Coronavirus Disease 2019 Mortality Research Articles

Eosinopenia as a prognostic factor of mortality for COVID-19 in end-stage kidney disease patients.

The unique role of eosinophil in coronavirus disease 2019 (COVID-19) patients has been shown in several studies, but its role in end-stage kidney disease (ESKD) patients who contracted COVID-19 is less reported. This study investigated eosinopenia's predictive value as a mortality marker in ESKD patients with COVID-19. It is a retrospective study of ESKD patients who contracted COVID-19 between May 2020 and October 2021 in West Nusa Tenggara General Hospital, Indonesia. Comparative analysis was carried out between the death dan survival group. Logistic regression analysis was done to investigate the role of eosinopenia on the outcome after controlling other significant variables. The analyses included one hundred fifteen confirmed COVID-19 in ESKD patients. The average age was 50, 53% of patients were males, 41% were newly diagnosed with ESKD, and the mortality rate was 25.2%. This study's prevalence of eosinopenia, high neutrophil-to-lymphocyte ratio (NLR), and high C-reactive protein (CRP) in the nonsurvivors was 51.4%, 39.3%, and 30.8%, respectively. Diastolic blood pressure <90 mmHg (P=0.004), respiratory rate >22 x/minutes (P=0.011), oxygen saturation <93% (P=0.008), NLR >6 (p<0.001), eosinophil count <0.01 x103/uL (p<0.001), CRP >20 mg/L (P=0.047), and isolation hemodialysis (HD) therapy (p<0.001) were independently associated with mortality of COVID-19 in ESKD patients. However, on multivariate logistic regression analysis, eosinopenia (P=0.019) and HD (P=0.001) were risk factors that remained significant prognostic mortality factors. Eosinopenia was common in ESKD patients with COVID-19, particularly in the death group. Eosinopenia at admission and HD during hospitalization were risk factors for COVID-19 mortality in ESKD patients.

Chronic Anticoagulation in Patients with Atrial Fibrillation and COVID-19: A Systematic Review and Meta-Analysis.

Coronavirus disease 2019 (COVID-19) is associated with hypercoagulability. It remains uncertain whether ongoing anticoagulation for atrial fibrillation (AF) in patients who later contract COVID-19 improves clinical outcomes. To compare chronic oral anticoagulation with no previous anticoagulation in patients with AF who contracted a COVID-19 infection concerning the outcomes of all-cause mortality, COVID-19 mortality, intensive care unit (ICU) admission, and hospitalization. We systematically searched PubMed, Embase, and Cochrane Library for eligible studies from inception to December 2022. We included studies comparing COVID-19 outcomes in patients with versus without prior chronic anticoagulation for AF. Risk ratios (RR) with 95% confidence intervals (CI) were pooled with a random-effects model. The level of significance was set at p < 0.05. Quality assessment and risk of bias were performed according to Cochrane recommendations. Ten studies comprising 1,177,858 patients with COVID-19 and AF were identified, of whom 893,772 (75.9%) were on prior chronic anticoagulation for AF. In patients with COVID-19, being on chronic anticoagulation for AF significantly reduced all-cause mortality (RR 0.75; 95% CI 0.57 to 0.99; p = 0.048; I2 = 89%) and COVID-19-related mortality (RR 0.76; 95% CI 0.72 to 0.79; p < 0.001; I2 = 0%) when compared with no prior anticoagulation. In contrast, there was no difference between groups regarding hospitalization (RR 1.08; 95% CI 0.82 to 1.41; p = 0.587; I2 = 95%) or ICU admission (RR 0.86; 95% CI 0.68 to 1.09; p = 0.216; I2 = 69%). In this meta-analysis, chronic anticoagulation for patients with AF who contracted COVID-19 was associated with significantly lower rates of all-cause mortality and COVID-19-related mortality as compared with no previous anticoagulation.

Anticoagulação Crônica em Pacientes com Fibrilação Atrial e COVID-19: Uma Revisão Sistemática e Metanálise

Abstract Background: Coronavirus disease 2019 (COVID-19) is associated with hypercoagulability. It remains uncertain whether ongoing anticoagulation for atrial fibrillation (AF) in patients who later contract COVID-19 improves clinical outcomes. Objectives: To compare chronic oral anticoagulation with no previous anticoagulation in patients with AF who contracted a COVID-19 infection concerning the outcomes of all-cause mortality, COVID-19 mortality, intensive care unit (ICU) admission, and hospitalization. Methods: We systematically searched PubMed, Embase, and Cochrane Library for eligible studies from inception to December 2022. We included studies comparing COVID-19 outcomes in patients with versus without prior chronic anticoagulation for AF. Risk ratios (RR) with 95% confidence intervals (CI) were pooled with a random-effects model. The level of significance was set at p &lt; 0.05. Quality assessment and risk of bias were performed according to Cochrane recommendations. Results: Ten studies comprising 1,177,858 patients with COVID-19 and AF were identified, of whom 893,772 (75.9%) were on prior chronic anticoagulation for AF. In patients with COVID-19, being on chronic anticoagulation for AF significantly reduced all-cause mortality (RR 0.75; 95% CI 0.57 to 0.99; p = 0.048; I2 = 89%) and COVID-19-related mortality (RR 0.76; 95% CI 0.72 to 0.79; p &lt; 0.001; I2 = 0%) when compared with no prior anticoagulation. In contrast, there was no difference between groups regarding hospitalization (RR 1.08; 95% CI 0.82 to 1.41; p = 0.587; I2 = 95%) or ICU admission (RR 0.86; 95% CI 0.68 to 1.09; p = 0.216; I2 = 69%). Conclusions: In this meta-analysis, chronic anticoagulation for patients with AF who contracted COVID-19 was associated with significantly lower rates of all-cause mortality and COVID-19-related mortality as compared with no previous anticoagulation.

A Prediction Model for Clinical Outcomes of COVID-19 Hospitalized Patients: Construction and Accuracy Assessment.

The coronavirus disease 2019 (COVID-19) pandemic spread rapidly with considerable morbidity nationwide since China's liberalization in December 2022. Our work has focused on identifying different predictive factors from the laboratory examination of critically ill patients, and forecasting the unfavorable outcome of critically ill patients with COVID-19 through a combined diagnosis of biological markers. We conducted a retrospective study at the Department of First Affiliated Hospital of Wenzhou Medical University, China, from December 24, 2022, to January 10, 2023, where 434 critically ill patients who met the inclusion criteria were involved. Machine analysis was employed to search for the parameters with the highest predictive value to calculate COVID-19 mortality by exploiting 66 typical laboratory results. Combined diagnosis of serum albumin (ALB), lactate dehydrogenase (LDH), direct bilirubin (Dbil), ferritin, pulse oxygen saturation (SpO2), and neutrophil count (NEUT#) was evaluated, and the result with the highest predictive value (NEUT#) was selected as the predictor for COVID-19 mortality with a sensitivity of 89.2% and a specificity of 77.4%. The increased levels of LDH, Dbil, ferritin, and NEUT#, along with lowered ALB and SpO2 levels are the most decisive variables for forecasting the mortality for COVID-19 according to our machine-learning-based model. The combined diagnosis could be used to improve further diagnostic performance.

COVID-19 Mortality and Severity in Cancer Patients and Cancer Survivors.

We aimed to investigate mortality, severity, and risk of hospitalization in coronavirus disease 2019 (COVID-19) patients with cancer. Data of all patients aged 40-79 years from the Korean Disease Control and Prevention Agency-COVID19-National Health Insurance Service who were diagnosed with COVID-19 between January 1, 2020 and March 31, 2022, in Korea were included. After 1:1 propensity score matching, 397,050 patients with cancer and 397,050 patients without cancer were enrolled in the main analysis. A cancer survivor was defined as a patient who had survived 5 or more years since the diagnosis of cancer. Multiple logistic regression analysis was performed to compare the risk of COVID-19 according to the diagnosis of cancer and time since diagnosis. Cancer, old age, male sex, incomplete vaccination against COVID-19, lower economic status, and a higher Charlson comorbidity index were associated with an increased risk of hospitalization, hospitalization with severe state, and death. Compared to patients without cancer, the adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for hospitalization, hospitalization with severe state, and death in patients with cancer were 1.09 (1.08-1.11), 1.17 (1.11-1.24), and 1.94 (1.84-2.05), respectively. Compared to patients without cancer, the ORs (95% CIs) for hospitalization in cancer survivors, patients with cancer diagnosed 2-5 years, 1-2 years, and < 1 year ago were 0.96 (0.94-0.98), 1.10 (1.07-1.13), 1.30 (1.25-1.34), and 1.82 (1.77-1.87), respectively; the ORs (95% CIs) for hospitalization for severe disease among these patients were 0.90 (0.85-0.97), 1.22 (1.12-1.32), 1.60 (1.43-1.79), and 2.29 (2.09-2.50), respectively. The risks of death, severe state, and hospitalization due to COVID-19 were higher in patients with cancer than in those without; the more recent the diagnosis, the higher the aforementioned risks. Cancer survivors had a lower risk of hospitalization and hospitalization with severe disease than those without cancer.

Association between Peripheral Arterial Thrombosis and COVID-19 using CT Angiography: A Retrospective Observational Study

Introduction: Arterial thromboembolism is a major cause of morbidity and mortality in Coronavirus Disease 2019 (COVID-19) patients in both General Inpatient ward and Intensive Care Unit (ICU) settings. As COVID-19 is associated with coagulopathy or vasculopathy, it is necessary to investigate whether the peripheral vessels were also affected due to COVID-19-related thrombosis. Computed Tomography Angiography (CTA) is a quick, accurate, non invasive, and reliable method for assessing the location, extent and severity of arterial thrombosis. Aim: To evaluate the association of acute peripheral arterial thrombosis in patients with COVID-19 infection and assess the differences in peripheral extremity clot burden using peripheral limb CTA. Materials and Methods: A retrospective observational study was conducted in the Department of Radiology, Topiwala National Medical College and B.Y.L. Nair Charitable. Hospital, Mumbai, Maharashtra, India, from April 2020 to April 2021. A total of 70 patients with medical records of acute limb ischaemia, consisting of 35 Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection-positive patients and 35 SARS-CoV-2 negative patients, who underwent peripheral CTA were included in the present study. For calculating arterial clot severity and extent in the peripheral extremities, three different systems were used. Age, sex, symptoms, co-morbidities, and CT thrombus burden score were analysed in both groups. The association between variables was analysed using the Chi- square test. Results: The age range of patients presenting with acute limb ischaemia was 24-74 years (mean age=50 years). Claudication, pain and redness had a significant association with COVID- 19 positive patients (p-value&lt;0.001). It was also observed that proximal vessels had a slightly higher preponderance for thrombosis. A significant mean difference in arterial thrombus burden was observed in SARS-CoV-2 infection positive patients, with greater thrombus burden involving proximal vessels. In only the proximal vessels, the overall clot burden was 2.31±3.09 and 0.89±1.25 in the COVID-19 positive and negative groups, respectively (p-value=0.014). COVID-19 infected patients had a predilection for peripheral arterial thrombosis compared to controls, with a significant p-value of 0.034 in proximal upper limb involvement. Conclusion: Computed tomography angiography is the preferred diagnostic modality for the evaluation of arterial thrombosis. Greater clot burden was seen in the proximal vessels of both upper and lower limbs in COVID-19 patients.

The Impact of Serum Albumin on the Mortality Prediction in COVID Patients at a Private Hospital in Madurai

Abstract Background: The objective of the study was to identify the serum albumin levels and their correlation with the length of hospital stay and mortality in coronavirus disease 2019 (COVID-19) patients. To achieve this, we studied the correlation between serum albumin levels to the length of hospital stay and mortality outcomes. Materials and Methods: It is a retrospective observational study in which information about COVID-19 patients admitted to a private hospital in Madurai was collected between March 2021 and August 2021. The time from admission to discharge of patients and mortality outcomes was taken into account. Results: A total of 176 COVID-19 patients were included, of which 150 patients (85%) recovered and 26 patients (15%) died during the hospital admission. The median length of hospital stays of COVID-19 patients who were hospitalized and discharged alive was found to be 8.5 ± 4.6 days by the Kaplan–Meier curve. The mean albumin levels in alive patients were found to be 3.5 ± 0.37 g/dl compared to expired COVID-19 patients with low albumin levels of 3.3 ± 043 g/dl. Hence, we conclude that serum albumin levels had an impact on the outcome and hospital stay. Conclusion: Serum albumin levels at admission might reflect the severity of infection and thus can serve as a predictive factor for COVID-19 outcomes.

Associations Between COVID-19, Delirium, and 1-Year Mortality: Exploring Influences on Delirium Incidence in COVID-19 Patients.

This study investigated the relationship between coronavirus disease 2019 (COVID-19), delirium, and 1-year mortality. Factors associated with delirium in COVID-19 patients were identified, along with the influence of psychotropic medications on delirium. The study used the South Korean National Health Insurance Service database. Adult COVID-19 patients diagnosed between October 2020 and December 2021 were included, with a propensity score-matched control group. Time-dependent Cox regression assessed associations among COVID-19, delirium, and mortality. Logistic regression analyzed the impact of psychotropic medications on delirium incidence. The study included 832,602 individuals, with 416,301 COVID-19 patients. COVID-19 (hazard ratio [HR], 3.03; 95% confidence interval [CI], 2.92-3.13) and delirium (HR, 2.33; 95% CI, 2.06-2.63) were independent risk factors for 1-year mortality. Comorbidities, insurance type, and residence were also related to mortality. Among COVID-19 patients, antipsychotic use was associated with lower delirium incidence (odds ratio [OR], 0.38; 95% CI, 0.30-0.47), while mood stabilizers (OR, 1.77; 95% CI, 1.40-2.21) and benzodiazepines (OR, 8.62; 95% CI, 7.46-9.97) were linked to higher delirium incidence. COVID-19 and delirium are risk factors for 1-year mortality. Some factors associated with delirium in COVID-19 patients are modifiable and can be targeted in preventive and therapeutic interventions.

Can periodontitis affect the COVID-19 severity, symptoms, hospital stay, and mortality? A case-control study.

Poor oral hygiene and periodontal disease have been identified as potential risk factors for the coronavirus disease 2019 (COVID-19). The present study aimed to determine the association between periodontitis and COVID-19 severity, nature of symptoms, mortality, and hospital stay. In total, 163 COVID-19-positive patients (men: 93; women: 70) were categorized into two groups: the control group, consisting of 120 patients with asymptomatic or mild symptoms, and the case group, consisting of 43 patients with moderate-to-severe symptoms. The severity of periodontal disease, oral hygiene status (OHI), pocket depth (PD), bleeding on probing (BOP), number of decayed/missing/filled teeth, mortality, duration of stay in the hospital, oxygen requirement, and nature of COVID-19 symptoms were assessed in both groups. The association between periodontitis and COVID-19 was analyzed with other confounding factors such as age, sex, comorbidities, oral hygiene, and smoking status. The presence of periodontitis increases the severity of COVID-19 by 3.7 times (p = 0.002). A statistically significant difference was noted for symptoms such as dizziness (p = 0.036), running nose/cold (p = 0.009), and headache (p = 0.005) in the presence of periodontitis. The risk estimate for death associated with periodontitis was 1.03. Additionally, the average duration of stay was longer for individuals with periodontitis than for those in the control group. There is a positive association between periodontal disease and COVID-19. Periodontitis increases the severity of COVID-19 and alters the symptoms. Hence, periodontal disease management should be an integral part of managing patients with coronavirus infection.

Tuberculosis Coinfection among COVID-19 Patients: Clinical Presentation and Mortality in a Tertiary Lung Hospital in Indonesia.

Tuberculosis (TB) and coronavirus disease 2019 (COVID-19) are the top two killers of infectious disease. We aimed to determine the association of TB coinfection with the inhospital mortality of COVID-19 patients in Indonesia as a TB-endemic country. We conducted a retrospective cohort study in a tertiary lung hospital in Indonesia. All TB-coinfected COVID-19 patients who were hospitalized between January 2020 and December 2021 were included in the study. COVID-19 patients without TB were randomly selected for the control group. Clinical characteristics and laboratory results were assessed. Survival analysis was performed to determine the estimated death rate and median survival time (MST). Multivariate Cox regression analysis was conducted to define the association of TB coinfection with the in-hospital mortality of COVID-19. We included 86 (8.3%) TB coinfections among 1034 confirmed COVID-19 patients. TB coinfection patients had younger age, malnutrition, and different symptoms compared to the COVID-19 group. TB-coinfected patients had a lower estimated death rate than the COVID-19 group (6.5 vs. 18.8 per 1000 population). MST in the COVID-19 group was 38 (interquartile range 16-47) days, whereas the same observation time failed to determine the MST in the TB coinfection group. TB coinfection had a crude hazard ratio of mortality 0.37 (95% confidence interval [CI] 0.15-0.94, P = 0. 004). The final model analysis including age, sex, and lymphocyte as confounding factors resulted in an adjusted HR of mortality 0.31 (95% CI 0.1-0.9). This study showed TB coinfection was negatively associated with the in-hospital mortality of COVID-19.

Estimating Excess Mortality During the COVID-19 Pandemic Between 2020-2022 in Korea.

The persistent coronavirus disease 2019 (COVID-19) pandemic has had direct and indirect effects on mortality, making it essential to analyze excess mortality to fully understand the impact of the pandemic. In this study, we constructed a mathematical model using number of deaths from Statistics Korea and analyzed excess mortality between 2020 and 2022 according to age, sex, and dominant severe acute respiratory syndrome coronavirus 2 variant period. Number of all-cause deaths between 2010 and 2022 were obtained from the annual cause-of-death statistics provided by Statistics Korea. COVID-19 mortality data were acquired from the Korea Disease Control and Prevention Agency. A multivariate linear regression model with seasonal effect, stratified by sex and age, was used to estimate the number of deaths in the absence of COVID-19. The estimated excess mortality rate was calculated. Excess mortality was not significant between January 2020 and October 2021. However, it started to increase monthly from November 2021 and reached its highest point during the omicron-dominant period. Specifically, in March and April 2022, during the omicron BA.1/BA.2-dominant period, the estimated median values for excess mortality were the highest at 17,634 and 11,379, respectively. Both COVID-19-related deaths and excess mortality increased with age. A notable increase in excess mortality was observed in individuals aged ≥ 65 years. In the context of excess mortality per 100,000 population based on the estimated median values in March 2022, the highest numbers were found among males and females aged ≥ 85 years at 1,048 and 910, respectively. This study revealed that the prolonged COVID-19 pandemic coupled with its high transmissibility not only increased COVID-19-related deaths but also had a significant impact on overall mortality rates, especially in the elderly. Therefore, it is crucial to concentrate healthcare resources and services on the elderly and ensure continued access to healthcare services during pandemics. Establishing an excess mortality monitoring system in the early stages of a pandemic is necessary to understand the impact of infectious diseases on mortality and effectively evaluate pandemic response policies.

Clinical and prognostic implications of hyaluronic acid in patients with COVID-19 reinfection and first infection.

Previous research has shown that human identical sequences of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) promote coronavirus disease 2019 (COVID-19) progression by upregulating hyaluronic acid (HA). However, the association of HA with mortality and long COVID in SARS-CoV-2 reinfection and first infection is unclear. Patients with COVID-19 at Beijing Ditan Hospital from September 2023 to November 2023 were consecutively enrolled. SARS-CoV-2 reinfections were matched 1:2 with first infections using a nearest neighbor propensity score matching algorithm. We compared the hospital outcomes between patients with COVID-19 reinfection and first infection. The association between HA levels and mortality and long COVID in the matched cohort was analyzed. The reinfection rate among COVID-19 hospitalized patients was 25.4% (62 cases). After propensity score matching, we found that reinfection was associated with a better clinical course and prognosis, including lower levels of C-reactive protein and erythrocyte sedimentation rate, fewer cases of bilateral lung infiltration and respiratory failure, and shorter viral clearance time and duration of symptoms (p < 0.05). HA levels were significantly higher in patients with primary infection [128.0 (90.5, 185.0) vs. 94.5 (62.0, 167.3), p = 0.008], those with prolonged viral clearance time [90.5 (61.5, 130.8) vs. 130.0 (95.0, 188.0), p < 0.001], and deceased patients [105.5 (76.8, 164.5) vs. 188.0 (118.0, 208.0), p = 0.002]. Further analysis showed that HA was an independent predictor of death (AUC: 0.789), and the risk of death increased by 4.435 times (OR = 5.435, 95% CI = 1.205-24.510, p = 0.028) in patients with high HA levels. We found that patients with HA levels above 116 ng/mL had an increased risk of death. However, the incidence of long COVID was similar in the different HA level groups (p > 0.05). Serum HA may serve as a novel biomarker for predicting COVID-19 mortality in patients with SARS-CoV-2 reinfection and first infection. However, HA levels may not be associated with long COVID.

Association of Polymorphisms of the IL-17A and IL-17F Genes with Increased Risk of Hypertension and Obesity in Mexican Patients with COVID-19.

Coronavirus disease 2019 (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV2). COVID-19 can cause a cytokine release syndrome in which cytokines, including interleukin 17 (IL-17), are massively secreted in response to a specific stimulus. This can contribute to mortality and severe forms of COVID-19. The study aimed to determine the association of SARS-CoV2 infection with the IL-17A rs2275913 and IL-17F rs763780 variants, as well as with the associated comorbidities in COVID-19-positive Mexican patients. The study included 178 patients positive to COVID-19 and 177 COVID-19 negative subjects. For genotyping, the samples were amplified with a TaqMan® probe. There was no association between the AA genotype and A allele of IL-17A variant or the IL-17F C allele with the presence of COVID-19. In regard to comorbidities, a statistically significant association was found between IL-17A rs2275913 AA genotype and hypertension, as well as with the presence of obesity (P = 0.003, OR 23, 95% CI: 2.97-178.092 and P = 0.025, OR 28, 95% CI: 1.52-178.029, respectively) in patients with COVID-19. In conclusion, rs2275913 IL-17A polymorphism in COVID-19 patients seems to confer a higher susceptibility to the presence of hypertension and obesity, increasing the risk of premature cardiovascular disease in this population. However, more studies should be conducted for a better understanding of their relation.

Effectiveness of Machine Learning for COVID-19 Patient Mortality Prediction Using WEKA

Timely detection of patients with a high mortality risk in coronavirus disease 2019 (COVID-19) can substantially improve triage, bed allocation, time reduction, and potential outcomes. A potential solution is using machine learning (ML) algorithms to predict mortality in COVID-19 hospitalized patients. The study's objective was to create and verify individual risk assessments for mortality using anonymous demographic, clinical, and laboratory findings at admission, as well as to assess the possibility of death using machine learning. We used a standardized format and electronic medical records. Data from 2,313 patients were collected from two Muhammadiyah hospitals from January 2020 to July 2022. Utilizing each patient's clinical manifestation state at admission and laboratory parameters, 24 demographic, clinical, and laboratory results were studied. The algorithms analyzed were AdaBoost, logistic regression, random forest, support vector machine, naïve Bayes, and decision tree, which were applied through WEKA version 3.8.6. Random forest performed better than the other machine learning techniques, with precision, sensitivity, receiver operating characteristic (ROC), and accuracy of 78.6%, 78.7%, 85%, and 78.65%, respectively. The three top predictors were septic shock (OR=21.518, 95% CI=4.933–93.853), respiratory failure (OR=15.503, 95% CI=8.507–28.254), and D-dimer (OR=3.288, 95% CI=2.510–4.306). Machine learning–based predictive models, especially the random forest algorithm, may make it easier to identify patients at high risk of death and guide physicians' appropriate interventions.

Association of genetic polymorphisms with COVID-19 infection and outcomes: An updated meta-analysis based on 62 studies

BackgroundThe relationship between genetic polymorphisms and coronavirus disease 2019 (COVID-19) remains to be inconsistent. This meta-analysis aimed to provide an updated evaluation of the role of genetic polymorphisms in the infection, severity and mortality of COVID-19 based on all available published studies. MethodsA systematic search was performed using six databases: PubMed, Embase, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure (CNKI) and Wanfang. Summary odds ratios (ORs) and corresponding 95 % confidence intervals (CIs) were used to calculate the genotypic comparison. All statistical analyses were conducted in Stata 12.0. ResultsA total of 62 studies with 19600 cases and 28899 controls was included in this meta-analysis. For COVID-19 infection, ACE Ins/Del polymorphism might be related with significantly decreased risk of COVID-19 infection under dominant, homozygote and allelic models. Meanwhile, the IFITM3 rs12252 and TMPRSS2 rs12329760 polymorphisms were significantly associated with the increased risk of COVID-19 infection under one or more models. Regarding COVID-19 severity, ACE2 rs2074192, ACE2 rs2106809, IFITM3 rs12252 and VDR rs1544410 polymorphisms might be related with significantly increased risk of COVID-19 severity in one or more models. Moreover, the analysis of TMPRSS2 rs2070788 indicated that a variant A allele decreased the risk of COVID-19 severity in recessive model. For COVID-19 mortality, the variant C allele of IFITM3 rs12252 polymorphism might be related with significantly increased risk of COVID-19 mortality under all genetic models. ConclusionsThis meta-analysis indicated that he infection, severity or mortality of COVID-19 were related to the above genetic polymorphisms, which might provide an important theoretical basis for understanding the clinical feature of COVID-19 disease.

Genetic diversity and evolutionary patterns of SARS-CoV-2 among the Bhutanese population during the pandemic.

The coronavirus disease 2019 (COVID-19) pandemic, caused by a dynamic virus, has had a profound global impact. Despite declining global COVID-19 cases and mortality rates, the emergence of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants remains a major concern. This study provides a comprehensive analysis of the genomic sequences of SARS-CoV-2 within the Bhutanese population during the pandemic. The primary aim was to elucidate the molecular epidemiology and evolutionary patterns of SARS-CoV-2 in Bhutan, with a particular focus on genetic variations and lineage dynamics. Whole-genome sequences of SARS-CoV-2 collected from Bhutan between May 2020 and February 2023 (n=135) were retrieved from the Global Initiative on Sharing All Influenza Database. The SARS-CoV-2 variants in Bhutan were predominantly classified within the Nextstrain clade 20A (31.1%), followed by clade 21L (20%) and clade 22D (15.6%). We identified 26 Pangolin lineages with variations in their spatial and temporal distribution. Bayesian time-scaled phylogenetic analysis estimated the time to the most recent common ancestor as February 15, 2020, with a substitution rate of 0.97×10-3 substitutions per site per year. Notably, the spike glycoprotein displayed the highest mutation frequency among major viral proteins, with 116 distinct mutations, including D614G. The Bhutanese isolates also featured mutations such as E484K, K417N, and S477N in the spike protein, which have implications for altered viral properties. This is the first study to describe the genetic diversity of SARS-CoV-2 circulating in Bhutan during the pandemic, and this data can inform public health policies and strategies for preventing future outbreaks in Bhutan.

Expert consensus on the management of interstitial lung disease during the COVID-19 epidemic

Expert consensus on the management of interstitial lung disease during the COVID-19 epidemic

Healthcare Systems and COVID-19 Mortality in Selected OECD Countries: A Panel Quantile Regression Analysis.

The pandemic caused by coronavirus disease 2019 (COVID-19) has exerted an unprecedented impact on the health of populations worldwide. However, the adverse health consequences of the pandemic in terms of infection and mortality rates have varied across countries. In this study, we investigate whether COVID-19 mortality rates across a group of developed nations are associated with characteristics of their healthcare systems, beyond the differential policy responses in those countries. To achieve the study objective, we distinguished healthcare systems based on the extent of healthcare decommodification. Using available daily data from 2020, 2021, and 2022, we applied quantile regression with non-additive fixed effects to estimate mortality rates across quantiles. Our analysis began prior to vaccine development (in 2020) and continued after the vaccines were introduced (throughout 2021 and part of 2022). The findings indicate that higher testing rates, coupled with more stringent containment and public health measures, had a significant negative impact on the death rate in both pre-vaccination and post-vaccination models. The data from the post-vaccination model demonstrate that higher vaccination rates were associated with significant decreases in fatalities. Additionally, our research indicates that countries with healthcare systems characterized by high and medium levels of decommodification experienced lower mortality rates than those with healthcare systems involving low decommodification. The results of this study indicate that stronger public health infrastructure and more inclusive social protections have mitigated the severity of the pandemic's adverse health impacts, more so than emergency containment measures and social restrictions.

The effect of Chronic treatments of Type 2-diabetes mellitus on COVID-19 Morbidity and Symptoms Severity

Coronavirus disease 2019 (COVID-19) is a highly contagious viral disease that causes the severe acute respiratory syndrome (SARS), and has had a disastrous impact on demographics around the world. Studies have classified type 2-diabetes mellitus (T2DM) as a risk factor for increasing mortality and se-verity of disease symptoms. However, the effect of different T2DM-chronic medications on disease progression is still unclear. The aim of this study was to determine the effect of glycemic control on COVID-19-related mortality and symptom severity, as well as the impact of commonly used T2DM therapeutic approaches on disease outcomes. This study included 109 COVID-19 patients with (68 patients) or without (41 patients) type 2-diabetes mellitus. Diabetic patients were further classified according to: 1) their glycemic control [HbA1c levels ˂6.5% (Well-controlled) and ≥ 6.5% (Less-controlled)], or 2) their pre-hospital anti-hyperglycemic med-ication [metformin (50%) or sulfonylureas (50%)]. Our results showed that diabetes is associated with a significantly higher risk of death in COVID-19 pa-tients. We also found that metformin treatment reduces plasma C-reactive protein levels and mortality Compared with sulfonylureas, and continuing with metformin during the hospital stay had a better prog-nostic for survival. We also, demonstrated that taking sulfonylurea is associated with an increase in COVID-19 mortality as compared to metformin by increasing cardiovascular events.

Relationship Between Human FCγRIIA rs1801274 G Allele and Risk of Death Among Different SARS-CoV-2 Variants.

Coronavirus disease 2019 (COVID-19), the illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in late 2019 and spread very quickly across the world. Different responses to infections have been related to fragment crystallizable gamma-receptor II alpha (FcγRIIA) polymorphisms. The purpose of this investigation was to determine if FCγRIIA rs1801274 polymorphism was related to COVID-19 mortality among different variants of SARS-CoV-2. The FCγRIIA rs1801274 polymorphism was genotyped using the polymerase chain reaction-restriction fragment length polymorphism technique in 1,734 recovered and 1,450 deceased patients. Deceased patients had significantly higher minor allele frequency of the FCγRIIA rs1801274 G allele than in the recovered cases. The COVID-19 mortality was associated with FCγRIIA rs1801274 GG and AG genotypes in the Delta variant and with FCγRIIA rs1801274 GG genotypes in the Alpha and Omicron BA.5 variants. The reverse transcription-quantitative polymerase chain reaction Ct values revealed statistically significant differences between individuals with a G allele and those with an A allele. In conclusion, among the several SARS-CoV-2 variants, there may be a correlation between the mortality rate of COVID-19 and the G allele of FCγRIIA rs1801274. To confirm our findings, thorough research is still required.