Predictors for in-hospital mortality from coronavirus disease 2019 (COVID-19) infection among adults aged 18-65 years

Epidemiology, clinical features and outcomes of hospitalized patients with COVID-19 by vaccination status: a multicenter historical cohort study

INTRODUCTION

COVID-19 disease resulted in over six million deaths worldwide. Although vaccines against SARS-CoV-2 demonstrated efficacy, breakthrough infections became increasingly common. There is still a lack of data regarding the severity and outcomes of COVID-19 among vaccinated compared to unvaccinated individuals.

METHODS

This was a historical cohort study of adult COVID-19 patients hospitalized in five Ascension hospitals in southeast Michigan. Electronic medical records were reviewed. Vaccine information was collected from the Michigan Care Improvement Registry. Data were analyzed using Student's t-test, analysis of variance, the chi-squared test, the Mann-Whitney and Kruskal-Wallis tests, and multivariable logistic regression.

RESULTS

Of 341 patients, the mean age was 57.9 ± 18.3 years, 54.8% (187/341) were female, and 48.7% (166/341) were black/African American. Most patients were unvaccinated, 65.7%, 8.5%, and 25.8% receiving one dose or at least two doses, respectively. Unvaccinated patients were younger than fully vaccinated (p = 0.001) and were more likely to be black/African American (p = 0.002). Fully vaccinated patients were 5.3 times less likely to have severe/critical disease (WHO classification) than unvaccinated patients (p < 0.001) after controlling for age, BMI, race, home steroid use, and serum albumin levels on admission. The case fatality rate in fully vaccinated patients was 3.4% compared to 17.9% in unvaccinated patients (p = 0.003). Unvaccinated patients also had higher rates of complications.

CONCLUSIONS

Patients who were unvaccinated or partially vaccinated had more in-hospital complications, severe disease, and death as compared to fully vaccinated patients. Factors associated with severe COVID-19 disease included advanced age, obesity, low serum albumin, and home steroid use.

Mortality rate and predictors of COVID-19 inpatients in Ethiopia: a systematic review and meta-analysis

Introduction

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an extremely rare virus that devastates the economy and claims human lives. Despite countries' urgent and tenacious public health responses to the COVID-19 pandemic, the disease is killing a large number of people. The results of prior studies have not been used by policymakers and programmers due to the presence of conflicting results. As a result, this study was conducted to fill the knowledge gap and develop a research agenda.

Objective

This study aimed to assess the mortality rate and predictors of COVID-19 hospitalized patients in Ethiopia.

Methods

Electronic databases were searched to find articles that were conducted using a retrospective cohort study design and published in English up to 2022. The data were extracted using a Microsoft Excel spreadsheet and exported to StataTM version 17.0 for further analysis. The presence of heterogeneity was assessed and presented using a forest plot. The subgroup analysis, meta-regression, and publication bias were computed to identify the source of heterogeneity. The pool COVID-19 mortality rate and its predictors were calculated and identified using the random effects meta-analysis model, respectively. The significant predictors identified were reported using a relative risk ratio and 95% confidence interval (CI).

Results

Seven studies with 31,498 participants were included. The pooled mortality rate of COVID-19 was 9.13 (95% CI: 5.38, 12.88) per 1,000 person-days of mortality-free observation. Those study participants who had chronic kidney disease had 2.29 (95% CI: 1.14, 4.60) times higher chance of experiencing mortality than their corresponding counterparts, diabetics had 2.14 (95% CI: 1.22, 3.76), HIV patients had 2.98 (95% CI: 1.26, 7.03), hypertensive patients had 1.63 (95% CI: 1.43, 1.85), and smoker had 2.35 (95% CI: 1.48, 3.73).

Conclusion

COVID-19 mortality rate was high to tackle the epidemic of the disease in Ethiopia. COVID-19 patients with chronic renal disease, diabetes, hypertension, smoking, and HIV were the significant predictors of mortality among COVID-19 patients in Ethiopia. COVID-19 patients with chronic diseases and comorbidities need special attention, close follow-up, and care from all stakeholders.

Factors Associated with 28-day Critical Illness Development During the First Wave of COVID-19

Objective

This study aimed to define the predictors of critical illness development within 28 days postadmission during the first wave of the COVID-19 pandemic.

Materials and Methods

We conducted a prospective cohort study including 477 PCR-positive COVID-19 patients admitted to a tertiary care hospital in Istanbul from March 12 to May 12, 2020.

Results

The most common presenting symptoms were cough, dyspnea, and fatigue. Critical illness developed in 45 (9.4%; 95% CI=7.0%-12.4%) patients. In the multivariable analysis, age (hazard ratio (HR)=1.05, p<0.001), number of comorbidities (HR=1.33, p=0.02), procalcitonin ≥0.25 µg/L (HR=2.12, p=0.03) and lactate dehydrogenase (LDH) ≥350 U/L (HR=2.04, p=0.03) were independently associated with critical illness development. The World Health Organization (WHO) ordinal scale for clinical improvement on admission was the strongest predictor of critical illness (HR=4.15, p<0.001). The patients hospitalized at the end of the study period had a much better prognosis compared to the patients hospitalized at the beginning (HR=0.14; p=0.02). The C-index of the model was 0.92.

Conclusion

Age, comorbidity number, the WHO scale, LDH, and procalcitonin were independently associated with critical illness development. Mortality from COVID-19 seemed to be decreasing as the first wave of the pandemic advanced.

Graphic Abstract

Graphic Abstract.

Physiologic Scoring Systems in Predicting the COVID-19 Patients' one-month Mortality; a Prognostic Accuracy Study

Introduction : It is critical to quickly and easily identify severe coronavirus disease 2019 (COVID-19) patients and predict their mortality. This study aimed to determine the accuracy of the physiologic scoring systems in predicting the mortality of COVID-19 patients. Methods: This prospective cross-sectional study was performed on COVID-19 patients admitted to the emergency department (ED). The clinical characteristics of the participants were collected by the emergency physicians and the accuracy of the Quick Sequential Failure Assessment (qSOFA), Coronavirus Clinical Characterization Consortium (4C) Mortality, National Early Warning Score-2 (NEWS2), and Pandemic Respiratory Infection Emergency System Triage (PRIEST) scores for mortality prediction was evaluated. Results: Nine hundred and twenty-one subjects were included. Of whom, 745 (80.9%) patients survived after 30 days of admission. The mean age of patients was 59.13 ± 17.52 years, and 550 (61.6%) subjects were male. Non-Survived patients were significantly older (66.02 ± 17.80 vs. 57.45 ± 17.07, P< 0.001) and had more comorbidities (diabetes mellitus, respiratory, cardiovascular, and cerebrovascular disease) in comparison with survived patients. For COVID-19 mortality prediction, the AUROCs of PRIEST, qSOFA, NEWS2, and 4C Mortality score were 0.846 (95% CI [0.821-0.868]), 0.788 (95% CI [0.760-0.814]), 0.843 (95% CI [0.818-0.866]), and 0.804 (95% CI [0.776-0.829]), respectively. All scores were good predictors of COVID-19 mortality. Conclusion: All studied physiologic scores were good predictors of COVID-19 mortality and could be a useful screening tool for identifying high-risk patients. The NEWS2 and PRIEST scores predicted mortality in COVID-19 patients significantly better than qSOFA.

Clinical Features and Risk Factors for In-Hospital Mortality From COVID-19 Infection at a Tertiary Care Medical Center, at the Onset of the US COVID-19 Pandemic

Background:

Mortality from COVID-19 has been associated with older age, black race, and comorbidities including obesity, Understanding the clinical risk factors and laboratory biomarkers associated with severe and fatal COVID-19 will allow early interventions to help mitigate adverse outcomes. Our study identified risk factors for in-hospital mortality among patients with COVID-19 infection at a tertiary care center, in Detroit, Michigan.

Methods:

We conducted a single-center, retrospective cohort study at a 776-bed tertiary care urban academic medical center. Adult inpatients with confirmed COVID-19 (nasopharyngeal swab testing positive by real-time reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay) from March 8, 2020, to June 14, 2020, were included. Clinical information including the presence of comorbid conditions (according to the Charlson Weighted Index of Comorbidity (CWIC)), initial vital signs, admission laboratory markers and management data were collected. The primary outcome was in-hospital mortality.

Results:

Among 565 hospitalized patients, 172 patients died for a case fatality rate of 30.4%. The mean (SD) age of the cohort was 64.4 (16.2) years, and 294 (52.0%) were male. The patients who died were significantly older (mean [SD] age, 70.4 [14.1] years vs 61.7 [16.1] years; P < 0.0001), more likely to have congestive heart failure (35 [20.3%] vs 47 [12.0%]; P = 0.009), dementia (47 [27.3%] vs 48 [12.2%]; P < 0.0001), hemiplegia (18 [10.5%] vs 18 [4.8%]; P = 0.01) and a diagnosis of malignancy (16 [9.3%] vs 18 [4.6%]; P = 0.03).From multivariable analysis, factors associated with an increased odds of death were age greater than 60 years (OR = 2.2, P = 0.003), CWIC score (OR = 1.1, P = 0.023), qSOFA (OR = 1.7, P < 0.0001), WBC counts (OR = 1.1, P = 0.002), lymphocytopenia (OR = 2.0, P = 0.003), thrombocytopenia (OR = 1.9, P = 0.019), albumin (OR = 0.6, P = 0.014), and AST levels (OR = 2.0, P = 0.004) on admission.

Conclusions:

This study identified risk factor for in-hospital mortality among patients admitted with COVID-19 in a tertiary care hospital at the onset of U.S. Covid-19 pandemic. After adjusting for age, CWIC score, and laboratory data, qSOFA remained an independent predictor of mortality. Knowing these risk factors may help identify patients who would benefit from close observations and early interventions.

Do risk factors at the time of hospital admission differ by sex for in-hospital mortality from coronavirus disease 2019 (COVID-19)?

Background:

Sex-disaggregated data for coronavirus disease 2019 (COVID-19) reported higher hospitalized fatality rates among men than women.

Objective:

To determine whether the risk factors for in-hospital mortality from COVID-19, present at the time of hospital admission, differed by patient sex.

Design and setting:

Single-center, retrospective cohort study at a tertiary-care urban academic center.

Methods:

We reviewed the electronic medical records of patients positive for COVID-19 via qualitative polymerase chain reaction (PCR) assay, admitted between March 8 and June 14, 2020. Patients were stratified by sex to assess the association of variables present on admission with in-hospital mortality.

Results:

The overall inpatient case fatality rate (CFR) was 30.4% (172 of 565). The CFR among male patients was higher than among female patients: 99 (33.7%) versus 73 (26.9%), respectively (P = .08). Among males, comorbid conditions associated with in-hospital mortality were chronic pulmonary disease (P = .02) and connective tissue disease (P = .03). Among females, these comorbid conditions were congestive heart failure (P = .03), diabetes with complication (P = .05), and hemiplegia (P = .02). Variables that remained independently associated with death in males included age >70 years, public insurance, incremental increase in quick sepsis-related organ failure assessment (qSOFA) and C-reactive protein (CRP), lymphocytopenia, and thrombocytopenia. Among females, variables that remained independently associated with mortality included public insurance, incremental increase in Charlson weighted index of comorbidity (CWIC) score, qSOFA, and CRP.

Conclusions:

Risk factors for in-hospital mortality by sex included public insurance type, incremental increase in qSOFA and CRP in both sexes. For male patients, older age, lymphocytopenia and thrombocytopenia were also associated with mortality, whereas a higher Charlson score was associated with in-hospital mortality in female patients.