ABSTRACTIntroductionRisk factors of adverse outcomes in COVID-19 are defined but stratification of mortality using non-laboratory measured scores, particularly at the time of pre-hospital SARS-CoV-2 testing, is lacking.MethodsMultivariate regression with bootstrapping was used to identify independent mortality predictors in a derivation cohort of COVID-19 patients. Predictions were externally validated in a large random sample of the ISARIC cohort (N=14,231) and a smaller cohort from Aintree (N=290).Results983 patients (median age 70, IQR 53-83; in-hospital mortality 29.9%) were recruited over an 11-week study period. Through sequential modelling, a 5-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%).ConclusionThe 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 pre-admission 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.

Introduction We aimed to develop and validate a prediction table for a simplified measure of rightward shift of the fetal oxyhaemoglobin saturation (SpO 2 ) versus inspired oxygen pressure ( P I O 2 ) curve as an objective marker of lung disease severity in very preterm infants, independent of unit altitude or oxygen prescribing policies. Methods Very preterm infants (n=219) had an oxygen reduction test at median (IQR) test age of 35 4 (34 5 –36 0 ) weeks’ postmenstrual age (PMA). Shift was derived from at least three paired SpO 2 versus P I O 2 measurements using a computer algorithm, using the fetal oxyhaemoglobin dissociation curve as the reference. Linear regression of resultant shift values enabled construction of a table to predict shift using a single paired SpO 2 versus P I O 2 measurement, validated subsequently in a separate infant cohort using Bland-Altman analysis. Receiver operating curve analysis provided threshold values equating to a clinical diagnosis of mild bronchopulmonary dysplasia (BPD) or moderate to severe BPD. Results The median (IQR) age of 63 infants in the validation cohort was 36 0 (35 6 –36 2 ) weeks’ PMA. Mean difference (95% CI) between predicted and measured shift was 2.1 (−0.8% to 4.9%) with wide limits of agreement (−20.7% to 24.8%). Predicted shift >10.1 kPa identified mild BPD with 71% sensitivity and 88% specificity while values>13.0 kPa identified moderate to severe BPD with 81% sensitivity and 100% specificity. Discussion Shift predicted from a single paired SpO 2 versus P I O 2 measurement using our validated table enables objective bedside screening of lung disease severity in very preterm infant cohorts at 36 weeks’ PMA.