Development of decision tree classification algorithms in predicting mortality of COVID-19 patients.

INTRODUCTION: The accurate prediction of COVID-19 mortality risk, considering influencing factors, is crucial in guiding effective public policies to alleviate the strain on the healthcare system. As such, this study aimed to assess the efficacy of decision tree algorithms (CART, C5.0, and CHAID) in predicting COVID-19 mortality risk and compare their performance with that of the logistic model. METHODS: This retrospective cohort study examined 5080 cases of COVID-19 in Babol, a city in northern Iran, who tested positive for the virus via PCR from March 2020 to March 2022. In order to check the validity of the findings, the data was randomly divided into an 80% training set and a 20% testing set. The prediction models, such as Logistic regression models and decision tree algorithms, were trained on the 80% training data and tested on the 20% testing data. The accuracy of these methods for the test samples was assessed using measures like ROC curve, sensitivity, specificity, and AUC. RESULTS: The findings revealed that the mortality rate for COVID-19 patients who were admitted to hospitals was 7.7%. Through cross validation, it was determined that the CHAID algorithm outperformed other decision tree and logistic regression algorithms in specificity, and precision but not sensitivity in predicting the risk of COVID-19 mortality. The CHAID algorithm demonstrated a specificity, precision, accuracy, and F-score of 0.98, 0.70, 0.95, and 0.52 respectively. All models indicated that factors such as ICU hospitalization, intubation, age, kidney disease, BUN, CRP, WBC, NLR, O2 sat, and hemoglobin were among the factors that influenced the mortality rate of COVID-19 patients. CONCLUSIONS: The CART and C5.0 models had outperformed in sensitivity but CHAID demonstrates a better performance compared to other decision tree algorithms in specificity, precision, accuracy and shows a slight improvement over the logistic regression method in predicting the risk of COVID-19 mortality in the population under study.

Circulatory diseases and the wide sex and ethnic life expectancy gaps in Bulgaria since 2010.

OBJECTIVES: Despite extensive public health initiatives, Bulgaria still has the lowest life expectancy at birth (LE) in the European Union. Sex and ethnic differences in LE and mortality are also exceptionally large. We aimed to identify what causes of death drive these wide disparities and thus provide clear targets for future public health interventions. DESIGN AND METHODS: We conducted a retrospective analysis of mortality rates from 2010 to 2022 to assess sex disparities in LE by age and cause of death. Combining mortality data with the 2021 Bulgarian census also allowed us to study LE disparities among the three main ethnic groups (Bulgarians, Turks, and Roma). We implemented standard demographic decomposition methods to quantify the role of seven major causes of death on LE disparities. RESULTS: We found that the difference between male and female LE has persisted for around seven years. Circulatory diseases contribute 3.66 years, or around 50% of the male-female gap. Ethnic LE disparities are larger for women than for men. Circulatory diseases account for more than 60% of these ethnic LE gaps. COVID-19 mortality explained between 0.5 and 1.1 years of the male-female gap. We found minimal differences in COVID-19 mortality across ethnic groups in Bulgaria. CONCLUSION: In Bulgaria, circulatory diseases contributed more to both the sex and ethnic LE gaps than in any other previously studied country. Our findings suggest that future public health policy initiatives should focus on circulatory diseases to narrow the Bulgarian LE disparities. One possible target for such a policy would be to reduce excessive smoking and alcohol consumption.

COVID-19 deaths in dental occupations and other healthcare occupations among U.S. decedents in 2020.

BACKGROUND: Early studies during the COVID-19 pandemic suggested dental occupations were among the highest risk for exposure to SARs-CoV-2 because of multiple factors increasing exposure, including close proximity to unmasked patients and performance of aerosol-generating procedures. However, to date, few studies have investigated COVID-19 deaths in United States dental occupations, and compared COVID-19 deaths among healthcare occupations. METHODS: We analyzed 2020 mortality data collected by the National Center for Health Statistics' National Vital Statistics System. Multivariable logistic regression was used to generate odds ratios (ORs) and 95% confidence intervals for COVID-19 as the underlying cause of death in relation to occupation in working-age decedents (≤65 years), after adjusting for age, sex, race/ethnicity, education, and medical conditions associated with severe COVID-19. RESULTS: Dental occupations did not have significantly higher risk for COVID-19 death when compared to all other occupations combined. Among healthcare occupations with frequent, direct patient- or client interactions, LPNs and LVNs, and speech and language pathologists had significantly elevated adjusted ORs for COVID-19 death when compared to dentists, dental hygienists, or dental assistants. Similarly, nurse practitioners had significantly higher ORs for COVID-19 mortality than dentists or dental hygienists, and approached significance when compared to dental assistants. Conversely, massage therapists and other health diagnosing and treating practitioners had significantly lower adjusted ORs for COVID-19 death compared with dental occupations. CONCLUSION: Our study highlights potential differences in work-related transmission of SARs-CoV-2 and subsequent COVID-19 deaths in healthcare occupations, and furthers a previously limited understanding of COVID-19 deaths in healthcare occupations in 2020, before COVID-19 vaccine availability. Our results indicate that dental occupations were not among the highest, nor lowest risk, healthcare occupations for COVID-19 deaths in 2020, despite their known risks of direct exposure.

Outcomes of Covid-19 among patients with ischemic heart disease: A propensity matched analysis.

BACKGROUND: Prior research has linked cardiovascular diseases with higher COVID-19 mortality and worse hospital outcomes, particularly in severe heart failure. Large population-based data regarding the impact of pre-existing ischemic heart disease (IHD) on COVID-19 outcomes is not well established. OBJECTIVE: To study the impact of COVID-19 infection on IHD hospital mortality and other outcomes. METHODS: The study included a patient cohort from the 2020 and 2021 National Inpatient Sample (NIS) database. Propensity score matching was used to match the study cohort (COVID-19 with IHD) to controls (COVID-19 without IHD) using a 1:1 matching ratio. The outcomes analyzed were in-hospital mortality, rates of acute kidney injury (AKI), acute myocardial injury (AMI), cardiogenic shock, cardiac arrest, mechanical ventilation, tracheal intubation, pulmonary embolism (PE), ventricular tachycardia (VT), ventricular fibrillation (VF), length of stay (LOS), and total hospitalization charges. RESULTS: A total of 2,532,652 patients met the inclusion criteria (1,199,008 females [47.3 %), predominantly Caucasian 1,456,203 (57.5 %); mean [SD] age 63, (5.4), including 29,315 (1.1 %) patients with a history of IHD. Following propensity matching, 4,772 COVID-19 patients with and without IHD were matched. IHD patients had higher rates of AMI (adjusted odds ratio (aOR) 3.75, 95 % CI 3.27-4.31, p < 0.001), cardiogenic shock (aOR 2.89, 95 % CI 1.60-5.19, p < 0.001), VT (aOR 3.26, 95 % CI 2.48-4.29, p < 0.001), and VF (aOR 2.23, 95 % CI 1.25-3.99, p < 0.001). The odds ratios of in-hospital mortality, AKI, PE, mechanical ventilation, tracheal intubation, and resource use were not significantly different. CONCLUSION: A history of IHD does not impact COVID-19 mortality but increases the risk of in-hospital cardiac complications.

Inpatient mortality and outcomes of COVID-19 among patients with non-ischemic cardiomyopathy: A propensity matched analysis.

BACKGROUND: Patients with chronic medical conditions, particularly cardiovascular diseases, are at a greater risk of adverse outcomes due to COVID-19. The effect of COVID-19 on patients with non-ischemic cardiomyopathy (NICM) is not known well. OBJECTIVES: To study the impact of COVID-19 infection on NICM hospital mortality and other outcomes. METHODS: This study included a cohort of patients from the 2020 and 2021 National Inpatient Sample databases. Patients hospitalized for COVID-19 with and without NICM were matched using a 1:1 propensity score-matching ratio. Outcomes analyzed were in-hospital mortality, rates of acute kidney injury (AKI), acute myocardial infarction (AMI), cardiogenic shock, cardiac arrest, mechanical ventilation, tracheal intubation, pulmonary embolism (PE), ventricular tachycardia (VT), ventricular fibrillation (VF), length of stay (LOS), and total hospitalization charges. RESULTS: A total of 2,532,652 patients met the inclusion criteria (1,199,008 females [47.3 %], predominantly white 1,456,203 (57.5 %); mean [SD] age 63 [5.4] years), including 64,155 (2.5 %) patients with a history of NICM. Following propensity matching, 10,258 COVID-19 patients with and without NICM were matched. Patients with NICM had higher rates of AMI (11.1 vs. 7.1 %, p < 0.001), cardiogenic shock (2 vs. 0.6 %, p < 0.001), cardiac arrest (4.4 vs. 3.2 %, p < 0.01), mechanical ventilation (13.7 vs 12 %, p < 0.01), VT (8.5 vs. 2.2 %, p < 0.001), and VF (1.0 vs 0.25 %, p < 0.001). The odds ratios for in-hospital mortality, AKI, and PE did not differ significantly. CONCLUSION: A History of NICM does not affect COVID-19 mortality but increases the risk of cardiovascular complications.

Indirect Effects of PM2.5 Exposure on COVID-19 Mortality in Greater Jakarta, Indonesia: An Ecological Study.

Background: Air pollution, including PM2.5, was suggested as one of the primary contributors to COVID-19 fatalities worldwide. Jakarta, the capital city of Indonesia, was recognized as one of the ten most polluted cities globally. Additionally, the incidence of COVID-19 in Jakarta surpasses that of all other provinces in Indonesia. However, no study has investigated the correlation between PM2.5 concentration and COVID-19 fatality in Jakarta. Objective: To investigate the correlation between short-term and long-term exposure to PM2.5 and COVID-19 mortality in Greater Jakarta area. Methods: An ecological time-trend study was implemented. The data of PM2.5 ambient concentration obtained from Nafas Indonesia and the National Institute for Aeronautics and Space (LAPAN)/National Research and Innovation Agency (BRIN). The daily COVID-19 death data obtained from the City's Health Office. Findings: Our study unveiled an intriguing pattern: while short-term exposure to PM2.5 showed a negative correlation with COVID-19 mortality, suggesting it might not be the sole factor in causing fatalities, long-term exposure demonstrated a positive correlation. This suggests that COVID-19 mortality is more strongly influenced by prolonged PM2.5 exposure rather than short-term exposure alone. Specifically, our regression analysis estimate that a 50 µg/m3 increase in long-term average PM2.5 could lead to an 11.9% rise in the COVID-19 mortality rate. Conclusion: Our research, conducted in one of the most polluted areas worldwide, offers compelling evidence regarding the influence of PM2.5 exposure on COVID-19 mortality rates. It emphasizes the importance of recognizing air pollution as a critical risk factor for the severity of viral respiratory infections.

Issue 4 - Impact of air pollution on COVID-19 mortality and morbidity: An epidemiological and mechanistic review.

Air pollution is a major global environment and health concern. Recent studies have suggested an association between air pollution and COVID-19 mortality and morbidity. In this context, a close association between increased levels of air pollutants such as particulate matter ≤2.5 to 10 µM, ozone and nitrogen dioxide and SARS-CoV-2 infection, hospital admissions and mortality due to COVID 19 has been reported. Air pollutants can make individuals more susceptible to SARS-CoV-2 infection by inducing the expression of proteins such as angiotensin converting enzyme (ACE)2 and transmembrane protease, serine 2 (TMPRSS2) that are required for viral entry into the host cell, while causing impairment in the host defence system by damaging the epithelial barrier, muco-ciliary clearance, inhibiting the antiviral response and causing immune dysregulation. The aim of this review is to report the epidemiological evidence on impact of air pollutants on COVID 19 in an up-to-date manner, as well as to provide insights on in vivo and in vitro mechanisms.

COVID-19 Predictors of Morbidity and Mortality.

Background and objectives There are multiple factors and comorbid conditions that can impact the outcomes of COVID-19. This study aimed to assess how patients with certain comorbidities and risk factors were affected by COVID-19. Methodology This retrospective study involved 578 inpatients who presented to the emergency room (ER) due to COVID-19 infection, diagnosed with COVID-19 between 2020 and 2021. This research takes note of COVID-19 severity, particularly in individuals with comorbidities such as chronic obstructive pulmonary disease (COPD), diabetes mellitus (DM), chronic kidney disease (CKD), coronary artery disease (CAD), and hypertension. Results A two-sample t-test found that age was a significant factor affecting hospital length of stay (LOS) and mortality. An ANOVA analysis of race, DM, and CAD showed a significant effect on LOS (p-values = 0.005, 0.01, and 0.01, respectively) but not on mortality and intubation. White patients had an increased LOS compared to other ethnicities. CKD and hypertension significantly affect mortality and LOS. However, COPD did significantly influence all three variables: mortality, intubation, and LOS (p-values = 0.005, 0.013, and 0.01, respectively). A multiple ANOVA test showed that COPD, hypertension, and CKD had a significant effect on mortality, intubation, and LOS (p-values = 0.014, 0.004, and 0.01, respectively). DM showed weaker significance on mortality, intubation, and LOS (p-value = 0.108). Conclusions Patients with all three comorbid conditions (COPD, hypertension, and CKD) had increased length of stay, intubation, and mortality; thus, appropriate measures including close observation and early intervention may be necessary to prevent mortality in these patients.

Effect of increasing doses of colchicine on the treatment of 333 COVID-19 inpatients.

BACKGROUND: Previous research done in Bulgaria demonstrated a fivefold reduction in mortality from COVID-19 with increased doses of colchicine from two hospitals in the country. We report here a further 333 cases of COVID-19 inpatients, treated with different doses of colchicine and its effect on mortality. MATERIALS AND METHODS: A case-control comparison from two additional hospitals was conducted between increased doses of colchicine and added bromhexine to standard of care (SOC) versus current SOC. Risk and odds ratio, as well as subgroup analysis, was conducted with newly reported data, alongside aggregate data from all hospital centers to determine the extent of mortality reduction in COVID-19 inpatients. RESULTS: There was a clear reduction in the mortality of inpatients with increasing doses of colchicine-between twofold and sevenfold. Colchicine loading doses of 4 mg are more effective than those with 2 mg. Despite these doses being higher than the so-called "standard doses," colchicine inpatients experienced lower mortality than SOC patients (5.7% vs. 19.53%). This mortality benefit was evident in different age subgroups, with a 4-mg loading dose of colchicine proving slightly superior to a 2-mg loading dose. Colchicine led to an overall relative risk reduction of 70.7%, with SOC patients having 3.91 higher odds of death. The safety of the doses was not different than the reported in the summary of product characteristics. CONCLUSION: Inpatients in Bulgaria with added colchicine and bromhexine to SOC achieved better clinical and mortality outcomes than those on SOC alone. These results question the World Health Organization-recommended strategy to inhibit viral replication. We posit that our treatment strategy to inhibit the Severe acute respiratory syndrome coronavirus 2 entry into the cell with inhaled bromhexine and the hyperactivated NLRP3 inflammasome with higher doses of colchicine, prevents the development of cytokine storm. The timing of the initiation of treatment seems critical.

Is Metformin Use Associated with a More Favorable COVID-19 Course in People with Diabetes?

Background: Diabetes Mellitus (DM) has been associated with a higher Coronavirus disease-19 (COVID-19) mortality, both in hospitalized patients and in the general population. A possible beneficial effect of metformin on the prognosis of COVID-19 has been reported in some observational studies, whereas other studies disagree. Methods: To investigate the possible effect of metformin on COVID-19 in-hospital mortality, we performed a retrospective study that included all SARS-CoV-2-positive patients with DM who were admitted to two Italian hospitals. In order to adjust for possible confounders accounting for the observed reduction of mortality in metformin users, we adopted the COVID-19 Mortality Risk Score (COVID-19 MRS) as a covariate. Results: Out of the 524 included patients, 33.4% died. A binomial logistic regression showed that metformin use was associated with a significant reduction in case fatality (OR 0.67 [0.45-0.98], p = 0.039), with no significant effect on the need for ventilation (OR 0.75 [0.5-1.11], p = 0.146). After adjusting for COVID-19 MRS, metformin did not retain a significant association with in-hospital mortality [OR 0.795 (0.495-1.277), p = 0.342]. Conclusions: A beneficial effect of metformin on COVID-19 was not proven after adjusting for confounding factors. The use of validated tools to stratify the risk for COVID-19 severe disease and death, such as COVID-19 MRS, may be useful to better explore the potential association of medications and comorbidities with COVID-19 prognosis.

Widening Disparities in COVID-19 Mortality and Life Expectancy Among 15 Major Racial and Ethnic Groups in the United States, 2020-2021.

Persistent and often widening racial/ethnic and socioeconomic inequalities in health have long existed in the US. Although racial/ethnic disparities in COVID-19 mortality are well documented, COVID-19 mortality risks and resultant reductions in life expectancy during the pandemic for detailed racial and ethnic groups in the US, including Asian and Hispanic subgroups, are not known. We used 2020-2021 US mortality data to estimate age-adjusted COVID-19 mortality rates, life expectancy, and the consequent declines in life expectancy due to COVID-19 overall and for the 15 largest racial/ethnic groups. We used standard life table methodology, cause-elimination life tables, and inequality indices to analyze trends in racial/ethnic disparities. The number of COVID-19 deaths increased from 350,827 in 2020 to 416,890 in 2021. COVID-19 death rates varied 7-fold among the racial/ethnic groups; Japanese and Chinese had the lowest mortality rates and Mexicans and American Indians/Alaska Natives (AIANs) had the highest rates. In 2021, life expectancy ranged from 70.3 years for Blacks and 70.6 years for AIANs to 85.2 years for Japanese and 87.7 years for Chinese. The life-expectancy gap was wide- 22.4 years in 2020 and 23.2 years in 2021. COVID-19 mortality had the greatest impact in reducing the life expectancy of Mexicans (3.53 years in 2020 and 3.78 years in 2021), Central/South Americans (4.86 years in 2020 and 3.50 years in 2021), and AIANs (2.51 years in 2020 and 2.38 years in 2021). Racial/ethnic inequalities in COVID-19 mortality, life expectancy, and resultant reductions in life expectancy during the pandemic widened between 2020 and 2021.

A Retrospective Study on the Outcome of Coronavirus Disease 2019 (COVID-19) Patients Admitted to a District General Hospital and Predictors of High Mortality.

BACKGROUND: The clinical features and severity of coronavirus disease 2019 (COVID-19) vary between patients and countries. Patients with certain conditions are predisposed to poor outcomes compared with those without medical conditions, such as diabetes, dementia, and hypertension (HTN). METHODS: The aim of this retrospective study was to assess factors associated with higher mortality in patients with COVID-19 infections and to identify the reason for hospital admission in these patients. The study was performed on patients admitted between 1 and 31 March 2020. Data collection was done retrospectively from electronic medical records. RESULTS: There were 269 patient admissions during this period, of which 147 were included in this audit. The mean age of COVID-19-positive patients was 62.8 years and 65.9 years for COVID-19-negative patients during this period. Forty-seven patients requiring hospital admission were COVID-19 positive and 93 were COVID-19 negative. There were no COVID-19 swabs in the seven patients included in the audit. Approximately 50% of the COVID-19-positive patients presented with fever and shortness of breath (sob), followed by dyspnea and cough (seven patients). The most common comorbidity was HTN, followed by type 2 diabetes mellitus (T2DM) and ischemic heart disease (IHD). The survival rate was 72.3% in COVID-19-positive patients and 80% in COVID-19-negative patients. The average length of stay was 14.4 days for COVID-19-positive survivors compared to 7.8 days for COVID-19-negative survivors. Most patients who tested positive for COVID-19 infection received oseltamivir vaccination and antibiotics. The presence of HTN, diabetes mellitus (DM), age, and organ failure was associated with a high mortality risk. CONCLUSION: Our study supports the findings of previous studies that diabetes, HTN, coronary artery disease, old age, and organ failure were associated with high mortality in patients admitted to hospitals with COVID-19 infections.

From test to rest: evaluating socioeconomic differences along the COVID-19 care pathway in the Netherlands.

INTRODUCTION: The COVID-19 pandemic exacerbated healthcare needs and caused excess mortality, especially among lower socioeconomic groups. This study describes the emergence of socioeconomic differences along the COVID-19 pathway of testing, healthcare use and mortality in the Netherlands. METHODOLOGY: This retrospective observational Dutch population-based study combined individual-level registry data from June 2020 to December 2020 on personal socioeconomic characteristics, COVID-19 administered tests, test results, general practitioner (GP) consultations, hospital admissions, Intensive Care Unit (ICU) admissions and mortality. For each outcome measure, relative differences between income groups were estimated using log-link binomial regression models. Furthermore, regression models explained socioeconomic differences in COVID-19 mortality by differences in ICU/hospital admissions, test administration and test results. RESULTS: Among the Dutch population, the lowest income group had a lower test probability (RR = 0.61) and lower risk of testing positive (RR = 0.77) compared to the highest income group. However, among individuals with at least one administered COVID-19 test, the lowest income group had a higher risk of testing positive (RR = 1.40). The likelihood of hospital admissions and ICU admissions were higher for low income groups (RR = 2.11 and RR = 2.46, respectively). The lowest income group had an almost four times higher risk of dying from COVID-19 (RR = 3.85), which could partly be explained by a higher risk of hospitalization and ICU admission, rather than differences in test administration or result. DISCUSSION: Our findings indicated that socioeconomic differences became more pronounced at each step of the care pathway, culminating to a large gap in mortality. This underlines the need for enhancing social security and well-being policies and incorporation of health equity in pandemic preparedness plans.

Assessing the Association between Biomarkers and COVID-19 Mortality Using the Joint Modelling Approach.

We evaluated the association between biomarkers and COVID-19 mortality. Baseline characteristics of 403 COVID-19 patients included sex and age; biomarkers, measured throughout the follow-up, included lymphocytes, neutrophils, ferritin, C-reactive protein, glucose, and LDH. Hazard ratios (HRs) and corresponding 95% credible intervals (CIs) were estimated through joint models (JMs) using a Bayesian approach. We fitted univariable (a single biomarker) and multivariable (all biomarkers) JMs. In univariable analyses, all biomarkers were significantly associated with COVID-19 mortality. In multivariable analysis, HRs were 1.78 (95% CI: 1.13-2.87) with a doubling of neutrophils levels, 1.49 (95% CI: 1.19-1.95) with a doubling of C-reactive protein levels, 2.66 (95% CI: 1.45-4.95) for an increase of 100 mg/dL of glucose, and 1.31 (95% CI: 1.12-1.55) for an increase of 100 U/L of LDH. No evidence of association was observed for lymphocytes and ferritin in multivariable analysis. Men had a higher COVID-19 mortality risk than women (HR = 1.75; 95% CI: 1.07-2.80) and age showed the strongest effect with a rapid increase from 60 years. These findings using JM confirm the usefulness of biomarkers in assessing COVID-19 severity and mortality. Monitoring trend patterns of such biomarkers can provide additional help in tailoring the appropriate care pathway.

Should we ignore SARS-CoV-2 disease?

Current World Health Organization (WHO) reports claim a decline in COVID-19 testing and reporting of new infections. To discuss the consequences of ignoring severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, the endemic characteristics of the disease in 2023 with the ones estimated before using 2022 data sets are compared. The accumulated numbers of cases and deaths reported to the WHO by the 10 most infected countries and global figures were used to calculate the average daily numbers of cases DCC and deaths DDC per capita and case fatality rates (CFRs = DDC/DCC) for two periods in 2023. In some countries, the DDC values can be higher than the upper 2022 limit and exceed the seasonal influenza mortality. The increase in CFR in 2023 shows that SARS-CoV-2 infection is still dangerous. The numbers of COVID-19 cases and deaths per capita in 2022 and 2023 do not demonstrate downward trends with the increase in the percentages of fully vaccinated people and boosters. The reasons may be both rapid mutations of the coronavirus, which reduced the effectiveness of vaccines and led to a large number of re-infections, and inappropriate management.

The effect of SARS-COV-2 variant on non-respiratory features and mortality among vaccinated and non-fully vaccinated patients.

OBJECTIVE: To determine the effect of SARS-CoV-2 variants on non-respiratory features of COVID-19 in vaccinated and not fully vaccinated patients using a University of California database. METHODS: A longitudinal retrospective review of medical records (n = 63,454) from 1/1/2020-4/26/2022 using the UCCORDS database was performed to compare non-respiratory features, vaccination status, and mortality between variants. Chi-square tests were used to study the relationship between categorical variables using a contingency matrix. RESULTS: Fever was the most common feature across all variants. Fever was significantly higher in not fully vaccinated during the Delta and Omicron waves (p = 0.001; p = 0.001). Cardiac features were statistically higher in not fully vaccinated during Omicron; tachycardia was only a feature of not fully vaccinated during Delta and Omicron; diabetes and GI reflux were features of all variants regardless of vaccine status. Odds of death were significantly increased among those not fully vaccinated in the Delta and Omicron variants (Delta OR: 1.64, p = 0.052; Omicron OR: 1.96, p < 0.01). Vaccination was associated with a decrease in the frequency of non-respiratory features. CONCLUSIONS: Risk of non-respiratory features of COVID-19 is statistically higher in those not fully vaccinated across all variants. Risk of death and correlation with vaccination status varied.

Differences in Covid-19 mortality among persons 70 years and older in an integrated care setting in region Stockholm: a multi-level analysis between March 2020-February 2021.

BACKGROUND: In Norrtälje municipality, within Region Stockholm, there is a joint integrated care organisation providing health and social care, which may have facilitated a more coordinated response to the covid-19 pandemic compared to the otherwise decentralised Swedish system. This study compares the risk of covid-19 mortality among persons 70 years and older, in the municipalities of Stockholm, Södertälje, and Norrtälje, while considering area and individual risk factors. METHODS: A population-based study using linked register data to examine covid-19 mortality among those 70 + years (N = 127,575) within the municipalities of interest between the periods March-August 2020 and September 2020-February 2021. The effect of individual and area level variables on covid-19 mortality among inhabitants in 68 catchment areas were examined using multi-level logistic models. RESULTS: Individual factors associated with covid-19 mortality were sex, older age, primary education, country of birth and poorer health as indicated by the Charlson Co-morbidity Index. The area-level variables associated were high deprivation (OR: 1.56, CI: 1.18-2.08), population density (OR: 1.14, CI: 1.08-1.21), and usual care. Together, this explained 85.7% of the variation between catchment areas in period 1 and most variation was due to individual risk factors in period 2. Little of the residual variation was attributed to differences between catchment areas. CONCLUSION: Integrated care in Norrtälje may have facilitated a more coordinated response during period 1, compared to municipalities with usual care. In the future, integrated care should be considered as an approach to better protect and meet the care needs of older people during emergency situations.

Relationship Between Rhabdomyolysis and SARS-CoV-2 Disease Severity.

Background Rhabdomyolysis has historically been associated with viral infections, of which influenza A is the most common. A literature review suggests that up to 1/3 of patients hospitalized with COVID-19 develop acute kidney injury (AKI), and of those, nearly half are admitted to the ICU. AKI complicating COVID-19 infection is attributed to several pathogeneses, including sepsis, direct cytopathic effects on the kidneys, and rhabdomyolysis. Objective We aimed to link COVID-19 infection to the development of rhabdomyolysis via creatine kinase (CK) measurement to assess whether this association increases ICU admission, length of stay (LOS), and mortality. Design and setting In this single-center, retrospective cohort study, we enrolled 984 adult patients with confirmed COVID-19 infection requiring admission to a community hospital between March 2020 and May 2021. Measurements Demographic data, laboratory values, and clinical outcomes were collected. The primary outcome measured was the development of rhabdomyolysis and/or AKI. Secondary outcomes included associations of rhabdomyolysis with ICU admission, length of hospital stay, and mortality, utilizing multivariable logistic regression methods. Results Out of the 984 patients included, 39 met the clinical criteria for rhabdomyolysis (4%). The incidence of rhabdomyolysis was higher in patients with AKI (38.3%) and in those who required ICU admission (53.8%) (p<0.001). There was an insignificant difference in death in this cohort (11 patients, 52.4%, p=0.996). However, the mean LOS in patients who had rhabdomyolysis was 18.2 days versus 9.8 days in patients who did not develop rhabdomyolysis (p<0.001). Conclusion Objectively tracking CK levels in COVID-19-infected patients can assist in diagnosing rhabdomyolysis, identifying AKI etiology, and accordingly making a preliminary prognosis for COVID-19 infection, which could direct physicians to initiate more intensive treatment earlier.

Insights into Covid-19 mortality: A comprehensive study of cardiovascular sensitivity, gender, race, and geography trends in the United States (2020-2023).

This investigation meticulously explores the evolving landscape of Covid-19-related mortality in the United States from 2020 to 2023. Leveraging the comprehensive CDC WONDER database, the study conducts a detailed analysis of age-adjusted mortality rates (AAMRs), considering various demographic and regional parameters. The identified pattern illustrates an initial surge in AAMRs from 2020 to 2021, followed by a subsequent decline until 2023. Notably, there is a discernible reduction in AAMRs for both the elderly (85 years and older) and infants (below one year). Within specific demographic segments, heightened AAMRs are observed among NH American Indian or Alaska Native individuals, men, and residents in particular states and regions. Emphasizing the significant impact of Covid-19 on cardiovascular health, the study underscores increased mortality rates associated with the cardiovascular and respiratory systems. AAMR rates were standardized per 100,000 population, providing a comparative metric. Noteworthy states with elevated AAMRs include Mississippi, Oklahoma, Kentucky, New Mexico, and Alabama, with the Southern region exhibiting the highest AAMR. The research sheds light on demographic and regional disparities in Covid-19-related mortality, calling for intensified efforts in prevention and treatment strategies. These findings, offering nuanced insights, serve as a guide for strategic public health initiatives to mitigate the multifaceted repercussions of the pandemic, especially among vulnerable populations.

Mortality risk after COVID-19 vaccination: A self-controlled case series study.

BACKGROUND: Although previous studies found no-increased mortality risk after COVID-19 vaccination, residual confounding bias might have impacted the findings. Using a modified self-controlled case series (SCCS) design, we assessed the risk of non-COVID-19 mortality, all-cause mortality, and four cardiac-related death outcomes after primary series COVID-19 vaccination. METHODS: We analyzed all deaths between December 14, 2020, and August 11, 2021, among individuals from eight Vaccine Safety Datalink sites. Demographic characteristics of deaths in recipients of COVID-19 vaccines and unvaccinated individuals were reported. We conducted SCCS analyses by vaccine type and death outcomes and reported relative incidences (RI). The observation period for death spanned from the dates of emergency use authorization to the end of the study period (August 11, 2021) without censoring the observation period upon death. We pre-specified a primary risk interval of 28-day and a secondary risk interval of 14-day after each vaccination dose. Adjusting for seasonality in mortality analyses is crucial because death rates vary over time. Deaths among unvaccinated individuals were included in SCCS analyses to account for seasonality by incorporating calendar month in the models. RESULTS: For Pfizer-BioNTech (BNT162b2), RIs of non-COVID-19 mortality, all-cause mortality, and four cardiac-related death outcomes were below 1 and 95 % confidence intervals (CIs) excluded 1 across both doses and both risk intervals. For Moderna (mRNA-1273), RI point estimates of all outcomes were below 1, although the 95 % CIs of two RI estimates included 1: cardiac-related (RI = 0.78, 95 % CI, 0.58-1.04) and non-COVID-19 cardiac-related mortality (RI = 0.80, 95 % CI, 0.60-1.08) 14 days after the second dose in individuals without pre-existing cancer and heart disease. For Janssen (Ad26.COV2.S), RIs of four cardiac-related death outcomes ranged from 0.94 to 0.98 for the 14-day risk interval, and 0.68 to 0.72 for the 28-day risk interval and 95 % CIs included 1. CONCLUSION: Using a modified SCCS design and adjusting for temporal trends, no-increased risk was found for non-COVID-19 mortality, all-cause mortality, and four cardiac-related death outcomes among recipients of the three COVID-19 vaccines used in the US.