Coronavirus Disease 2019 Mortality Research Articles

Disparities in infectious disease-related health care utilization between Medicaid-enrolled American Indians and non-Hispanic Whites-Lessons from the first 16 months of coronavirus disease 2019 and a decade of flu seasons.

To understand why American Indian and Alaskan Native (AIAN) populations have had exceptionally high COVID-19 mortality, we compare patterns of healthcare utilization and outcomes for two serious infectious respiratory diseases-Influenza-like-illness (ILI) and coronavirus disease 2019 (COVID-19)-between American Indian and Alaskan Native (AIAN) populations (as identified in Medicaid data) and non-Hispanic Whites over the 2009-2021 period. We select all people under the age of 65 years identified as non-Hispanic White or AIAN in the New York State Medicaid claims data between 2009 and 2021. We analyze data across 10 ILI cohorts (between September 2009 and August 2020) and 4 COVID-19 cohorts (March-June 2020, July-September 2020, October-December 2020, and January-June 2021). We examine mortality and utilization rates using logistic regressions, adjusting for demographic characteristics, prior chronic conditions, and geographic location (including residence near a reservation). We stratify the analysis by rural vs. nonrural counties. We use the New York State Medicaid claims data for the analysis. We find that even among Medicaid beneficiaries, who are similar in socioeconomic status and identical in health insurance coverage, AIAN populations have much lower rates of use of outpatient services and much higher rates of acute (inpatient and emergency room) service utilization for both ILI and COVID-19 than non-Hispanic Whites. Prior to COVID-19, demographic and health status-adjusted all-cause mortality rates, including from ILI, were lower among American Indians than among non-Hispanic Whites on New York State Medicaid, but this pattern reversed during the COVID-19 pandemic. Both findings are driven by nonrural counties. We did not observe significant differences in all-cause mortality and acute service utilization comparing AIAN to non-Hispanic Whites in rural areas. The utilization and mortality disparities we identify within the Medicaid population highlight the need to move beyond insurance in addressing poor health outcomes in the American Indian population.

Patient Characteristics and Clinical Outcomes During the 2020-2021 COVID-19 Wave: An Observational Study at a Tertiary Hospital in Saudi Arabia.

Background and objective The continued prevalence and threat of coronavirus disease 2019 (COVID-19) have been reported, and evidence suggests that several people still get infected with the virus. Gaining a thorough understanding of the patient demographic factors and laboratory findings could contributeto assessing the severity, mortality, and progression of COVID-19. In light of this, the current study aimed to evaluate the demographic characteristics, laboratory findings, and outcomes of confirmed COVID-19 patients at a tertiary hospital in the Kingdom of Saudi Arabia (KSA). Methodology We collected data spanning the period 2020-2021 from the electronic health records of Al-Noor Specialized Hospital, Maincluding demographics (age, gender, and nationality), severity (i.e., ICU admission), length of hospital stay, mortality, and laboratory parameters. Results We observed an overall mortality rate of10.2% (338 of 3,307 patients). The mortality rate was significantly higher in males (n=210; 62.1%) and patients aged more than 70 years (n=91; 26.9%). Patients with blood group O comprised 131 (29%) of the 338 non-survivors, followed by those with A (n=85; 25.1%) and Bgroups (n=79; 23.4%). The mortality rate among ICU patients was 63.3% (n=214). Furthermore, the following laboratory findings showed abnormal mean values in terms of severity and mortality in COVID-19 patients: hemoglobin (HB) concentration, white blood cell (WBC) count, lymphocyte count (LC), C-reactive protein (CRP), creatinine (CREA), and uric acid (UA) levels. Conclusions Old age, male gender, and certain laboratory findings have a critical role inthe severity and mortality risk in COVID-19 patients. There was no significant association between blood type and the severity and mortality of COVID-19. Continuous monitoring based on these findings may be essential to managing COVID-19 patients.

Comparative analysis of COVID-19 responses in Japan and Africa: diet, phytochemicals, vitamin D, and gut microbiota in reducing mortality-A systematic review and meta-analysis.

As the novel coronavirus disease 2019 (COVID-19) pandemic subsides, the clinical sequelae are becoming more problematic. Interestingly, the statistical data indicate that Africa has experienced the lowest number of cases and deaths, with an unexpected phenomenon where the number of deaths from COVID-19 has not increased significantly. Several studies have investigated the relationship between diet and coronavirus. However, no systematic review/meta-analysis has conclusively linked diet (phytochemicals and vitamin D) and the gut microbiota in the context of COVID-19. This study examined the responses to COVID-19 in Japan and Africa, formulating the following hypotheses: (1) a healthy diet is effective against COVID-19, (2) blood vitamin D levels are associated with COVID-19 mortality, and (3) COVID-19 is associated with the gut microbiota. To investigate these hypotheses, a keyword search and meta-analysis were conducted using PubMed, and each hypothesis was tested. This study found that a healthy diet, particularly rich in phytochemicals such as polyphenols and flavonoids, is effective against COVID-19. An association was detected between blood vitamin D levels and COVID-19 mortality. The gut microbiota was linked to COVID-19 and its amelioration. These findings may have significant implications for not only understanding COVID-19 but also future prevention of pneumonia.

Significant association between asthma and a lower risk of mortality among COVID-19 patients in Spain: A meta-analysis.

Various prevalences of asthma in coronavirus disease 2019 (COVID-19) have been reported in different regions, and the association between asthma and COVID-19 subsequent mortality has been in debate. Thus, this study aimed to investigate whether there was a significant association between asthma and COVID-19 mortality in Spain through a meta-analysis. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were strictly complied with conducting this study. The pooled odds ratio (OR) with a corresponding 95% confidence interval (CI) was calculated by a random-effects model. The I 2 statistics for heterogeneity, sensitivity analysis for robustness, Begg's test, and Egger's test for publication bias, along with subgroup analyses for confounding bias, were also performed to support the foundation of this study. The meta-analysis revealed that asthma was significantly associated with a lower risk of mortality among COVID-19 patients in Spain with a random-effects model (pooled OR = 0.78, 95% CI = 0.69-0.88, I 2 = 35%). Further subgroup analyses by male proportion and sample size also indicated that a statistically significant negative correlation did exist between asthma and COVID-19 mortality. Robustness and no publication on-bias were evidenced by sensitivity analysis, Egger's test, and Begg's test, respectively. In conclusion, patients with asthma were found to have a lower risk of mortality from COVID-19 in Spain, especially among elderly patients. In addition, asthmatic patients infected with COVID-19 may be at risk of death compared to non-asthmatic patients, which is not a cause for undue concern, thereby reducing the burden of medication.

The surfactant protein B polymorphisms (rs7316 and rs1130866) and their correlation with disease progression of COVID-19

BackgroundIt is critical to examine the pathogenic pathways in coronavirus disease 2019 (COVID-19) that resulted in the development of severe lung injury. Surfactant protein B (SFTPB) is a vital component for sustaining life and serves pivotal functions in the host’s defensive mechanisms and alveolar surface tension reduction. Our study aimed to determine the effect of SFTPB rs7316 and rs1130866 variants on the course of disease in COVID-19 patients. MethodsThe study cohort comprised 3,184 individuals diagnosed with COVID-19. We employed the RFLP approach to determine the variations of the SFTPB genes. ResultsSFTPB rs7316 did not exhibit a statistically significant correlation with COVID-19 mortality across different inheritance models. But, after making more changes for SARS-CoV-2 variants, it was found that there was a strong link between the TT and TC genotypes of SFTPB rs7316 and death rates, especially for the Delta variant. Furthermore, our study’s findings indicate a significant association between the SFTPB rs1130866 G allele and an elevated risk of mortality in COVID-19 across all variants of SARS-CoV-2. ConclusionsThe use of the SFTPB rs1130866 marker has the potential to facilitate the prediction of COVID-19 severity. On the other hand, for SFTPB rs7316, this kind of prediction seems to depend on the particular SARS-CoV-2 variants.

Clinical and epidemiological characteristics of COVID-19 mortality in Saudi Arabia: A retrospective multi-center study

ABSTRACT Background/Aim: Coronavirus disease 2019 (COVID-19) increased morbidity and mortality in health institutions worldwide. The present study describes the epidemiological and clinical characteristics of COVID-19 mortality rates. Investigating the factors that affect COVID-19 mortality will be helpful in reducing the burden of morbidity and mortality in healthcare systems. Materials and Methods: The current retrospective observational study was carried out in the Kingdom of Saudi Arabia. COVID-19 cases resulting in death were admitted to hospitals from March 2020 to June 2020. The epidemiological and clinical characteristics of these cases of COVID-19-related death were collected and evaluated. Results: A total of 3260 COVID-19 death cases were included. The mean age of the subjects was 55 years. COVID-19 deaths more frequently in patients aged 50–59 years, 60–69 years, and 40–49 years (26%, 22%, and 17%, respectively). A greater percentage of COVID-19-related deaths (47%) was observed in June than in March (>1%), April (15%), and May (37%). Men accounted for most death cases (76%) compared to women. The COVID-19 mortality rate was higher among non-Saudi (71%) than Saudis (29%). The highest COVID-19 mortality was observed in Tabuk Region, whereas the lowest was observed in Najran. The mean stay duration of COVID-19 cases in the intensive care unit (ICU) was 11 days. The independent t-test indicated a statistically significant increase in the life expectancy (6 days) of ICU cases compared to non-ICU cases. Conclusion: The findings suggest that older age, male gender, and non-Saudi are risk factors that enhance COVID-19 mortality rates, while medical care increases the life expectancy of COVID-19 cases.

A critical review on phytochemicals as antiviral medications for SARS-CoV-2 virus infection.

A pandemic of acute respiratory infection, which was specified as coronavirus disease 2019, was instigated by a different strain of the virulent coronavirus SARS-CoV-2 that first appeared in late 2019. Since viral infections spread fast and there is presently no effective treatment, the use of plants with a long history of use in treating these infections has been explored regularly. The pandemic of coronavirus disease 2019 (COVID-19) has brought to light the dearth of medications with approval to treat acute viral illnesses. Because of this, the illness had a high fatality rate. The mortality rate was initially quite high and varied according to the patient's geographic location. For instance, among Chinese patients, the rate was 3·6%, whereas 1·5% of COVID-19-related deaths were documented outside of China. As of 2020, India has a 1.4% case fatality rate (CFR) of COVID-19 mortality, compared to 2.8% in Brazil and 1.8% in the USA. Many studies are being conducted to create pharmaceutical compounds specifically targeting important SARS-CoV-2 proteins. Several drug discovery initiatives are being undertaken to find powerful inhibitors by combining biochemical assay and computer-aided drug design techniques. Although plant-derived compounds have not had much success in the dominion of antivirals, plants are, however, believed to be a limitless supply of medications for a variety of diseases and clinical conditions. The scientific foundation required for developing novel natural source medications is provided by the chemical characterization and analysis of plant components. Most viral infections treated by ethnobotanical applications and historical literature on ayurveda, and traditional medicine are generally attributed to phytochemicals, which are compounds derived from medicinal plants. In this review, we have described the application of vascular plant-derived chemicals, such as tannins, polyphenols, alkaloids, and flavonoids, as antivirals, especially for managing COVID-19. This article discusses novel bioactive compounds and their molecular structures that target the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as prospective candidates for anti-coronavirus disease drugs. Moreover, to confirm the effectiveness of the phytochemicals that have demonstrated antiviral activity, clinical trials would need to be conducted in addition to the preclinical research that has already been done. To ensure spectacular findings, more applications of the compound would need to be studied to fully understand the effects of those phytochemicals whose clinical usefulness has already been established.

Effectiveness of laboratory tests in tracking severely COVID-19 infections

AIM: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a virus that causes COVID-19 (Coronavirus Disease 2019), and poses serious difficulties in terms of healthcare systems and global public health. With the large number of publications on COVID-19, clinicians need a synthesis of evidence to provide guidance when dealing with patients with COVID-19. Emerging studies reveal the existence of numerous demographic, clinical, immunological, biochemical and radiographic data that may be useful for clinicians to predict the severity and mortality of COVID-19. The aim is of this study; To determine laboratory parameters that can predict the course and severity of COVID-19 disease in patients with diagnosed solely SARS-CoV 2 PCR test positivity results and independently of the clinic status of selected patients and based on laboratory findings. MATERIALS AND METHODS: This study is a retrospective cross-sectional study conducted at Karacabey State Hospital between January and April 2022. Among the patients who applied to the COVID-19 outpatient clinic, 469 patients (261 females, 208 males) over the age of 18 and positive for SARS-CoV-2 RT-PCR were included in the study. The patients were divided into groups as outpatients, inpatients and patients in need of intensive care (intensive care unit, ICU). Demographic data (age, gender), COVID-19 RT-PCR results, and simultaneous laboratory parameters of the patients were scanned retrospectively. RESULTS: When CRP, urea, ferritin, LEU, NEU, MONO, RBC, HGB, HCT, MCV, NLR, PLR, CRP-NR, and SII index values were taken into consideration, a statistically significant difference was found between the groups. Creatinine, ALT, AST, LDH, troponin I, mass CK-MB, D dimer, LYM, EOS, PLT, ELR, and PNR values were not significantly different between the groups. CONCLUSIONS: Advantages of this study; Comparing the changes in the patient's other laboratory findings based on a single positive PCR test result and finding meaningful rates in terms of serious covid risk. The disadvantage of this study is that it is a study independent of the patient's clinic and disease stage. CRP, urea, ferritin, and indexes such as NLR, PLR, CRP-NR, and SII index values can be used to predict the severity of the disease.

The predictive significance of uric acid to high density lipoprotein- cholesterol ratio and uric acid for the severity and mortality of coronavirus disease-19

ObjectiveThe non-invasive and inexpensive predictive indicators seem to be essential for the evaluation of coronavirus disease-19 (COVID-19) prognosis. Uric acid to high-density lipoprotein-cholesterol ratio (UHR) have been known as inflammatory and metabolic biomarker in some disorders. This study aimed to evaluate the usefulness of serum uric acid (UA) and UHR values on admission as prognostic indicators for the severity and mortality of COVID-19. Regression models were accomplished to assess the association between UA and UHR with the severity and mortality of COVID-19.ResultsThis study was performed with 424 confirmed COVID-19 patients. The mean UA and UHR values of the severe group and deceased group were statistically higher than those mild group and survivor group, respectively (P < 0.05). Compared to the survivor cases, deceased subjects had lower serum concentrations of HDL-c (p < 0.05). Multivariate logistic regression analysis showed that UHR and UA values statistically are correlated with the severity (OR = 1.20 CI:1.07–1.35, OR = 1.19 CI:1.023–1.381 respectively) and mortality (OR = 10.04 CI:1.50–67.30, OR = 10.73 CI:1.47–87.11, respectively) of COVID-19. Compared with a reference range, serum UA levels ≥ 7.3 mg/dl and a UHR value greater than 0.185 increase the risk of critical care of COVID-19 almost 2.5 and 3.5 times, respectively. In summary, our results revealed that UHR index value and serum UA levels are useful biochemical indicators for predicting the severity and mortality of COVID-19.

Designing a model to estimate the burden of COVID-19 in Iran

The novel coronavirus disease 2019 (COVID-19) is the latest evidence of an epidemic disease resulting in an extraordinary number of infections and claimed several lives, along with extensive economic and social consequences. In response to the emergency situation, countries introduced different policies to address the situation, with different levels of efficacy. This paper outlines the protocol for developing a model to analyze the burden of COVID-19 in Iran and the effect of policies on the incidence and cumulative death of the disease. The importance of the model lies in the fact that no study, according to the authors’ best knowledge, tried to quantify the impact of the disease on Iran society and the impact of various implemented interventions on disease control. Based on a systematic review of COVID-19 prediction models and expert interviews, we developed a system dynamics model that not only includes an epidemic part but also considers the impact of various policies implemented by the Ministry of Health. The epidemic model estimates the incidence and mortality of COVID-19 in Iran. The model also intends to evaluate the effect of implemented policies on these outcomes. The model reflects the continuum of COVID-19 infection and care in Iran (of which some of its elements are unique) and key activities and decisions in delivering care. The model is calibrated and validated using data published by the Ministry of Health of Iran. Finally, the study aims to provide evidence of the impact of interventions intended to curb COVID-19 in Iran. Insights provided by the model will be necessary for controlling either future waves of the disease or similar future pandemics.

The Model for End-Stage Liver Disease (MELD) Score Predicting Mortality Due to SARS-CoV-2 in Mexican Patients.

Background/Objectives: Coronavirus Disease 2019 (COVID-19) can cause liver injury and a deterioration of hepatic function. The Model for End-Stage Liver Disease (MELD) score is a good predictor for poor prognosis of hospitalized COVID-19 patients in the United States, Egypt and Turkey. Nevertheless, the best cut-off value for the MELD score to predict mortality in the Mexican population has yet to be established. Methods: A total of 234 patients with COVID-19 were studied in a tertiary-level hospital. Patients were stratified into survivors (n = 139) and non-survivors (n = 95). Receiver operating characteristic curves, Cox proportional hazard models, Kaplan-Meier method, and Bonferroni corrections were performed to identify the predictors of COVID-19 mortality. Results: MELD score had an area under the curve of 0.62 (95% CI: 0.56-0.68; p = 0.0009), sensitivity = 53.68%, and specificity = 73.38%. Univariate Cox proportional hazard regression analysis suggested that the leukocytes > 10.6, neutrophils > 8.42, neutrophil-to-lymphocyte ratio (NLR) > 8.69, systemic immune-inflammation index (SII) > 1809.21, MELD score > 9, and leukocyte glucose index (LGI) > 2.41 were predictors for mortality. However, the multivariate Cox proportional hazard model revealed that only the MELD score >9 (Hazard Ratio [HR] = 1.83; 95% confidence interval [CI]: 1.2-2.8; Pcorrected = 0.03) was an independent predictor for mortality of COVID-19. Conclusions: Although the MELD score is used for liver transplantation, we suggest that a MELD score >9 could be an accurate predictor for COVID-19 mortality at admission to ICU requiring mechanical ventilation.

The effectiveness of COVID-19 vaccination in preventing hospitalisation and mortality: A nationwide cross-sectional study in Iran.

The pandemic of the coronavirus disease 2019 (COVID-19) led to a global health crisis, prompting widespread vaccination efforts to reduce severe outcomes. In this study, we assessed the impact of mass COVID-19 vaccination on hospitalisation and mortality rates in Iran, where over 83% of the vaccinated population received inactivated virus vaccines. Using retrospective, cross-sectional analysis, we examined data from the Iran Health Insurance Organisation, covering 41 million individuals from 20 February 2020 to 20 March 2022. We analysed hospital records from 956 Iranian hospitals, focusing on inpatient stays, short-term hospitalisations, and emergency department visits. Study outcomes included COVID-19 hospital admissions and associated mortality. We used negative binomial regression to compare hospital admission rates between periods, while we used a poison regression model with a log link to assess mortality risks before and after vaccination. Among 806 076 hospital admissions, 57 599 deaths were recorded. COVID-19 hospitalisations increased with age, and women had slightly higher admission rates than men. Advanced age and male sex correlated with higher mortality rates. Hospital admissions rose to 1178.66 per million population per month post-vaccination compared to 459.78 pre-vaccination. The incidence rate ratio was 2.09 (95% confidence interval (CI) = 1.90-2.32, P < 0.001), mainly due to the Delta variant. In contrast, post-vaccination mortality rates decreased from 111.33 to 51.66 per 1000 admissions per month. Post-vaccination, COVID-19 mortality significantly decreased, with a relative risk being 0.61 (95% CI = 0.60-0.62, P < 0.001) across all age groups and sexes. The Delta variant increased hospital admissions among vaccinated individuals, but widespread vaccination significantly reduced COVID-19-related mortality.

Artificial intelligence-powered chest computed tomography analysis unveils prognostic insights for COVID-19 mortality among prevalent hemodialysis patients.

Coronavirus disease 2019 (COVID-19) has led to severe pneumonia and mortality worldwide, however, clinical outcomes in end-stage renal disease patients remain unclear. This study evaluates the prognostic value of chest computed tomography (CT) findings in predicting COVID-19-related outcomes in prevalent hemodialysis patients. We retrospectively analyzed 326 prevalent hemodialysis patients diagnosed with COVID-19 who underwent chest CT scans. Characteristics assessed included pleural effusion, lung involvement volume, nodular consolidation, patchy infiltration, and ground-glass opacity. Artificial intelligence (AI)-assisted CT analysis quantified lung involvement. The primary endpoint was in-hospital mortality. Clinical data were collected, and logistic regression analysis assessed the association between CT findings and mortality. The mean age of the patients was 66.7 ± 12.6 years, 61.0% were male, and 58.6% were diabetic. Chest CT showed that 18.1% had lung involvement >10%, 32.5% had pleural effusion, 68.7% had nodular consolidation, 57.1% had patchy infiltration, and 58.0% had ground-glass opacity. Seventy patients (21.5%) died. Multivariate logistic regression analysis identified lung involvement >2.7% (odds ratio [OR], 16.70; 95% confidence interval [CI], 4.35-65.63), pleural effusion (OR, 3.28; 95% CI, 1.15-9.35), nodular consolidation (OR, 4.08; 95% CI, 1.12-14.82), and patchy infiltration (OR, 3.75; 95% CI, 1.17-12.03) as significant mortality risk factors. Chest CT findings, including lung involvement >2.7% and the presence of pleural effusion, nodular consolidation, and patchy infiltrates, significantly indicated mortality in COVID-19 pneumonia among prevalent hemodialysis patients. AI-assisted CT analysis proved useful in assessing lung involvement extent, showing that even minimal lung involvement can be associated with increased mortality.

ENaC gene variants and their involvement in Covid‑19 severity.

Epidemiological studies report the association of diverse cardiovascular conditions with coronavirus disease 2019 (COVID-19), but the causality has remained to be established. Specific genetic factors and the extent to which they can explain variation in susceptibility or severity are largely elusive. The present study aimed to evaluate the link between 32 cardio-metabolic traits and COVID-19. A total of 60 participants were enrolled, who were categorized into the following 4 groups: A control group with no COVID-19 or any other underlying pathologies, a group of patients with a certain form of dyslipidemia and predisposition to atherosclerotic disease, a COVID-19 group with mild or no symptoms and a COVID-19 group with severe symptomatology hospitalized at the Intensive Care Unit of Sotiria Hospital (Athens, Greece). Demographic, clinical and laboratory data were recorded and genetic material was isolated, followed by simultaneous analysis of the genes related to dyslipidemia using a custom-made next-generation sequencing panel. In the COVID-19 group with mild or absent symptoms, the variant c.112C>T:p.P38S was detected in the sodium channel epithelial 1 subunit α (SCNN1A) gene, with a major allele frequency (Maf) of <0.01. In the COVID-19 group with severe symptoms, the variant c.786G>A:p.T262T was detected in the SCNN1B gene, which encodes for the β-subunit of the epithelial sodium channel ENaC, with a Maf <0.01. None of the two rare variants were detected in the control or dyslipidemia groups. In conclusion, the current study suggests that ENaC variants are likely associated with genetic susceptibility to COVID-19, supporting the rationale for the risk and protective genetic factors for the morbidity and mortality of COVID-19.

Clinical and Laboratory Factors Associated with Mortality in ICU-Hospitalized COVID-19 Patients in a Western Center of Iran

Introduction: The purpose of this study was to investigate the demographic, clinical, and laboratory risk factors associated with mortality in Coronavirus disease 2019 (COVID-19) patients who were admitted to the intensive care unit (ICU) in Iran. Material &amp; Methods: This retrospective study analyzed data from 867 COVID-19 patients admitted to the ICU of Shahid Beheshti Hospital in Hamadan (west of Iran) from September 2020 to March 2022. The association between demographic, clinical, and laboratory factors and mortality rates was assessed using univariable and multiple logistic regression analysis. Results: During the study period, 512 (59.1%) patients were deceased from Covid-19. According to the adjusted logistic regression, the odds of death in patients with an age higher than 60 years were 1.12 (95% CI: 1.01- 1.24; p=0.026). The OR estimate of death in patients with bradycardia and tachycardia was 2.32 (95% CI: 1.72- 3.12; p &lt; 0.001) and 2.40 (95% CI: 1.67- 3.42; p &lt; 0.001), respectively. Moreover, SPO2 lower than 88%, WBC over 11 ×1000μL, K over 5.2 mEq/L, and LDH above 942 U/L were significantly associated with increased odds of death (p &lt; 0.05). Conclusion: The study identified several demographic, clinical, and laboratory risk factors associated with mortality in COVID-19 patients admitted to the ICU in Iran. These findings can help healthcare providers identify patients at higher risk of poor outcomes and tailor interventions accordingly.

Sulfated Bile Acids in Serum as Potential Biomarkers of Disease Severity and Mortality in COVID-19.

The fight against coronavirus disease 2019 (COVID-19) continues. Since the pandemic's onset, several biomarkers have been proposed to assess the diagnosis and prognosis of this disease. This research aimed to identify potential disease severity biomarkers in serum samples of patients with COVID-19 during the disease course. Data were collected using untargeted and targeted mass spectrometry methods. The results were interpreted by performing univariate and multivariate analyses. Important metabolite classes were identified by qualitative untargeted metabolomics in 15 serum samples from survivors of COVID-19. Quantitative targeted metabolomics on a larger patient cohort including 15 non-survivors confirmed serum 3-sulfate bile acids (i.e. GLCA-3S) were significantly increased in non-survivors compared to survivors during the early disease stage (p-value < 0.0001). Notably, it was associated with a higher risk of mortality (odds ratio of 26). A principal component analysis showed the ability to discriminate between survivors and non-survivors using the BA concentrations. Furthermore, increased BA-S is highly correlated with known parameters altered in severe clinical conditions.

Effectiveness of the First and Second Severe Acute Respiratory Syndrome Coronavirus 2 Vaccine Dose: A Nationwide Cohort Study From Austria on Hybrid Versus Natural Immunity.

We aimed to evaluate the effectiveness of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccinations in previously SARS-CoV-2-infected adults in the general population of Austria during the Delta wave and with extended follow-up. In a nationwide retrospective cohort study, we calculated age-, sex-, and nursing home residency-adjusted Cox proportional hazard ratios (HRs) of coronavirus disease 2019 (COVID-19) deaths, SARS-CoV-2 infections, and non-COVID-19 deaths from 1 October to 31 December 2021, and secondarily with extended follow-up to 30 June 2022. Relative vaccine effectiveness (rVE) is rVE = (1 - HR) × 100. Among 494 646 previously infected adults, 169 543 had received 2 vaccine doses, 133 567 had received 1 dose, and 190 275 were unvaccinated at baseline. We recorded 17 COVID-19 deaths (6 vaccinated, 11 unvaccinated) and 8209 SARS-CoV-2 infections. Absolute risk of COVID-19 deaths was 0.003%. rVE estimates for COVID-19 deaths and reinfections exceeded 75% until the end of 2021 but decreased substantially with extended follow-up. The risk of non-COVID-19 death was lower in those vaccinated versus unvaccinated. First and second SARS-CoV-2 vaccine doses appear effective in the short-term, but with diminishing effectiveness over time. The extremely low COVID-19 mortality, regardless of vaccination, indicates strong protection of previous infection against COVID-19 death. Lower non-COVID-19 mortality in the vaccinated population might suggest a healthy vaccinee bias.

Lack of association of ABO and RhD blood groups with COVID-19 mortality: A 2-center cross-sectional study in Saudi Arabia.

Several diseases, including both noninfectious diseases and bacterial and viral diseases, are associated with the ABO and RH blood group systems. Previous studies have shown a link between blood type and the probability of coronavirus disease 2019 (COVID-19) infection. In this study, we aimed to explore the correlation between deaths caused by COVID-19 and ABO and RhD blood types in Saudi Arabia. In this cross-sectional observational study, data from COVID-19 patients were collected from 2 major hospitals treating COVID-19 in Riyadh City, Saudi Arabia, between March 2020 and November 2021. The association between ABO and RhD blood types and COVID-19 outcomes was investigated. A total of 2302 real-time polymerase chain reaction-confirmed COVID-19 patients were enrolled in this study; a chi-square test was used to determine the statistical significance of the data. Of the 2302 enrolled patients, 1008 (43.8%) had blood type O, 677 (29.41%) had blood type A, 502 (21.8%) had blood type B, and 115 (5%) had blood type AB. Of the patients, 2143 (93.1%) were RhD-positive. The O-positive blood type had the highest mortality rate among COVID-19-infected patients, whereas the AB-negative type had the lowest. However, statistical analysis revealed no significant correlation between blood type (ABO or RhD) and COVID-19-based susceptibility or mortality. In conclusion, we found no association between ABO and RhD blood types and either susceptibility to or mortality due to COVID-19 in Saudi Arabia.

Estimated Deaths Averted in Adults by COVID-19 Vaccination in Select Latin American and Caribbean Countries.

The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact on global health, with millions of lives lost worldwide. Vaccination has emerged as a crucial strategy in mitigating the impact of the disease. This study aims to estimate the number of deaths averted through vaccination in Latin America and the Caribbean region (LAC) during the first year and a half of vaccination rollout (January 2021-May 2022). Publicly available data on COVID-19 deaths and vaccination rates were used to estimate the total number of deaths averted via vaccination in LAC. Using estimates for number of deaths, number of vaccinated, and vaccine effectiveness, a counterfactual estimated number of deaths observed without vaccination was calculated. Vaccine effectiveness estimates were obtained from published studies. The analysis focused on 17 countries in LAC and considered adults aged 18 years and older. After accounting for underreporting, the analysis estimated that >1.49 million deaths were caused by COVID-19 in the selected countries during the study period. Without vaccination, the model estimated that between 2.10 and 4.11 million COVID-19 deaths would have occurred. Consequently, vaccination efforts resulted in ∼610 000 to 2.61 million deaths averted. This study represents the first large-scale, multicenter estimate of population-level vaccine impact on COVID-19 mortality in LAC. The findings underscore the substantial impact of timely and widespread vaccination in averting COVID-19 deaths. These results provide crucial support for vaccination programs aimed at combating epidemic infectious diseases in the region and future pandemics.

Clinical profiles and mortality predictors of hospitalized patients with COVID-19 in Ethiopia

BackgroundStudying the characteristics of hospitalized Coronavirus Disease 2019 (COVID-19) patients is vital for understanding the disease and preparing for future outbreaks. The aim of this study was to analyze and describe the clinical profiles and factors associated with mortality among COVID-19 patients admitted to Jimma Medical Center COVID-19 Treatment Center (JMC CTC) in Ethiopia.MethodsAll confirmed COVID-19 patients admitted to JMC CTC between 17 April 2020 and 05 March 2022 were included in this study. Socio-demographic data, clinical information, and outcome variables were collected retrospectively from medical records and COVID-19 database at the hospital. Bivariable and multivariable analyses were performed to determine factors associated with COVID-19 severity and mortality. A P-value < 0.05 was considered statistically significant.ResultsA total of 542 confirmed COVID-19 patients were admitted to JMC CTC, of which 322 (59.4%) were male. Their median age was 48 years (IQR 32–64). About 51% (n = 277) of them had severe COVID-19 upon admission. Patients with hypertension [AOR: 2.8 (95% CI: 1.02–7.7, p = 0.046)], diabetes [AOR: 8.8 (95% CI: 1.2–17.3, p = 0.039)], and underlying respiratory diseases [AOR: 18.8 (95% CI: 2.06–71.51, p = 0.009)] were more likely to present with severe COVID-19 cases. Overall, 129 (23.8%) died in the hospital. Death rate was higher among patients admitted with severe disease [AHR = 5.5 (3.07–9.9) p < 0.001)] and those with comorbidities such as hypertension [AHR = 3.5 (2.28–5.41), p < 0.001], underlying respiratory disease [AHR = 3.4 (1.97–5.94), p < 0.001], cardiovascular disease (CVDs) [AHR = 2.8 (1.73–4.55), p < 0.001], and kidney diseases [AHR = 3.7 (2.3–5.96), p < 0.001].ConclusionAbout half of COVID-19 cases admitted to the hospital had severe disease upon admission. Comorbidities such as hypertension, diabetes, and respiratory diseases were linked to severe illness. COVID-19 admissions were associated with high inpatient mortality, particularly among those with severe disease and comorbidities.