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

Abstract

IntroductionRisk 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.MethodsMultivariate 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).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 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%).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 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.

Remote management of covid-19 using home pulse oximetry and virtual ward support

“…Many patients hospitalised with acute covid-19 have severe hypoxia 478. Hypoxia, silent hypoxia, and the need for supplementary oxygen are all independent predictors of worse outcomes in covid-19 8910111213141516. Novel prognostic tools such as the 4C score have shown the importance of identifying hypoxia early,917 and there are physiological reasons for managing the complication promptly and actively 118…”

“…16 is based on a hospital assessed cohort -QCovid36 does not incorporate acute variables so will underestimate severity in sick patients who lack known risk factors -NEWS237 is not covid-19 specific and the score may change only at a late stage of deterioration…”

Evaluation of the ROX index in SARS-CoV-2 Acute Respiratory failure treated with both High-Flow Nasal Oxygen (HFNO) and Continuous Positive Airway Pressure (CPAP)

“…Comorbidities including stroke, dementia, chronic kidney disease were not different between the arms or with different outcomes (see table 1). Inflammatory markers including leucocytosis and lymphopenia, selected as relevant in multivariate assessment of risk in COVID 19 28 were not different at baseline or between therapy outcomes: 7/35 (20%) HFNO patients and 10/95 (10.5%) CPAP patients had a raised WCC and 8/35 HFNO (22%) and 20/95 CPAP patients (21%) had a low lymphocyte count. Radiological severity assessed by CXR zonal scores were a median of 2.5/6 in HFNO failure and 4/6 in CPAP failure, p=0.87 (ns).…”

“…This was part of a National Health Service Health Research Authority (20/HRA/2344; ethics reference: 283888) approved study which included patient and public participation in the observational design. Baseline clinical characteristics and investigation results were collected according to a pre-specified protocol 28 .…”

COVID-19 Rapid Guideline - Organisation and Management in Low Resource Countries

“…Crucially and uniquely, the published early prognostication tool 'SOARS' (a clinical score based on 5 markers: Stroke, Obesity, Age, Respiratory rate and Saturations) supports decision making at hospitals' entry point. 28 When used together with 'virtual hospitals' and home-based monitoring, this tool effectively and safely streams patients into community-based care and should be a consideration where beds, ventilators, oxygen and drugs are in short supply. 29 Additional benefits of this approach included reassuringly low mortality rates (in the home-cared group) and very low re-admission rates in comparison to patients discharged without this additional support.…”