Background The novel coronavirus SARS-19 produces ‘COVID-19’ in patients with symptoms. COVID-19 patients admitted to the hospital require early assessment and care including isolation. The National Early Warning Score (NEWS) and its updated version NEWS2 is a simple physiological scoring system used in hospitals, which may be useful in the early identification of COVID-19 patients. We investigate the performance of multiple enhanced NEWS2 models in predicting the risk of COVID-19. Methods Our cohort included unplanned adult medical admissions discharged over 3 months (11 March 2020 to 13 June 2020 ) from two hospitals (YH for model development; SH for external model validation). We used logistic regression to build multiple prediction models for the risk of COVID-19 using the first electronically recorded NEWS2 within ± 24 hours of admission. Model M0’ included NEWS2; model M1’ included NEWS2 + age + sex, and model M2’ extends model M1’ with subcomponents of NEWS2 (including diastolic blood pressure + oxygen flow rate + oxygen scale). Model performance was evaluated according to discrimination (c statistic), calibration (graphically), and clinical usefulness at NEWS2 ≥ 5. Results The prevalence of COVID-19 was higher in SH (11.0 %=277/2520) than YH (8.7 %=343/3924) with a higher first NEWS2 scores ( SH 3.2 vs YH 2.8) but similar in-hospital mortality (SH 8.4 % vs YH 8.2 %). The c-statistics for predicting the risk of COVID-19 for models M0’,M1’,M2’ in the development dataset were: M0’: 0.71 (95 %CI 0.68–0.74); M1’: 0.67 (95 %CI 0.64–0.70) and M2’: 0.78 (95 %CI 0.75–0.80)). For the validation datasets the c-statistics were: M0’ 0.65 (95 %CI 0.61–0.68); M1’: 0.67 (95 %CI 0.64–0.70) and M2’: 0.72 (95 %CI 0.69–0.75) ). The calibration slope was similar across all models but Model M2’ had the highest sensitivity (M0’ 44 % (95 %CI 38-50 %); M1’ 53 % (95 %CI 47-59 %) and M2’: 57 % (95 %CI 51-63 %)) and specificity (M0’ 75 % (95 %CI 73-77 %); M1’ 72 % (95 %CI 70-74 %) and M2’: 76 % (95 %CI 74-78 %)) for the validation dataset at NEWS2 ≥ 5. Conclusions Model M2’ appears to be reasonably accurate for predicting the risk of COVID-19. It may be clinically useful as an early warning system at the time of admission especially to triage large numbers of unplanned hospital admissions. Supplementary Information The online version contains supplementary material available at 10.1186/s12913-021-06951-x.
【저자키워드】 vital signs, National Early Warning Score, emergency admission, Novel coronavirus SARS-19, Computer-aided national early warning score, 【초록키워드】 hospital, Symptoms, Novel coronavirus, hospitals, sensitivity, specificity, Cohort, Patient, Model, Isolation, Logistic regression, dataset, Admission, Care, score, in-hospital mortality, COVID-19 patients, Blood, COVID-19 patient, Hospital admissions, physiological, scoring system, NEWS2, supplementary material, calibration slope, risk of COVID-19, diastolic, Result, highest, clinically, evaluated, appear, discharged, recorded, build, prevalence of COVID-19, 【제목키워드】 Accuracy, Admission, score, retrospective, validation study, risk of COVID-19,