• Drago Plečko, Nicolas Bennett, Johan Mårtensson, Tariq A Dam, Robert Entjes, RettigThijs C DTCDDepartment of Intensive Care, Amphia Ziekenhuis, Breda, The Netherlands., Dave A Dongelmans, Age D Boelens, Sander Rigter, Stefaan H A Hendriks, Remko de Jong, Marlijn J A Kamps, Marco Peters, Attila Karakus, Diederik Gommers, Dharmanand Ramnarain, Evert-Jan Wils, Sefanja Achterberg, Ralph Nowitzky, Walter van den Tempel, de JagerCornelis P CCPCDepartment of Intensive Care, Jeroen Bosch Ziekenhuis, Den Bosch, The Netherlands., Fleur G C A Nooteboom, Evelien Oostdijk, Peter Koetsier, Alexander D Cornet, Auke C Reidinga, Wouter de Ruijter, Rob J Bosman, Tim Frenzel, Louise C Urlings-Strop, Paul de Jong, SmitEllen G MEGMIntensive Care, Spaarne Gasthuis, Haarlem en Hoofddorp, The Netherlands., Olaf L Cremer, D Jannet Mehagnoul-Schipper, Harald J Faber, Judith Lens, Gert B Brunnekreef, Barbara Festen-Spanjer, Tom Dormans, Daan P de Bruin, Robbert C A Lalisang, Sebastiaan J J Vonk, Martin E Haan, Lucas M Fleuren, Patrick J Thoral, ElbersPaul W GPWGDepartment of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands., and Rinaldo Bellomo.
• Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands.
• Acta Anaesthesiol Scand. 2022 Jan 1; 66 (1): 657565-75.

BackgroundThe prediction of in-hospital mortality for ICU patients with COVID-19 is fundamental to treatment and resource allocation. The main purpose was to develop an easily implemented score for such prediction.MethodsThis was an observational, multicenter, development, and validation study on a national critical care dataset of COVID-19 patients. A systematic literature review was performed to determine variables possibly important for COVID-19 mortality prediction. Using a logistic multivariable model with a LASSO penalty, we developed the Rapid Evaluation of Coronavirus Illness Severity (RECOILS) score and compared its performance against published scores.ResultsOur development (validation) cohort consisted of 1480 (937) adult patients from 14 (11) Dutch ICUs admitted between March 2020 and April 2021. Median age was 65 (65) years, 31% (26%) died in hospital, 74% (72%) were males, average length of ICU stay was 7.83 (10.25) days and average length of hospital stay was 15.90 (19.92) days. Age, platelets, PaO2/FiO2 ratio, pH, blood urea nitrogen, temperature, PaCO2, Glasgow Coma Scale (GCS) score measured within +/-24 h of ICU admission were used to develop the score. The AUROC of RECOILS score was 0.75 (CI 0.71-0.78) which was higher than that of any previously reported predictive scores (0.68 [CI 0.64-0.71], 0.61 [CI 0.58-0.66], 0.67 [CI 0.63-0.70], 0.70 [CI 0.67-0.74] for ISARIC 4C Mortality Score, SOFA, SAPS-III, and age, respectively).ConclusionsUsing a large dataset from multiple Dutch ICUs, we developed a predictive score for mortality of COVID-19 patients admitted to ICU, which outperformed other predictive scores reported so far.© 2021 The Authors. Acta Anaesthesiologica Scandinavica published by John Wiley & Sons Ltd on behalf of Acta Anaesthesiologica Scandinavica Foundation.

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