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1.
IJID Reg ; 3: 234-241, 2022 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-35720134

RESUMO

Purpose: As hyperinflammation is recognized as a driver of severe COVID-19 disease, checking markers of inflammation is gaining more attention. Our study aimed to evaluate the utility of cost-effective hemogram-derived ratios in predicting intensive care unit (ICU) admission in COVID-19 patients. Methods: This multicenter retrospective study included hospitalized COVID-19 patients from four dedicated COVID-19 hospitals in Sylhet, Bangladesh. Data on demographics, clinical characteristics, laboratory parameters and survival outcomes were analyzed. Logistic regression analysis was used to identify the significance of each hemogram-derived ratio in predicting ICU admission. Results: Of 442 included patients, 98 (22.17%) required ICU admission. At the time of admission, patients requiring ICU had a higher neutrophil count and lower lymphocyte and platelet counts than patients not requiring ICU. Peripheral capillary oxygen saturation at admission was significantly lower in those who subsequently required ICU admission. Neutrophil-to-lymphocyte ratio, derived neutrophil-to-lymphocyte ratio, neutrophil-to-platelet ratio, and systemic immune-inflammation index were significant predictors of ICU admission. Conclusion: Hemogram-derived ratios can be an effective tool in facilitating the early categorization of at-risk patients, enabling timely measures to be taken early in the disease course.

2.
Health Sci Rep ; 5(4): e663, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-35686199

RESUMO

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.

3.
Interdiscip Perspect Infect Dis ; 2022: 5904332, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35698592

RESUMO

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.

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