Objective: In this study, we aimed to determine the factors that contribute to the early determination of mortality risk in patients hospitalized with COVID-19 Methods: We included 941 adult inpatients (474 male [50 4%], mean age, 53 5 +/- 17 0 The patients were divided into two groups: the discharge group and the death group Epidemiological data, medical history, underlying comorbidities, laboratory findings, chest computed tomographic scans, real-time reverse transcription polymerase chain reaction detection results, and survival data were obtained with retrospective recordings on admission and follow-up The statistical relationship between survival data and parameters was analyzed A mathematical model was created from the data of both groups Results: While 863 patients survived, 78 were non-survivors During the study period, the preliminary case fatality rate of the inpatients was 8 3% The mean age of the non-survivors was 71 7 +/- 11 2 SD (P1000 ng/ml), high C-reactive protein (CRP), CK-MB, and LDH, and low lymphocyte count were associated with poor prognosis Conclusions: According to week 1 data of patients with COVID-19, advanced age, hypertension, D-Dimer, CRP, CK-MB, high LDH, and low lymphocyte were associated with poor prognosis We believe that this model will be useful in predicting patient mortality
Is It Possible To Predict Mortality Using Initial Data Of Adult Patients Hospitalized with COVID-19? A Mortality Prediction Model in the Early Phase of COVID-19