ArticlePloS one2023
Determinants of mortality among hospitalized patients with COVID-19 during first and second waves of the pandemic: A retrospective cohort study from an isolation center in Kano, Nigeria.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- A study of family care needs after pediatric congenital heart disease interventions based on the KANO model.BMC cardiovascular disorders · 2025Article
- In-hospital mortality predictors among COVID-19 patients in the West Bank, Palestine: a multi-center retrospective cohort study.Frontiers in medicine · 2025Article
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39 authors.
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Abstract
backgroundCoronavirus disease 2019 (COVID-19) has emerged as an important cause of morbidity and mortality worldwide. The aim of this study is to identify the clinical predictors of mortality among patients with COVID-19 pneumonia during first and second waves in a treatment center in northwestern Nigeria.
methodsThis was a retrospective cohort study of 195 patients hospitalized with COVID-19 between April 2020 to March 2021 at a designated COVID-19 isolation center in Kano State, Northwest Nigeria. Data were summarized using frequencies and percentages. Unadjusted odds ratios and 95% confidence intervals and p-values were obtained. To determine independent determinants of mortality, we performed a stepwise multivariate logistic regression model.
resultsOf 195 patients studied, 21(10.77%) patients died. Males comprised 158 (81.03%) of the study population. In the adjusted stepwise logistic regression analysis, age>64 years (OR = 9.476, 95% CI: 2.181-41.165), second wave of the pandemic (OR = 49.340, 95% CI:6.222-391.247), cardiac complications (OR = 24.984, 95% CI: 3.618-172.508), hypertension (OR = 5.831, 95% CI:1.413-24.065) and lowest systolic blood pressure while on admission greater than or equal to 90mmHg were independent predictors of mortality (OR = 0.111, 95%CI: 0.021-0.581).
conclusionStrategies targeted to prioritize needed care to patients with identified factors that predict mortality might improve patient outcome.
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