Predictors of mortality and ICU requirement in hospitalized COVID-19 patients with diabetes: A multicentre study.

AIM: This study aimed to identify the predictors of mortality and ICU requirements in hospitalized COVID-19 Patients with Diabetes. DESIGN: Cross-sectional study. METHODS: It was a retrospective study of patients hospitalized with COVID-19 infection from October 2020-February 2021 in four hospitals in Sylhet, Bangladesh. Logistic regression analysis was applied to explore the predictors of ICU requirement and in-hospital mortality. RESULTS: In the whole cohort (n = 500), 11% of patients died and 24% of patients required intensive care unit (ICU) support. Non-survivors had significantly higher prevalence of lymphopenia, thrombocytopenia and leukocytosis. Significant predictors of in-hospital mortality were older age, neutrophil count, platelet count and admission peripheral capillary oxygen saturation (SpO2). Older age, ischemic heart disease, WBC count, D-dimer and admission SpO2 were identified as significant predictors for ICU requirement. PATIENT OR PUBLIC CONTRIBUTION: No.

Clinical Characteristics and Predictors of Mortality in Elderly Patients Hospitalized with COVID-19 in Bangladesh: A Multicenter, Retrospective Study.

Purpose: Elderly patients are at high risk of fatality from COVID-19. The present work aims to describe the clinical characteristics of elderly inpatients with COVID-19 and identify the predictors of in-hospital mortality at admission. Materials and Methods: In this retrospective, multicenter cohort study, we included elderly COVID-19 inpatients (n = 245) from four hospitals in Sylhet, Bangladesh, who had been discharged between October 2020 and February 2021. Demographic, clinical, and laboratory data were extracted from hospital records and compared between survivors and nonsurvivors. We used univariable and multivariable logistic regression analysis to explore the risk factors associated with in-hospital death. Principal Results. Of the included patients, 202 (82.44%) were discharged and 43 (17.55%) died in hospital. Except hypertension, other comorbidities like diabetes, chronic kidney disease, ischemic heart disease, and chronic obstructive pulmonary disease were more prevalent in nonsurvivors. Nonsurvivors had a higher prevalence of leukocytosis (51.2 versus 30.7; p=0.01), lymphopenia (72.1 versus 55; p=0.05), and thrombocytopenia (20.9 versus 9.9; p=0.07). Multivariable regression analysis showed an increasing odds ratio of in-hospital death associated with older age (odds ratio 1.05, 95% CI 1.01-1.10, per year increase; p=0.009), thrombocytopenia (OR = 3.56; 95% CI 1.22-10.33, p=0.019), and admission SpO2 (OR 0.91, 95% CI 0.88-0.95; p=0.001). Conclusions: Higher age, thrombocytopenia, and lower initial level of SpO2 at admission are predictors of in-hospital mortality in elderly patients with COVID-19.

Significance of hemogram-derived ratios for predicting in-hospital mortality in COVID-19: A multicenter study.

Background: To address the problem of resource limitation, biomarkers having a potential for mortality prediction are urgently required. This study was designed to evaluate whether hemogram-derived ratios could predict in-hospital deaths in COVID-19 patients. Materials and Methods: This multicenter retrospective study included hospitalized COVID-19 patients from four COVID-19 dedicated hospitals in Sylhet, Bangladesh. Data on clinical characteristics, laboratory parameters, and survival outcomes were analyzed. Logistic regression models were fitted to identify the predictors of in-hospital death. Results: Out of 442 patients, 55 (12.44%) suffered in-hospital death. The proportion of male was higher in nonsurvivor group (61.8%). The mean age was higher in nonsurvivors (69 ± 13 vs. 59 ± 14 years, p < 0.001). Compared to survivors, nonsurvivors exhibited higher frequency of comorbidities, such as chronic kidney disease (34.5% vs. 15.2%, p ≤ 0.001), chronic obstructive pulmonary disease (23.6% vs. 10.6%, p = 0.011), ischemic heart disease (41.8% vs. 19.4%, p < 0.001), and diabetes mellitus (76.4% vs. 61.8%, p = 0.05). Leukocytosis and lymphocytopenia were more prevalent in nonsurvivors (p < 0.05). Neutrophil-to-lymphocyte ratio (NLR), derived NLR (d-NLR), and neutrophil-to-platelet ratio (NPR) were significantly higher in nonsurvivors (p < 0.05). After adjusting for potential covariates, NLR (odds ratio [OR] 1.05; 95% confidence interval [CI] 1.009-1.08), d-NLR (OR 1.08; 95% CI 1.006-1.14), and NPR (OR 1.20; 95% CI 1.09-1.32) have been found to be significant predictors of mortality in hospitalized COVID-19 patients. The optimal cut-off points for NLR, d-NLR, and NPR for prediction of in-hospital mortality for COVID-19 patients were 7.57, 5.52 and 3.87, respectively. Conclusion: Initial assessment of NLR, d-NLR, and NPR values at hospital admission is of good prognostic value for predicting mortality of patients with COVID-19.