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.

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.

Artificial intelligence (AI) tools to support clinicians in providing patient-centered care can contribute to patient empowerment and care efficiency. We aimed to draft potential AI tools for tailored patient support corresponding to patients' needs and assess clinicians' perceptions about the usefulness of those AI tools. To define patients' issues, we analyzed 528,199 patient messages of 11,123 patients with diabetes by harnessing natural language processing and AI. Applying multiple prompt-engineering techniques, we drafted a series of AI tools, and five endocrinologists evaluated them for perceived usefulness and risk. Patient education and administrative support for timely and streamlined interaction were perceived as highly useful, yet deeper integration of AI tools into patient data was perceived as risky. This study proposes assorted AI applications as clinical assistance tailored to patients' needs substantiated by clinicians' evaluations. Findings could offer essential ramifications for developing potential AI tools for precision patient care for diabetes and beyond.

The United States has experienced high surge in COVID-19 cases since the dawn of 2020. Identifying the types of diagnoses that pose a risk in leading COVID-19 death casualties will enable our community to obtain a better perspective in identifying the most vulnerable populations and enable these populations to implement better precautionary measures.

To identify demographic factors and health diagnosis codes that pose a high or a low risk to COVID-19 death from individual health record data sourced from the United States.

We used logistic regression models to analyze the top 500 health diagnosis codes and demographics that have been identified as being associated with COVID-19 death.

Among 223,286 patients tested positive at least once, 218,831 (98%) patients were alive and 4,455 (2%) patients died during the duration of the study period. Through our logistic regression analysis, four demographic characteristics of patients; age, gender, race and region, were deemed to be associated with COVID-19 mortality. Patients from the West region of the United States: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming had the highest odds ratio of COVID-19 mortality across the United States. In terms of diagnoses, Complications mainly related to pregnancy (Adjusted Odds Ratio, OR:2.95; 95% Confidence Interval, CI:1.4 - 6.23) hold the highest odds ratio in influencing COVID-19 death followed by Other diseases of the respiratory system (OR:2.0; CI:1.84 - 2.18), Renal failure (OR:1.76; CI:1.61 - 1.93), Influenza and pneumonia (OR:1.53; CI:1.41 - 1.67), Other bacterial diseases (OR:1.45; CI:1.31 - 1.61), Coagulation defects, purpura and other hemorrhagic conditions(OR:1.37; CI:1.22 - 1.54), Injuries to the head (OR:1.27; CI:1.1 - 1.46), Mood [affective] disorders (OR:1.24; CI:1.12 - 1.36), Aplastic and other anemias (OR:1.22; CI:1.12 - 1.34), Chronic obstructive pulmonary disease and allied conditions (OR:1.18; CI:1.06 - 1.32), Other forms of heart disease (OR:1.18; CI:1.09 - 1.28), Infections of the skin and subcutaneous tissue (OR: 1.15; CI:1.04 - 1.27), Diabetes mellitus (OR:1.14; CI:1.03 - 1.26), and Other diseases of the urinary system (OR:1.12; CI:1.03 - 1.21).

We found demographic factors and medical conditions, including some novel ones which are associated with COVID-19 death. These findings can be used for clinical and public awareness and for future research purposes.

COVID-19, severe acute respiratory syndrome coronavirus 2, rapidly spread worldwide. Severe and critical patients are expected to rapidly deteriorate. Although several studies have attempted to uncover the mechanisms underlying COVID-19 severity, most have focused on the perturbations of single genes. However, the complex mechanism of COVID-19 involves numerous perturbed genes in a molecular network rather than a single abnormal gene. Thus, we aimed to identify COVID-19 severity-specific markers in the Japanese population using gene network analysis. In order to reveal the severity-specific molecular interplays, we developed a novel computational network biology strategy that measures dissimilarity between networks based on the comprehensive information of gene network (i.e., expression levels of genes and network structure) by using Kullback-Leibler divergence. Monte Carlo simulations demonstrated the effectiveness of our strategy for differential gene network analysis. We applied this method to publicly available whole blood RNA-seq data from the Japan coronavirus disease 2019 Task Force and identified differentially regulated molecular interplays between 368 severe and 105 non-severe samples. Our analysis suggests the gene network between HLA class II, CIITA, and CD74 as a COVID-19 severity specific molecular marker. Although the association between HLA class II and COVID-19 has been demonstrated, our data analysis revealed that the molecular interplay of HLA class II with its target and/or regulator is a crucial marker for COVID-19 severity. Our findings from computational network biology analysis suggest that suppression and activation of the molecular interplay between HLA class II, CIITA, and CD74 provide crucial clues to uncover the mechanisms of COVID-19 severity.

SARS-CoV-2 poses significant challenges to people living with diabetes (PLWD). This systematic review aimed to explore the impact of COVID-19 on mortality, complications associated with diabetes and haematological parameters among PLWD.

Systematic review and meta-analysis using the Grading of Recommendations Assessment, Development and Evaluation (GRADE).

EMBASE, MEDLINE, Cochrane Central Register of Controlled Trials and LILACS were searched between 1 December 2019 and 14 January 2025.

Eligible studies included case-control and cohort studies involving PLWD categorised into two groups: those with confirmed SARS-CoV-2 infection and those without.

Meta-analyses estimated the odds ratios (ORs) and mean differences (MDs) of outcomes including mortality, intensive care unit (ICU) admission, diabetic ketoacidosis (DKA), acute kidney injury, hospitalisation length and haematological parameters. We pooled results using random-effects models and assessed study quality with the Newcastle-Ottawa Scale. A funnel plot was used to detect potential publication bias. The overall certainty of evidence was assessed using GRADE.

25 of 7266 unique studies were eligible, including 1 154674 PLWD (561 558 with COVID-19 and 593 116 without COVID-19). SARS-CoV-2 infection in PLWD was associated with significantly increased mortality (OR 2.52, 95% CI 1.45 to 4.36, I2=99%), acute kidney injury (3.69, 95% CI 2.75 to 4.94, I2=0%), random plasma glucose in subjects with type 1 diabetes (MD 20.38 mg/dL, 95% CI 7.39 to 33.36, I2=0%), haemoglobin A1C in subjects with type 2 diabetes (0.21%, 95% CI 0.05 to 0.38, I2=13%), creatinine (0.12 mg/dL, 95% CI 0.04 to 0.19, I2=0%), C reactive protein (38.30 mg/L, 95% CI 4.79 to 71.82, I2=82%) and D-dimer (1.52 µg/mL, 95% CI 0.73 to 2.31, I2=0%). No significant differences were observed in the incidence of ICU admission and DKA, hospitalisation length, haemoglobin, leucocyte, lymphocyte, neutrophil to lymphocyte ratio, platelet, blood urea nitrogen, estimated glomerular filtration rate, procalcitonin, albumin, ferritin and bilirubin among PLWD with and without SARS-CoV-2 infection.

SARS-CoV-2 infection is associated with elevated risks of mortality and acute kidney injury and poor glycaemic control in PLWD, alongside increased levels of inflammatory and coagulation biomarkers. These findings underscore the urgent need for tailored clinical management strategies for PLWD with COVID-19.

CRD42023418039.

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.

Azvudine and nirmatrelvir-ritonavir are prioritized treatments for SARS-CoV-2 infection in China, but their effectiveness and safety in hospitalized patients with COVID-19 and pre-existing diabetes remains unknown. In this retrospective cohort study, we collected 32,864 hospitalized COVID-19 patients from nine hospitals, among which 636 azvudine recipients and 318 nirmatrelvir-ritonavir recipients were enrolled for final analysis after exclusion and propensity score matching. Kaplan-Meier and multivariate Cox regression analysis results showed that azvudine had a lower risk of all-cause death compared with nirmatrelvir-ritonavir for the treatment of patients with COVID-19 and pre-existing diabetes (log rank: p = 0.044; HR: 0.63; 95% CI: 0.431-0.934). No significant difference was found in composite disease progression between the two groups. Five sensitivity analyses verified the robustness of the results. Overall, azvudine may be comparable to nirmatrelvir-ritonavir in terms of both all-cause death and composite disease progression among hospitalized patients with COVID-19 and pre-existing diabetes, with acceptable adverse events.

The world is currently grappling with the potentially life-threatening coronavirus disease 2019 (COVID-19), marking it as the most severe health crisis in the modern era. COVID-19 has led to a pandemic, with the World Health Organization (WHO) predicting that individuals with diabetes are at a higher risk of contracting the virus compared to the general population. This review aims to provide a practical summary of the long-term impacts of COVID-19 on patients with diabetes. Specifically, it focuses on the effects of SARS-CoV-2 on different types of diabetic patients, the associated mortality rate, the underlying mechanisms, related complications, and the role of vitamin D and zinc in therapeutic and preventive approaches.

Relevant literature was identified through searches on PubMed, Web of Science, and Science Direct in English, up to April 2023.

COVID-19 can lead to distressing symptoms and pose a significant challenge for individuals living with diabetes. Older individuals and those with pre-existing conditions such as diabetes, coronary illness, and asthma are more susceptible to COVID-19 infection. Managing COVID-19 in individuals with diabetes presents challenges, as it not only complicates the fight against the infection but also potentially prolongs the recovery time. Moreover, the virus may thrive in individuals with high blood glucose levels. Various therapeutic approaches, including antidiabetic drugs, are available to help prevent COVID-19 in diabetic patients.

Diabetes increases the morbidity and mortality risk for patients with COVID-19. Efforts are globally underway to explore therapeutic interventions aimed at reducing the impact of diabetes on COVID-19.

People hospitalised for coronavirus disease 2019 (COVID-19) have elevated incidence of diabetes. However, it is unclear whether this is due to shared risk factors, confounding or stress hyperglycaemia in response to acute illness.

We analysed a multicentre prospective cohort study (PHOSP-COVID) of people ≥18 years discharged from NHS hospitals across the United Kingdom following COVID-19. Individuals were included if they attended at least one research visit with a HbA1c measurement within 14 months of discharge and had no history of diabetes at baseline. The primary outcome was new onset diabetes (any type), as defined by a first glycated haemoglobin (HbA1c) measurement ≥6.5% (≥48 mmol/mol). Follow-up was censored at the last HbA1c measurement. Age-standardised incidence rates and incidence rate ratios (adjusted for age, sex, ethnicity, length of hospital stay, body mass index, smoking, physical activity, deprivation, hypertension, hyperlipidaemia/hypercholesterolaemia, intensive therapy unit admission, invasive mechanical ventilation, corticosteroid use and C-reactive protein score) were calculated using Poisson regression. Incidence rates were compared with the control groups of published clinical trials in the United Kingdom by applying the same inclusion and exclusion criteria, where possible.

Incidence of diabetes was 91.4 per 1000 person-years and was higher in South Asian (incidence rate ratios [IRR] = 3.60; 1.77, 7.32; p < 0.001) and Black ethnic groups (IRR = 2.36; 1.07, 5.21; p = 0.03) compared with White ethnic groups. When restricted to similar characteristics, the incidence rates were similar to those in UK clinical trials data.

Diabetes incidence following hospitalisation for COVID-19 is high, but it remains uncertain whether it is disproportionately higher than pre-pandemic levels.

In this editorial, we have commented on the article that has been published in the recent issue of World Journal of Clinical Cases. The authors have described a case of unilateral thyroid cyst and have opined that the acute onset of infection may be linked to diabetes mellitus (DM). We have focused on the role of nutrition in the association between DM and infection. Patients with DM are at a high risk of infection, which could also be attributed to nutrition-related factors. Nutritional interventions for patients with diabetes are mainly based on a low-calorie diet, which can be achieved by adhering to a low-carbohydrate diet. However, dietary fiber supplementation is recommended to maintain the diversity of the gut microbiota. Furthermore, high-quality protein can prevent the increased risk of infection due to malnutrition. Supplementation of vitamins C, vitamins A, vitamins D, and folic acid improves blood sugar control and facilitates immune regulation. Mineral deficiencies augment the risk of infection, but the relationship with diabetes is mostly U-shaped and a good intake should be maintained.

To identify demographic, clinical and immunological factors associated with adverse COVID-19 outcomes.

A large randomised controlled trial of ChAdOx1 nCoV-19 was undertaken in Brazil. Participants were randomised 1:1 either to receive ChAdOx1 nCov-19 or to a control group. COVID-19 infections were confirmed by nucleic acid amplification test (NAAT) and classified using the WHO clinical progression scale. Anti-spike antibody responses and serum neutralising activity were measured 28 days after second vaccination in some participants. Exploratory analyses were conducted into factors associated with COVID-19 infection severity and hospitalisation, using logistic regression models adjusted for demographic and clinical factors.

10,416 participants were enrolled; 1790 had NAAT-positive COVID-19 infection; 63 cases required hospitalisation. More severe infection was associated with greater body-mass index (BMI) (odds ratio [OR] = 1.06 [95 %CI: 1.01-1.10], p = 0.01) and diabetes (OR = 3.67 [1.59-8.07], p = 0.003). Hospitalisation risk increased with greater age (OR = 1.06 [1.03-1.08], p < 0.001) and BMI (OR = 1.10 [1.05-1.16], p < 0.001). More severe infection and hospitalisation risks increased >180 days after last vaccination. In the fully vaccinated subgroup (n = 841), only greater age predicted hospitalisation (OR = 1.07 [1.03-1.12], p < 0.001). Serological responses to two vaccine doses diminished with age.

Unvaccinated individuals with high BMI and diabetes risked more severe COVID-19 outcomes. Vaccination mitigated this risk.

NCT04536051.

2019-Coronavirus reached the French island of Reunion, which is marked by a very high prevalence of metabolic disorders such as obesity and type 2 diabetes mellitus (T2DM), in March 2020. The objective was to determine the metabolic factors associated with the severity of SARS-CoV-2 infection in Reunion Island.

This retrospective observational cohort study enrolled patients who were hospitalized on the island from March 11th, 2020 to August 4th, 2021. Severe Covid-19 was defined according to the WHO's definition, including deaths. A multilevel logistic model with the circulation period of the variants as a random effect was performed.

The median age of the 681 patients enrolled was 56 years [42-68] and 54% were men. Obese patients and patients who were both diabetic and obese had an increased risk of developing severe Covid-19: 2.64 [1.46;4.78] and 2.96 [1.47;5.93], aOR [CI95%] respectively. Diabetic inpatients did not when adjusting for individual characteristics and accounting the period of circulation of variants: 1.24 [0.68;2.24] (P = 0.471).

This study reveals an unexpected prominence of obesity on T2DM (without precision) in the development of severe Covid-19. Despite a high prevalence of T2DM, this finding may partially explain why Covid-19 did not have an even greater impact on the island. Further studies should also consider the treatment of diabetes, diabetic complications, glycemic imbalance or stratify by the novel subgroups of T2DM to better understand the link between T2DM and severe Covid-19 in the Reunionese population.

Little is known about the long-term impact of diabetes on lung impairment in COVID-19 survivors over a three-year period. This study evaluated the long-term impact of diabetes on persistent radiological pulmonary abnormalities and lung function impairment in COVID-19 survivors over three years.

In this prospective, multicenter, cohort study, pulmonary sequelae were compared between COVID-19 survivors with and without diabetes. Serial chest CT scans, symptom questionnaires and pulmonary function tests were obtained 6 months, 12 months, 2 years and 3 years post-discharge. The independent predictors for lung dysfunction at the 3-year follow-up were analyzed.

A total of 278 COVID-19 survivors (63 [IQR 57-69] year-old, female: 103 [37.0%]) were included. At the 3-year follow-up, individuals in the diabetes group had higher incidences of respiratory symptoms, radiological pulmonary abnormalities and pulmonary diffusion dysfunction than those in the control group. Diabetes (OR: 2.18, 95% CI: 1.04-4.59, p = 0.034), allergy (OR: 2.26, 95% CI: 1.09-4.74, p = 0.029), female (OR: 2.70, 95% CI: 1.37-5.29, p = 0.004), severe COVID-19 (OR: 4.10, 95% CI: 1.54-10.93, p = 0.005), and fibrotic-like CT changes (OR: 5.64, 95% CI: 2.28-13.98, p < 0.001) were independent predictors of pulmonary diffusion dysfunction in COVID-19 survivors.

These results highlight the long-term deleterious effect of diabetes status on radiological pulmonary abnormalities and pulmonary dysfunction in COVID-19 survivors. This study provides important evidence support for long-term monitoring of lung abnormalities in COVID-19 recovery survivors with diabetes.

Recent studies have found that a link between people with type 1 diabetes mellitus (T1DM) are at higher risk of morbidity as well as mortality from COVID-19 infection, indicating a need for vaccination. T1DM appears to impair innate and adaptive immunity. The overabundance of pro-inflammatory cytokines produced in COVID-19 illness that is severe and potentially fatal is known as a "cytokine storm." Numerous cohorts have revealed chronic inflammation as a key risk factor for unfavorable COVID-19 outcomes. TNF-α, interleukin (IL)-1a, IL-1, IL-2, IL-6, and other cytokines were found in higher concentrations in patients with T1DM. Even more importantly, oxidative stress contributes significantly to the severity and course of COVID- 19's significant role in the progression and severity of COVID-19 diseases. Severe glucose excursions, a defining characteristic of type 1 diabetes, are widely recognized for their potent role as mediating agents of oxidative stress via several routes, such as heightened production of advanced glycation end products (AGEs) and activation of protein kinase C (PKC). Furthermore, persistent endothelial dysfunction and hypercoagulation found in T1DM may impair microcirculation and endothelium, which could result in the development of various organ failure and acute breathing syndrome.

Coronavirus disease 2019 (COVID-19) a global problem, has affected all aspects of health, that is, physical, social, and mental. Our study aimed to describe various social-demographic factors and existing comorbidities that affected mortality in COVID-19 admitted patients.

This was a hospital-based retrospective study. The study included medical records of COVID-19 patients admitted from April 2021 to August 2021. Data was entered in Microsoft Excel 2013 and analyzed in STATA version 18.0. The Chi-square test, unpaired t-test, and Cox proportional hazard model were employed for analysis.

Of the total 1156 admitted patients, 103 hospitalized patients progressed to death (8.91%). Factors found to be significant with non-survivorship were age, residence, admission status, and coexisting comorbidities. In hazard analysis, geriatric patients had 4.358 times more hazard of death. Patients with diabetes and hypertension had two times higher hazard of death than patients without these comorbidities.

Mortality of patients was substantially higher in patients' ages above 60 years and patients with comorbidities. Therefore, close monitoring and priority treatment should be provided to elderly patients and patients with comorbidities.

Traditional Chinese medicine (TCM) has developed a rich theoretical system and practical experience in fighting to infectious diseases over the past thousands of years, and has played an important role in controlling the spread owing to its unique advantages. In particular, its significant contribution to the prevention and control of Corona Virus Disease 2019 (COVID-19) is widely recognized. COVID-19 infection is mainly non-severe with a favorable overall outcome, but patients with comorbidities tend to have a poor prognosis. However, a comprehensive review of TCM for preventing and treating COVID-19 with comorbidities across various systems is still lacking. Hence, this scoping review aims to conduct a comprehensive investigation on treatment outcome of TCM for treating COVID-19 with comorbidities across various systems.

The scoping review was conducted by searching English databases including PubMed and Web of Science, and Chinese databases including China National Knowledge Infrastructure and Wanfang between January 2020 and January 2024. We followed the inclusion and exclusion criteria to identify relevant literature. Information for inclusion in the literature were subsequently extracted and consolidated.

We enrolled 13 literature that met the inclusion criteria in the review finally. Our analysis revealed that research on COVID-19 with comorbidities was mostly focused on circulatory diseases, including hypertension, heart failure, and cerebrovascular diseases, most common comorbidities were hypertension. Followed by endocrine and metabolic diseases such as diabetes, respiratory diseases including pulmonary tuberculosis and chronic obstructive pulmonary disease have been also addressed. However, there were few studies on co-infectious urogenital system disease, and no studies on the rheumatic, immune, hematological, nervous, reproductive, and skin systems diseases. Based on existing studies, TCM has significantly improved the clinical symptoms of COVID-19 with comorbidities such as fever, fatigue, dry cough, anorexia and asthma, the absorption of lung lesions, shortened the duration of viral shedding and the course of disease.

TCM has great application prospects in treating COVID-19 with comorbidities. These findings could provide important evidence for clinicians to treat COVID-19 with comorbidities. Multi-center studies are required to confirm our results in the future.

To examine inpatient COVID-19-related outcomes among patients with and without diabetes alone or with a history of established heart failure (HF) or established atherosclerotic cardiovascular disease (ASCVD).

Observational study; longitudinal analysis of registry data.

Hospitals in the USA reporting to the American Heart Association (AHA) COVID-19 Registry from January 2020 to May 2021.

20 796 individuals with diabetes (11 244 men; mean age 64.2) and 30 798 without diabetes (15 980 men; mean age 59.0) hospitalised for COVID-19 in the USA.

Primary outcome measures were all-cause mortality, inpatient major adverse cardiovascular events (MACE) and/or inpatient mechanical ventilation. Secondary outcome measures included the association with diabetes and these outcomes among those with and without pre-existing ASCVD and HF and the association with insulin use and these outcomes in patients hospitalised for COVID-19.

After adjustment for relevant covariates diabetes increased the risk of mortality (HR 1.12, 95% CI: 1.03 to 1.21), MACE (HR 1.32, 95% CI: 1.17 to 1.48) and mechanical ventilation (HR 1.33, 95% CI: 1.26 to 1.42). Among patients with established ASCVD or HF, diabetes did not modify the risk of adverse outcomes. There was a significant difference in the risk of mortality between patients taking insulin compared with those who were not (HR 1.32, 95% CI: 1.01 to 1.26); however, there was no difference in the risk of MACE or mechanical ventilation.

Diabetes was associated with a higher risk of in-hospital all-cause mortality, MACE and need for mechanical ventilation in patients hospitalised for COVID-19. Diabetes was independently associated with adverse outcomes, particularly among those without pre-existing cardiovascular disease.

Predicting post-COVID-19 diabetes is crucial for enhancing patient care and public health. This study investigates the role of metabolic factors in predicting the glycemic outcomes in patients recovering from moderate to severe COVID-19.

We conducted a retrospective analysis of 135 patients without pre-existing diabetes, selected from a cohort of 1980 individuals hospitalized between January 2020 and December 2022. Metabolic parameters, including blood glucose, Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), Triglyceride/Glucose (TyG) index, and high-sensitivity C-reactive protein (hs-CRP), were assessed at discharge and followed up after 4 months (T4) and 12 months (T12).

Statistical analysis revealed significant correlations of initial glycemia, HOMA-IR, and hs-CRP with the subsequent glycemic levels at T4 and T12. Multiple regression analysis confirmed that initial glycemia, HOMA-IR, and hs-CRP were strong predictors of elevated glycemia, while the TyG index did not show a significant predictive value. Conventional diabetes risk factors, including body mass index (BMI) and lipid profiles, showed low predictive power for post-COVID-19 glycemia.

This research highlights the critical role of metabolic and inflammatory pathways in managing glycemic control in COVID-19 patients. Markers like blood glucose, HOMA-IR, and hs-CRP are significant predictors of blood glucose levels, while the TyG index appears less helpful in this context. Early, targeted interventions based on these markers can improve patient outcomes and reduce the risk of post-COVID-19 complications like diabetes.

The 2019 coronavirus disease pandemic disrupts synchronized lifestyles and influences an individual's health status. However, Taiwan has limited studies on the impact of the epidemic on the health and lifestyle of its citizens. This study aims to investigate the impact on lifestyle and health status during the first wave of 2019 coronavirus disease in Taiwan. The 2008 to 2021 Taiwan Biobank database was adopted in this study, covering 29,572 participants and was designed into 3 time periods, Episodes 1, 2, and 3. The definition of metabolic syndrome (MetS) is based on the strict ministry of health and welfare. Logistic regression model was used to explore related risk factors. Prevalence rates of MetS were 16.5%, 17.0%, and 18.7% during Episodes 1, 2, and 3, respectively. When compared to the pre-pandemic prevalence of MetS, the odds ratios increased by 1.19 [95% confidence intervals (CIs): 1.02-1.38] during the nationwide Level 3 epidemic alert, particularly, in male aged 45 to 64 years old and females aged under 45 years old by 1.56 (95% CI: 1.14-2.13) and 1.89 (95% CI: 1.22-2.92), respectively. During pandemic, sweeping influences on Taiwanese health status, especially in the labor force, may provide a lesson in health promotion policy at a specific age.

The purpose of this study was to identify independent risk factors affecting patient survival and explore predictors of severe cases of coronavirus disease 2019 (COVID-19).

We conducted a retrospective, observational, case-control study on adult patients with severe COVID-19 who were admitted to affiliated hospitals in Tianjin between December 18, 2022, and January 31, 2023. We used univariate and multifactorial logistic regression analyses to analyze demographic indicators, comorbidity profiles, and laboratory parameters in two groups of patients (deceased and surviving) to identify independent risk factors for death in patients with severe COVID-19.

Patients in the deceased group were older than those in the survival group (p = 0.018), and there were more cases of coexisting respiratory insufficiency in the deceased group (p = 0.002). Additionally, laboratory test results for white blood cell count (WBC) and creatine kinase (CK) showed significantly higher values in the deceased group (p = 0.047 and p = 0.029, respectively), while arterial oxygen partial pressure (PAO2) showed significantly lower values compared to the survival group (p = 0.021). Age, respiratory insufficiency, WBCH (highest WBC value), CKH (highest CK value), and PAO2F (first PAO2 value) had area under curve (AUC) values of 0.698, 0.838, 0.721, 0.744, and 0.633, respectively.

The main risk factors for mortality in patients with severe COVID-19 that we identified in this study were the advanced age of patients, coexisting respiratory insufficiency, elevated levels of WBC and CK, and decreased levels of PAO2. Elevated WBC and CK laboratory parameters, in particular, demonstrated good predictive value for in-hospital mortality risk.

Epidemiological and clinical features of COVID-19 have been reported, but risk factors need to be determined to predict the course of the disease. In our study, we aimed to determine the effect of uric acid level on the severity of the disease. COVID-19 patients who received inpatient treatment between March 11, 2020 and May 30, 2020, and whose uric acid level was measured were included in the study. Demographic characteristics, comorbidities, symptoms, clinical course, laboratory parameters, and treatments were recorded. The study included 83 patients, of these 43 (52%) were males. The mean age was 59±17.1 years. The mean uric acid and albumin levels of the patients who needed oxygen were lower than in those who did not need oxygen (p=0.471 and p=0.057, respectively). There was a significant relationship between the presence of hypouricemia and mortality (p=0.019). In addition, the mean uric acid levels of patients who needed intensive care or died were lower than the mean uric acid levels of patients who did not need intensive care or who lived (p=0.665 and p=0.241, respectively). Oxygen need, intensive care need, and low uric acid level were found to be associated with increased length of hospital stay (p=0.00, p=0.001, p=0.012, and r=-0.276, respectively). Our study results suggest that uric acid levels may be associated with disease severity in the course of COVID-19.

A good adherence to pharmacological treatment in chronic pathologies such as type 2 diabetes and clinical depression is essential to improve illness prognosis.

The main goal of the TELE-DD study was to analyze the effectiveness of a telephone, psychoeducational, and individualized intervention carried out by nurses in patients with type 2 diabetes mellitus and comorbid clinical depression with prior nonadherence to pharmacological treatment. In this paper, we describe and analyze secondary outcomes of the trial intervention.

A prospective cohort study was used to assess the effectiveness of a telephonic intervention (IG) in n = 191 participants with a similar control group (CG). Adherence to pharmacological treatment was assessed using the patient's self-perceived adherence questionnaire. In addition to clinical (HbAc1, HDL, LDL), physical (body mass index, blood pressure) and psychological measures (Patient Health Questionnaire-9 affective state), and psychosocial distress due to Diabetes Distress Scale Questionnaire at 3, 6, 12, and 18 months of follow-up were also analyzed.

The proportion of "Total Adherents" in the IG was higher throughout the study. This was particularly true at month 18 of the intervention. Self-perceived adherence rates increased by 27.1% in the IG and by 1.1% in the CG. Results of clinical and physical measures were higher in the IG than in the CG at month 18 of the intervention.

The interview based on positive reinforcement as well as individualized attention and flexibility in making telephone calls and dissemination of the intervention in the media closest to the patients were key to achieving good participation and collaboration as well as continuity in adherence to treatment and self-care.

Post-COVID-19 conditions (PCCs), also known as long COVID, is persistently debilitating disorders that need investigation on their incidence, morbidity, and case-fatality rate.

The objectives of this cohort study were to determine the incidence, characteristics, case-fatality, morbidity, and recovery of post-COVID-19 symptoms throughout a two-year period of observation.

This was a population-based cohort study of post-COVID-19 cases among 12,925 SARS-CoV-2 positive individuals in eight administrative districts of Bangladesh between July and December 2021-2023. PCC was diagnosed according to WHO clinical diagnostic criteria, and the screening procedure was completed through a household screening process.

The incidence of PCC was 3.6%, the case-fatality rate was 1.92%, and the recovery rate was 9.0%. The significant predictors of PCC morbidity were geographical distribution, vaccination, comorbidities, and a longer duration of symptoms or multiple symptoms (p < 0.05).

Nearly 465 out of 522 people suffering from PCC are persistent and have a significant disability. However, the rate of recovery was 9.0%. It is necessary to investigate approaches to improve the recovery of PCC in Bangladesh.

Stressors from the COVID-19 pandemic and limited availability of mental health care services have negatively impacted youth mental health in a significant way. In the first year of the pandemic, global prevalence of anxiety and depression increased by roughly 25% in pediatric populations. While the general trend is clear, this research aimed to explore the added mental health burden of acute COVID-19 on pediatric patients with chronic conditions and describe the differences in mental health outcomes between pediatric patients with 2 common chronic conditions (asthma and diabetes) to better understand specific factors that may increase susceptibility to mental health concerns.

Using the TriNetX database, data were extracted for all pediatric patients (aged 5-17 years) with a positive SARS-CoV-2 infection (COVID-19) within a 1-year time frame (April 7, 2021, to April 6, 2022). These patients were divided into 4 cohorts based on the presence of chronic conditions before COVID-19 infection: diabetes (n = 1,587), asthma (n = 13,217), diabetes plus asthma (n = 626), and neither diabetes nor asthma (n = 104,427). For all cohorts, patients with other chronic illness and previous mental health diagnoses were excluded using relevant ICD-10 codes. After matching for demographics, comorbid conditions, and body mass index, odds ratios (ORs) of the following outcomes were compared between cohorts after 6 months: new psychiatric diagnosis using relevant ICD-10 codes, hospitalization within 1 week, and mortality.

After matching, there were statistically significant differences in outcomes between patients with chronic illness and healthy controls after 6 months. Compared with healthy controls, the asthma cohort OR of developing a new psychiatric diagnosis was 1.4 (95% CI 1.15-1.71, p < .001), and the diabetes cohort OR was 1.81 (95% CI 1.11-2.94, p = .015). The new psychiatric diagnosis OR of the asthma cohort compared with the diabetes cohort was 0.62 (95% CI 0.39-0.99, p = .045), suggesting that patients in the diabetes cohort were particularly susceptible to additional mental health diagnoses after an acute COVID-19 infection.

Compared with healthy controls, pediatric patients with asthma and pediatric patients with diabetes experienced increased odds of developing a new psychiatric diagnosis after an acute COVID-19 infection.

Data on the increase in mortality during the COVID-19 pandemic based on individuals' socioeconomic positions are limited. This study examines this increase in mortality in Spain during the epidemic waves of 2020 and 2021.

We calculated the overall and cause-specific mortality rates during the 2017-2019 pre-pandemic period and four epidemic periods in 2020 and 2021 (first, second, third-fourth, and fifth-sixth waves). Mortality rates were analyzed based on educational levels (low, medium, and high) and across various age groups (25-64, 65-74, and 75+). The increase in mortality during each epidemic period compared to the pre-pandemic period was estimated using mortality rate ratios (MRR) derived from Poisson regression models.

An inverse educational gradient in overall mortality was observed across all periods; however, this pattern was not consistent for COVID-19 mortality in some age groups. Among those aged 75 years and older, highly educated individuals showed higher COVID-19 mortality during the first wave. In the 25-64 age group, individuals with low education experienced the highest overall mortality increase, while those with high education had the lowest increase. The MRRs were 1.21 and 1.06 during the first wave and 1.12 and 0.97 during the last epidemic period. In the 65-74 age group, highly educated individuals showed the highest overall mortality increase during the first wave, whereas medium-educated individuals had the highest increase during the subsequent epidemic periods. Among those aged 75 and older, highly educated individuals exhibited the highest overall mortality increase while the individuals with low education showed the lowest overall mortality increment, except during the last epidemic period.

The varying educational patterns of COVID-19 mortality across different age groups contributed to the disparities of findings in increased overall mortality by education levels during the COVID-19 pandemic.

Diabetes Mellitus presents a formidable challenge as one of the most prevalent and complex chronic diseases, exerting significant strain on both patients and the world economy. It is recognized as a common comorbidity among severely ill individuals, often leading to a myriad of micro- and macro-vascular complications. Despite extensive research dissecting the pathophysiology and molecular mechanisms underlying vascular complications of diabetes, relatively little attention has been paid to potential lung-related complications. This review aims to illuminate the impact of diabetes on prevalent respiratory diseases, including chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), idiopathic pulmonary fibrosis (IPF), tuberculosis (TB), pneumonia infections, and asthma, and compare the vascular complications with other vascular beds. Additionally, we explore the primary mechanistic pathways contributing to these complications, such as the expression modulation of blood-tissue-barrier proteins, resulting in increased paracellular and transcellular permeability, and compromised immune responses rendering diabetes patients more susceptible to infections. The activation of inflammatory pathways leading to cellular injury and hastening the onset of these respiratory complications is also discussed.

To explore the impact of diabetes on the clinical features and prognosis of COVID-19 and assess the influence of glucocorticoid use on the prognosis of patients with COVID-19 and diabetes.

This retrospective multicenter cohort study included patients admitted between December 2022 and January 2023. The patients were grouped according to diabetes and glucocorticoid use. The primary outcome was in-hospital mortality.

Among 400 patients with glucocorticoid data, 109 (27.3%) had diabetes. The inflammatory cytokines were higher in patients with diabetes, manifested by higher IL-6 (25.33 vs. 11.29 ng/L, p = 0.011), CRP (26.55 vs. 8.62 mg/L, p = 0.003), and PCT (0.07 vs. 0.04 ng/ml, p = 0.010), while CD4+ (319 vs. 506 /mL, p = 0.004) and CD8+ (141 vs. 261 /mL, p < 0.001) T lymphocytes were lower. The overall mortality rate of hospitalized COVID-19 patients with diabetes was 13.46%. The diabetic patients who received glucocorticoids vs. those who did not receive glucocorticoids had a similar mortality (15.00% vs. 11.39%, p = 0.591).

Patients with COVID-19 and diabetes are more likely to experience hyperinflammatory response and T cell reduction, especially those with severe/critical disease. Glucocorticoid use was not associated with the prognosis of COVID-19 in patients with diabetes. Still, glucocorticoids should be used cautiously in diabetic patients with severe/critical COVID-19.

Dorzagliatin, an innovative dual-acting allosteric oral glucokinase activator that targets glucose homeostasis and insulin resistance, has gained approval for treating type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). The effectiveness of existing antidiabetic treatments in enhancing beta cell (β-cell) activity is restricted. Currently, there are no satisfactory medications available to address the fundamental deficiency in glucose sensing for glucokinase-maturity-onset diabetes of the young (GCK-MODY), which is caused by mutations in the glucokinase gene; researchers have embarked on glucokinase activators. Dorzagliatin enhances the affinity of glucokinase for glucose and glucose-sensing capacity, improves β-cell function, and reduces insulin resistance. Two phase 3 studies, an adjunct trial of dorzagliatin with metformin for T2DM patients and a monotherapy trial for drug-naïve T2DM patients, are key clinical trials that have shown a favorable safety and tolerability profile. They also demonstrated a rapid, sustained reduction in glycated hemoglobin (HbA1c) and a significant decrease in postprandial blood glucose. This review will summarize the substantial clinical evidence supporting the safety and efficacy of dorzagliatin in treating diabetes mellitus (DM) and clarify the molecular mechanisms underlying its action.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has had a profound global impact, with millions of confirmed cases and deaths worldwide. While most cases are mild, a subset progresses to severe respiratory complications and death, with factors such as thromboembolism, age, and underlying health conditions increasing the risk. Vascular endothelial damage has been implicated in severe outcomes, but specific biomarkers remain elusive. This study investigated syndecan-1 (SDC-1), a marker of endothelial damage, as a potential prognostic factor for COVID-19, focusing on the Japanese population, which is known for its aging demographics and high prevalence of comorbidities.

A multicenter retrospective study of COVID-19 patients in Fukushima Prefecture in Japan who were admitted between February 2020 and August 2021 was conducted. SDC-1 levels were measured along with other clinical and laboratory parameters. Outcomes including thrombosis, 28-day survival, and disease severity were assessed, and disease severity was categorized according to established guidelines.

SDC-1 levels were correlated with disease severity. Patients who died from COVID-19 had greater SDC-1 levels than survivors, and the area under the receiver operating characteristic curve (AUC) analysis suggested the potential of the SDC-1 level as a predictor of mortality (AUC 0.714). K‒M analysis also revealed a significant difference in survival based on an SDC-1 cutoff of 10.65 ng/mL.

This study suggested that SDC-1 may serve as a valuable biomarker for assessing COVID-19 severity and predicting mortality within 28 days of hospitalization, particularly in the Japanese population. However, further investigations are required to assess longitudinal changes in SDC-1 levels, validate its predictive value for long-term survival, and consider its applicability to new viral variants.

SDC-1 is emerging as a potential biomarker for assessing the severity and life expectancy of COVID-19 in the Japanese population, offering promise for improved risk stratification and patient management in the ongoing fight against the virus.

The aim of this study was to provide a scoping and comprehensive review for the clinical outcomes from the cross-link of Type 2 diabetes mellitus (T2DM), COVID-19, and sarcopenia.

By using PRISMA guidelines and searching through different databases that could provide findings of evidence on the association of T2DM, COVID-19, and sarcopenia.

Thirty-three studies reported a relationship between sarcopenia with T2DM, twenty-one studies reported the prognosis COVID-19 in patients with T2DM, ten studies reported the prognosis of COVID-19 in patients with sarcopenia, five studies discussed the outcomes of sarcopenia in patients with COVID-19, and one study reported sarcopenia outcomes in the presence of T2DM and COVID-19.

There is an obvious multidimensional relationship between T2DM, COVID-19 and sarcopenia which can cause prejudicial effects, poor prognosis, prolonged hospitalisation, lowered quality of life and a higher mortality rate during the current COVID-19 pandemic.

Diabetes and stress hyperglycemia have been related with poorer clinical outcomes in patients infected by SARS-CoV-2 and at risk for severe disease.

To evaluate clinical outcomes in three groups of patients (with diabetes, without diabetes and with stress hyperglycemia) with SARS-CoV-2 infection.

A retrospective cohort study was conducted in Cali (Colombia). We included patients 18 years old or older with a diagnosis of SARS-CoV-2 infection, managed in the emergency room, hospitalization, or intensive care unit between March 2020 and December 2021. Immunocompromised patients and pregnant women were excluded. Patients were classified into three groups: without diabetes, with diabetes, and with stress hyperglycemia. A comparison between the groups was performed.

A total of 945 patients were included (59.6% without diabetes, 27% with diabetes, and 13.4% with stress hyperglycemia). Fifty-five-point three percent required intensive care unit management, with a higher need in patients with stress hyperglycemia (89.8%) and diabetes (67.1%), with no difference between these groups (p = 0.249). We identified a higher probability of death in the group with stress hyperglycemia versus the one without diabetes (adjusted OR = 8.12; 95% CI: 5.12-12.88; p < 0.01). Frequency of acute respiratory distress syndrome, need for invasive mechanical ventilation, use of vasopressors and inotropes, need for de novo renal replacement therapy, and mortality was higher in patients with metabolic alterations (diabetes and stress hyperglycemia).

Diabetes and stress hyperglycemia were associated with worse clinical outcomes and mortality in patients with COVID-19. These patients should be identified early and considered them high risk at the COVID-19 diagnosis to mitigate adverse outcomes.

Although we are four years into the pandemic, there is still conflicting evidence regarding the clinical outcomes of diabetic patients hospitalized with COVID-19. The primary objective of this study was to evaluate the in-hospital mortality and morbidity of diabetic versus nondiabetic patients hospitalized with COVID-19 in the Northern UAE Emirates.

A retrospective analysis was performed on clinical data from patients with or without diabetes mellitus (DM) who were admitted to the isolation hospital with COVID-19 during the first and second waves of the disease (March 2020 to April 2021). The assessed endpoints were all-cause in-hospital mortality, length of hospitalization, intensive care unit (ICU) admission, and mechanical ventilation.

A total of 427 patients were included in the analysis, of whom 335 (78.5%) had DM. Compared to nondiabetics, diabetic COVID-19 patients had a significantly longer in-hospital stay (odds ratio (OR) = 2.35; 95% confidence interval (CI) = 1.19-4.62; p = 0.014), and a significantly higher frequency of ICU admission (OR = 4.50; 95% CI = 1.66-7.34; p = 0.002). The need for mechanical ventilation was not significantly different between the two groups (OR: distorted estimates; p = 0.996). Importantly, the overall in-hospital mortality was significantly higher among diabetic patients compared to their nondiabetic counterparts (OR = 2.26; 95% CI = 1.08-4.73; p = 0.03).

DM was associated with a more arduous course of COVID-19, including a higher mortality rate, a longer overall hospital stay, and a higher frequency of ICU admission. Our results highlight the importance of DM control in COVID-19 patients to minimize the risk of detrimental clinical outcomes.