The Charlson Comorbidity Index as a Predictor of mortality in hospitalized Covid-19 patients during the pandemic

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 preexisting 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.