Journal of Basic Research in Medical Sciences

en The Charlson Comorbidity Index as a Predictor of Mortality in Hospitalized COVID-19 Patients During the Pandemic پژوهشي Research <div style="text-align: justify;">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. Materials & 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.</div> Mortality, Prediction, Infection, Charlson Comorbidity Index 72 77 http://jbrms.medilam.ac.ir/browse.php?a_code=A-10-684-1&slc_lang=en&sid=1 Moslem Taheri Soodejani moslem.taheri2009@yahoo.com 10031947532846007533 10031947532846007533 No Center for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran Maryam Kazemi 10031947532846007534 10031947532846007534 No Center for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran Seyyed Mohammad Tabatabaei moh.taba@gmail.com 10031947532846007535 10031947532846007535 No Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran Mohammad Hassan Lotfi moslemtaheri7@gmail.com 10031947532846007536 10031947532846007536 Yes Center for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran