Author: Plecko, Drago; Bennett, Nicolas; MÃ¥rtensson, Johan; Dam, Tariq A; Entjes, Robert; Rettig, Thijs C D; Dongelmans, Dave A; Boelens, Age D; Rigter, Sander; Hendriks, Stefaan H A; de Jong, Remko; Kamps, Marlijn J A; Peters, Marco; Karakus, Attila; Gommers, Diederik; Ramnarain, Dharmanand; Wils, Evert-Jan; Achterberg, Sefanja; Nowitzky, Ralph; van den Tempel, Walter; de Jager, Cornelis P C; Nooteboom, Fleur G C A; Oostdijk, Evelien; Koetsier, Peter; Cornet, Alexander D; Reidinga, Auke C; de Ruijter, Wouter; Bosman, Rob J; Frenzel, Tim; Urlings-Strop, Louise C; de Jong, Paul; Smit, Ellen G M; Cremer, Olaf L; Mehagnoul-Schipper, D Jannet; Faber, Harald J; Lens, Judith; Brunnekreef, Gert B; Festen-Spanjer, Barbara; Dormans, Tom; de Bruin, Daan P; Lalisang, Robbert C A; Vonk, Sebastiaan J J; Haan, Martin E; Fleuren, Lucas M; Thoral, Patrick J; Elbers, Paul W G; Bellomo, Rinaldo
Title: Rapid Evaluation of Coronavirus Illness Severity (RECOILS) in intensive care: Development and validation of a prognostic tool for in-hospital mortality Cord-id: 9rhibe77 Document date: 2021_1_1
ID: 9rhibe77
Snippet: BACKGROUND: The 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. METHODS: This 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 mul
Document: BACKGROUND: The 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. METHODS: This 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. RESULTS: Our 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). CONCLUSIONS: Using 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.
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