Abstract Background The prognosis of patients with COVID-19 infection is uncertain. We derived and validated a new risk model for predicting progression to disease severity, hospitalization, admission to intensive care unit (ICU) and mortality in patients with COVID-19 infection (Gal-COVID-19 scores). Methods This is a retrospective cohort study of patients with COVID-19 infection confirmed by reverse transcription polymerase chain reaction (RT-PCR) in Galicia, Spain. Data were extracted from electronic health records of patients, including age, sex and comorbidities according to International Classification of Primary Care codes (ICPC-2). Logistic regression models were used to estimate the probability of disease severity. Calibration and discrimination were evaluated to assess model performance. Results The incidence of infection was 0.39% (10 454 patients). A total of 2492 patients (23.8%) required hospitalization, 284 (2.7%) were admitted to the ICU and 544 (5.2%) died. The variables included in the models to predict severity included age, gender and chronic comorbidities such as cardiovascular disease, diabetes, obesity, hypertension, chronic obstructive pulmonary disease, asthma, liver disease, chronic kidney disease and haematological cancer. The models demonstrated a fair–good fit for predicting hospitalization {AUC [area under the receiver operating characteristics (ROC) curve] 0.77 [95% confidence interval (CI) 0.76, 0.78]}, admission to ICU [AUC 0.83 (95%CI 0.81, 0.85)] and death [AUC 0.89 (95%CI 0.88, 0.90)]. Conclusions The Gal-COVID-19 scores provide risk estimates for predicting severity in COVID-19 patients. The ability to predict disease severity may help clinicians prioritize high-risk patients and facilitate the decision making of health authorities.
【저자키워드】 COVID-19, Hospitalization, severity, Prediction model, death, admission to ICU, 【초록키워드】 Asthma, Mortality, intensive care, obesity, disease severity, Infection, Haematological cancer, Comorbidity, Sex, Gender, risk, cardiovascular disease, Chronic kidney disease, progression, diabetes, classification, RT-PCR, hypertension, ICU, Electronic health record, Probability, ROC, Regression model, Patient, Spain, age, reverse transcription, incidence, estimate, Admission, patients, predict, COVID-19 patients, pulmonary disease, Liver disease, health authorities, retrospective cohort study, confidence interval, 95%CI, clinician, calibration, help, receiver operating characteristics, variable, high-risk patient, polymerase chain, Result, died, evaluated, required, facilitate, were used, demonstrated, prognosis of patient, chronic obstructive, patients with COVID-19, with COVID-19, 【제목키워드】 Comorbidity, development, predict, prognostic model,