Background This study aimed to develop a deep-learning model and a risk-score system using clinical variables to predict intensive care unit (ICU) admission and in-hospital mortality in COVID-19 patients. Methods This retrospective study consisted of 5,766 persons-under-investigation for COVID-19 between 7 February 2020 and 4 May 2020. Demographics, chronic comorbidities, vital signs, symptoms and laboratory tests at admission were collected. A deep neural network model and a risk-score system were constructed to predict ICU admission and in-hospital mortality. Prediction performance used the receiver operating characteristic area under the curve (AUC). Results The top ICU predictors were procalcitonin, lactate dehydrogenase, C-reactive protein, ferritin and oxygen saturation. The top mortality predictors were age, lactate dehydrogenase, procalcitonin, cardiac troponin, C-reactive protein and oxygen saturation. Age and troponin were unique top predictors for mortality but not ICU admission. The deep-learning model predicted ICU admission and mortality with an AUC of 0.780 (95% CI [0.760–0.785]) and 0.844 (95% CI [0.839–0.848]), respectively. The corresponding risk scores yielded an AUC of 0.728 (95% CI [0.726–0.729]) and 0.848 (95% CI [0.847–0.849]), respectively. Conclusions Deep learning and the resultant risk score have the potential to provide frontline physicians with quantitative tools to stratify patients more effectively in time-sensitive and resource-constrained circumstances.
【저자키워드】 SARS-CoV-2, coronavirus, Pneumonia, machine learning, Prediction model, 【초록키워드】 COVID-19, Mortality, intensive care, Comorbidities, C-reactive protein, prediction, risk, ferritin, procalcitonin, Symptom, lactate dehydrogenase, ICU, cardiac troponin, Retrospective study, oxygen saturation, Patient, ICU admission, age, vital signs, predictor, characteristic, Quantitative, Admission, predict, in-hospital mortality, COVID-19 patients, AUC, risk score, Laboratory test, 95% CI, physician, deep, Result, predicted, collected, develop, unique, clinical variable, 【제목키워드】 Mortality, ICU admission, COVID-19 patient, likelihood, deep, clinical variable,