Early prognostication of COVID-19 to guide hospitalisation versus outpatient monitoring using a point-of-test risk prediction score.

INTRODUCTION: Risk factors of adverse outcomes in COVID-19 are defined but stratification of mortality using non-laboratory measured scores, particularly at the time of prehospital SARS-CoV-2 testing, is lacking. METHODS: Multivariate regression with bootstrapping was used to identify independent mortality predictors in patients admitted to an acute hospital with a confirmed diagnosis of COVID-19. Predictions were externally validated in a large random sample of the ISARIC cohort (N=14 231) and a smaller cohort from Aintree (N=290). RESULTS: 983 patients (median age 70, IQR 53-83; in-hospital mortality 29.9%) were recruited over an 11-week study period. Through sequential modelling, a five-predictor score termed SOARS (SpO2, Obesity, Age, Respiratory rate, Stroke history) was developed to correlate COVID-19 severity across low, moderate and high strata of mortality risk. The score discriminated well for in-hospital death, with area under the receiver operating characteristic values of 0.82, 0.80 and 0.74 in the derivation, Aintree and ISARIC validation cohorts, respectively. Its predictive accuracy (calibration) in both external cohorts was consistently higher in patients with milder disease (SOARS 0-1), the same individuals who could be identified for safe outpatient monitoring. Prediction of a non-fatal outcome in this group was accompanied by high score sensitivity (99.2%) and negative predictive value (95.9%). CONCLUSION: The SOARS score uses constitutive and readily assessed individual characteristics to predict the risk of COVID-19 death. Deployment of the score could potentially inform clinical triage in preadmission settings where expedient and reliable decision-making is key. The resurgence of SARS-CoV-2 transmission provides an opportunity to further validate and update its performance.

Relevance of prediction scores derived from the SARS-CoV-2 first wave, in the evolving UK COVID-19 second wave, for safe early discharge and mortality: a PREDICT COVID-19 UK prospective observational cohort study.

OBJECTIVE: Prospectively validate prognostication scores, SOARS and 4C Mortality Score, derived from the COVID-19 first wave, for mortality and safe early discharge in the evolving pandemic with SARS-CoV-2 variants (B.1.1.7 replacing D614) and healthcare responses altering patient demographic and mortality. DESIGN: Protocol-based prospective observational cohort study. SETTING: Single site PREDICT and multisite ISARIC (International Severe Acute Respiratory and Emerging Infections Consortium) cohorts in UK COVID-19 second wave, October 2020 to January 2021. PARTICIPANTS: 1383 PREDICT and 20 595 ISARIC SARS-CoV-2 patients. PRIMARY OUTCOME MEASURES: Relevance of SOARS and 4C Mortality Score determining in-hospital mortality and safe early discharge in the evolving UK COVID-19 second wave. RESULTS: 1383 (median age 67 years, IQR 52-82; mortality 24.7%) PREDICT and 20 595 (mortality 19.4%) ISARIC patient cohorts showed SOARS had area under the curve (AUC) of 0.8 and 0.74, while 4C Mortality Score had AUC of 0.83 and 0.91 for hospital mortality, in the PREDICT and ISARIC cohorts respectively, therefore, effective in evaluating safe discharge and in-hospital mortality. 19.3% (231/1195, PREDICT cohort) and 16.7% (2550/14992, ISARIC cohort) with SOARS of 0-1 were candidates for safe discharge to a virtual hospital (VH) model. SOARS implementation in the VH pathway resulted in low readmission, 11.8% (27/229) and low mortality, 0.9% (2/229). Use to prevent admission is still suboptimal, as 8.1% in the PREDICT cohort and 9.5% in the ISARIC cohort were admitted despite SOARS score of 0-1. CONCLUSIONS: SOARS and 4C Mortality Score remains valid, transforming complex clinical presentations into tangible numbers, aiding objective decision making, despite SARS-CoV-2 variants and healthcare responses altering patient demographic and mortality. Both scores, easily implemented within urgent care pathways for safe early discharge, allocate hospital resources appropriately to the pandemic's needs while enabling normal healthcare services resumption.