Age-adjusted Charlson comorbidity index score is the best predictor for severe clinical outcome in the hospitalized patients with COVID-19 infection.

ABSTRACT: Aged population with comorbidities demonstrated high mortality rate and severe clinical outcome in the patients with coronavirus disease 2019 (COVID-19). However, whether age-adjusted Charlson comorbidity index score (CCIS) predict fatal outcomes remains uncertain.This retrospective, nationwide cohort study was performed to evaluate patient mortality and clinical outcome according to CCIS among the hospitalized patients with COVID-19 infection. We included 5621 patients who had been discharged from isolation or had died from COVID-19 by April 30, 2020. The primary outcome was composites of death, admission to intensive care unit, use of mechanical ventilator or extracorporeal membrane oxygenation. The secondary outcome was mortality. Multivariate Cox proportional hazard model was used to evaluate CCIS as the independent risk factor for death.Among 5621 patients, the high CCIS (≥ 3) group showed higher proportion of elderly population and lower plasma hemoglobin and lower lymphocyte and platelet counts. The high CCIS group was an independent risk factor for composite outcome (HR 3.63, 95% CI 2.45-5.37, P < .001) and patient mortality (HR 22.96, 95% CI 7.20-73.24, P < .001). The nomogram showed that CCIS was the most important factor contributing to the prognosis followed by the presence of dyspnea (hazard ratio [HR] 2.88, 95% confidence interval [CI] 2.16-3.83), low body mass index < 18.5 kg/m2 (HR 2.36, CI 1.49-3.75), lymphopenia (<0.8 x109/L) (HR 2.15, CI 1.59-2.91), thrombocytopenia (<150.0 x109/L) (HR 1.29, CI 0.94-1.78), anemia (<12.0 g/dL) (HR 1.80, CI 1.33-2.43), and male sex (HR 1.76, CI 1.32-2.34). The nomogram demonstrated that the CCIS was the most potent predictive factor for patient mortality.The predictive nomogram using CCIS for the hospitalized patients with COVID-19 may help clinicians to triage the high-risk population and to concentrate limited resources to manage them.

Clinical outcomes of initially asymptomatic patients with COVID-19: a Korean nationwide cohort study.

BACKGROUND: This study was performed to compare severe clinical outcome between initially asymptomatic and symptomatic infections and to identify risk factors associated with high patient mortality among initially asymptomatic patients. METHODS: In this retrospective, nationwide cohort study, we included 5621 patients who had been discharged from isolation or died from COVID-19 by 30 April 2020. The mortality rate and admission rate to intensive care unit (ICU) were compared between initially asymptomatic and symptomatic patients. We established a prediction model for patient mortality through risk factor analysis among initially asymptomatic patients. RESULTS: The prevalence of initially asymptomatic patients upon admission was 25.8%. The mortality rates were not different between groups (3.3% vs. 4.5%, p = .17). However, initially symptomatic patients were more likely to receive ICU care compared to initially asymptomatic patients (4.1% vs. 1.0%, p < .0001). The age-adjusted Charlson comorbidity index score (CCIS) was the most potent predictor for patient mortality in initially asymptomatic patients. CONCLUSIONS: The mortality risk was not determined by the initial presence of symptom among hospitalized COVID-19 patients. The CCIS was the most potent predictors for mortality. The clinicians should predict the risk of death by evaluating age and comorbidities but not the initial presence of symptom. Key messages The mortality rate was not different between initially asymptomatic and symptomatic patients. Symptomatic patients were more likely to admitted to the intensive care unit. Age and comorbidities were the potent risk factors for mortality.