The Journal of Infectious Diseases · 2020 · 44 citations · 20 references
NursingEmergency MedicineInternal MedicineClinical Decision SupportRisk AssessmentSurvival AnalysisDiagnostic Test EvaluationHealthcare Performance MeasurementHospital Performance EvaluationMortality Risk AssessmentPrognostic AssessmentAcuity ClassificationClinical Acuity AssessmentClinical Risk ScoresHospitalization Risk PredictionOutpatient ScreeningPatient Acuity MeasurementPatient Acuity StratificationProspective Cohort Data
BACKGROUND: We sought to develop an automatable score to predict hospitalization, critical illness, or death for patients at risk for coronavirus disease 2019 (COVID-19) presenting for urgent care. METHODS: We developed the COVID-19 Acuity Score (CoVA) based on a single-center study of adult outpatients seen in respiratory illness clinics or the emergency department. Data were extracted from the Partners Enterprise Data Warehouse, and split into development (n = 9381, 7 March-2 May) and prospective (n = 2205, 3-14 May) cohorts. Outcomes were hospitalization, critical illness (intensive care unit or ventilation), or death within 7 days. Calibration was assessed using the expected-to-observed event ratio (E/O). Discrimination was assessed by area under the receiver operating curve (AUC). RESULTS: In the prospective cohort, 26.1%, 6.3%, and 0.5% of patients experienced hospitalization, critical illness, or death, respectively. CoVA showed excellent performance in prospective validation for hospitalization (expected-to-observed ratio [E/O]: 1.01; AUC: 0.76), for critical illness (E/O: 1.03; AUC: 0.79), and for death (E/O: 1.63; AUC: 0.93). Among 30 predictors, the top 5 were age, diastolic blood pressure, blood oxygen saturation, COVID-19 testing status, and respiratory rate. CONCLUSIONS: CoVA is a prospectively validated automatable score for the outpatient setting to predict adverse events related to COVID-19 infection.
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Scikit-learn: Machine Learning in Python
Fabián Pedregosa, Gaël Varoquaux, Alexandre Gramfort et al. · arXiv (Cornell University) · 2012 · 63.7K citations · Full text
Clinical Characteristics of Coronavirus Disease 2019 in China
Wei‐jie Guan, Zhengyi Ni, Yu Hu et al. · New England Journal of Medicine · 2020 · 31.2K citations · Full text
Veterinary Medicine, Infectious Diseases, Internal Medicine +10