:: Volume 10, Issue 3 (6-2023) ::
2023, 10(3): 72-77 Back to browse issues page
The Charlson Comorbidity Index as a Predictor of mortality in hospitalized Covid-19 patients during the pandemic
Moslem Taheri Soodejani , Maryam Kazemi , Seyyed Mohammad Tabatabaei , Mohammad Hassan Lotfi
Center for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran , moslemtaheri7@gmail.com
Abstract:   (226 Views)
Introduction: This study aimed to predict the risk of mortality among COVID-19 patients in the central region of Iran by employing the Charlson Comorbidity Index (CCI), with adjustments made for age in the predictive model.
Material & Methods: In this cross-sectional study, encompassing all probable, suspicious, and confirmed COVID-19 cases from the onset of the pandemic (55307 individuals), 3415 cases resulting in death were designated as the study group, while the survivors constituted the control group.
Results: The Charlson Comorbidity Index revealed that over 11 percent of all patients had at least one underlying medical condition. Logistic regression analysis indicated a significantly elevated likelihood of mortality among patients with comorbidities. Specifically, individuals with a CCI score of 6 or higher were more than twice as likely to succumb to the virus compared to those without underlying diseases. Those with a score of 6 or more exhibited the highest odds ratio (OR 2.4; 95% CI 1.3-4.5).
Conclusion: The study findings underscore the heightened vulnerability of individuals to COVID-19 mortality, particularly among the elderly with pre-existing health conditions. The coexistence of age and comorbidities substantially increased the risk of death due to COVID-19 in this population. Consequently, targeted interventions and focused care strategies may be crucial for this high-risk demographic in pandemic management efforts.
Keywords: Mortality, Prediction, Infection, Charlson Comorbidity Index
Full-Text [PDF 1614 kb]   (65 Downloads)    
Type of Study: Research | Subject: Epidemiology
Received: 2022/09/6 | Accepted: 2023/12/11 | Published: 2023/06/25
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