Electrocardiogram abnormalities and higher body mass index as clinically applicable factors for predicting poor outcome in patients with coronavirus disease 2019

Background:Patients with coronavirus disease 2019(COVID-19)have high resource utilization.Identifying the causes of severe COVID-19 is helpful for early intervention to reduce the consumption of medical resources.Methods:We included 103 patients with COVID-19 in this single-center observational study.To evaluate the incidence,predictors,and effects of COVID-19,we analyzed demographic information,laboratory results,comorbidities,and vital signs as factors for association with severe COVID-19.Results:The incidence of severe COVID-19 was 16.5%and the percent poor outcome(including mortality,entering in ICU or transferred to a superior hospital)was 6.8%.The majority of severe COVID-19 patients had abnormal electrocardiogram(ECG)(82.35%),hypertension(76.47%)and other cardiac diseases(58.82%).Multivariate logistic regression was used to determine the predictors of severe illness.Abnormal body mass index(BMI)and ECG(P<0.05)were independent predictors of severe COVID-19.ECG abnormality was associated with increased odds of poor outcome(area under the receiver operating characteristic curves[AUC],0.793;P=0.010)and severe COVID-19(AUC,0.807;P<0.0001).Overweight was also associated with increased odds of poor outcome(AUC,0.728;P=0.045)and severe illness COVID-19(AUC,0.816;P<0.0001).Conclusion:Overweight and electrophysiological disorders on admission are important predictors of prognosis of patients with COVID-19.