneumonia (COVID-19) has resulted in millions of deaths over the past three years. As one of the most commonly affected extra-pulmonary organs, numerous studies have reported varying degrees of liver injury in a significant proportion of patients with COVID-19, particularly in severe and critically ill patients. Early prediction of liver dysfunction in hospitalized patients would facilitate the clinical management of COVID-19 and improve clinical prognosis, but reliable and valid predictive models are still lacking.MethodsWe collected data from 286 patients with RT-PCR confirmed COVID-19 admitted to various ICUs from the case system. These patients were randomly divided into a training cohort (50%) and a validation cohort (50%). In the training cohort, we first used ROC curves to measure the predictive efficiency of each of the variables for the development of liver damage during hospitalization in patients with COVID-19, followed by LASSO regression analysis to screen the variables for predictive models and logistic regression analysis to identify relevant risk factors. A nomogram based on these variables was created following the above model. Finally, the efficiency of the prediction models in the training and validation cohorts was assessed using AUC, consistency index (C index), calibration curves and Decision Curve Analysis.ResultsOut of a total of 80 parameters for COVID-19 patients admitted to the ICUs, 10 were determined to be significantly associated with the occurrence of liver dysfunction during hospitalization. Based on these predictors, further prediction models were used to construct and develop a nomogram that was offered for practical clinical application. The C-index of the column line graphs for the training and validation cohorts was 0.956 and 0.844 respectively. in addition, the calibration curves for the model showed a high degree of agreement between the predicted and actual incidence of liver dysfunction in patients with COVID-19.ConclusionBy developing a predictive model and associated nomogram, we predicted the incidence of liver dysfunction during hospitalization in patients with COVID-19 in the ICU. The model's predictive performance was determined in both the training and validation cohorts, contributing to the clinical management of COVID-19.

Background: COVID-19 has largely become an endemic disease in many regions, with sporadic outbreaks, with some areas where the disease shows a seasonal pattern like the influenza virus. The focus has shifted towards managing mild and moderate forms of disease through outpatient care, aiming to prevent healthcare system overload. Consequently, identifying markers that could be used in stratifying the risk and the prognostic assessment has become crucial. Cardiovascular implications of COVID-19 are a critical area of research due to their significant impact on disease severity, mortality, and morbidity. Methods: We conducted a retrospective, observational study and included 472 patients, diagnosed with COVID-19, all of whom were admitted to Prof. Dr. Matei Bals National Institute of Infectious Disease, Bucharest, Romania. Levels of cardiac biomarkers like creatine kinase (CK), creatine kinase-myocardial band (CKMB), myoglobin, troponins, and NT-pro-BNP were measured and analyzed in relation to clinical presentation and outcomes. Results: We combined CKMB, myoglobin, and troponin I to predict hospital length of stay (LOS). Our model significantly predicted LOS (F = 12.537, p = 0.0001), with higher levels associated with prolonged stays (β = 0.166, p = 0.000). Logistic regression demonstrated that the combination of elevated CKMB and myoglobin levels significantly increased the odds of a longer LOS (OR = 1.679, p = 0.000). Furthermore, we found significant correlations with acute respiratory failure (p = 0.001), severe forms of disease (p = 0.000), and the development of complications during hospitalization (p = 0.027). Conclusions: These findings emphasize the value of combining cardiac biomarkers to stratify risk and predict hospital outcomes in COVID-19 patients. Routine cardiac monitoring and targeted management strategies could decrease the risk of complications, reducing the LOS. Our findings highlight the potential of cardiac biomarkers as prognostic tools to stratify risk, guide clinical interventions, and improve outcomes in COVID-19 patients.

Age is among the strongest risk factors for severe outcomes from SARS-CoV-2 infection. Here we describe upper respiratory tract (URT) and peripheral blood transcriptomes of 202 participants (age range of 1 week to 83 years), including 137 non-hospitalized individuals with mild SARS-CoV-2 infection and 65 healthy individuals. Among healthy children and adolescents, younger age is associated with higher URT expression of innate and adaptive immune pathways. SARS-CoV-2 infection induces broad upregulation of URT innate and adaptive immune responses among children and adolescents. Peripheral blood responses among SARS-CoV-2-infected children and adolescents are dominated by interferon pathways, while upregulation of myeloid activation, inflammatory, and coagulation pathways is observed only in adults. Among SARS-CoV-2-infected individuals, fever is associated with blunted URT immune responses and more pronounced systemic immune activation. These findings demonstrate that immune responses to SARS-CoV-2 differ across the lifespan, from distinct signatures in childhood and adolescence to age-associated alterations in adults.

Objectives: To compare the health status, exercise capacity, and health-related quality of life (HRQoL) in survivors of COVID-19-associated acute respiratory distress syndrome (ARDS) at 8, 12, and 24 months post-diagnosis. Methods: We conducted a prospective, single-center follow-up study embedded within a larger multicenter cohort of adults with COVID-19 who required hospital admission. Eligible participants underwent clinical interviews, physical examinations, chest radiography, and the 6-min walk test (6MWT). Standardized scales were used to assess post-traumatic stress disorder (PTSD), anxiety, depression, and HRQoL. Results: Out of 1295 patients with COVID-19, 365 developed ARDS, of whom 166 survived. After excluding deaths and loss to follow-up, 95 patients were monitored for 24 months. Over 60% of patients had persistent symptoms, though significant improvements were recorded in quality of life and physical recovery. More than 70% recovered their previous physical capacity, but 15% did not return to their usual lifestyle habits. Symptoms such as arthralgia and fatigue decreased, but cognitive issues, such as memory loss and insomnia, persisted. Radiological improvements were noted, although pulmonary function remained impaired. The prevalence of PTSD and anxiety decreased, while depression remained stable at around 30%. Conclusions: Long COVID continues to impose significant physical, mental, and social challenges. Symptoms like fatigue and anxiety have a profound impact on daily life. Strategies are urgently needed to help patients regain health and resume their normal lives.

Immunocompromised patients are at increased risk for severe outcomes from COVID-19 due to their altered immune responses, yet their inflammatory profiles and the interplay between immunosuppression remain poorly understood. We aimed to illustrate the inflammation profile and clinical outcomes of hospitalized immunocompromised patients with COVID-19.

We conducted a retrospective study using a multicenter database and included adult hospitalized patients with Corona virus disease 2019 (COVID-19) in China's late 2022 COVID-19 wave. Crude and adjusted 28- and 60-day mortality was compared between the two groups. Inflammatory phenotypes were evaluated by serum interleukin-6 (IL-6) and C-reactive protein (CRP) level. The interplay between overt inflammation and immunosuppression was analyzed.

Among the 4078 included patients, 348 (8.5%) were immunocompromised. Immunocompromised patients had lower crude mortality but higher adjusted mortality at 28-day (hazard ratio [HR] = 1.55; 95% CI 1.08 to 2.23) and 60-day (HR = 1.47; 95% CI 1.05 to 2.06). Besides, immunocompromised patients had a higher risk of developing hyperinflammation (odd ratio [OR] =1.92; 95% CI 1.47 to 2.50, p <0.001). Moreover, hyperinflammation mediated a major part of the deleterious survival effect of immunosuppression on COVID-19.

Immunodeficiency not only increases short-term mortality risk but also predisposes patients to hyperinflammation. The complex interplay between immunosuppression, hyperinflammation, and COVID-19 outcomes warrants more detailed profiling of inflammation and immunity in this population.