Rapid Evaluation of Coronavirus Illness Severity (RECOILS) in intensive care: Development and validation of a prognostic tool for in-hospital mortality.

Autor: Plečko D; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands.; Department of Mathematics, Seminar for Statistics, ETH Zürich, Zurich, Switzerland., Bennett N; Department of Mathematics, Seminar for Statistics, ETH Zürich, Zurich, Switzerland., Mårtensson J; Department of Physiology and Pharmacology, Section of Anaesthesia and Intensive Care, Karolinska Institutet, Stockholm, Sweden.; Department of Perioperative Medicine and Intensive Care, Karolinska University Hospital, Stockholm, Sweden., Dam TA; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands., Entjes R; Department of Intensive Care, Admiraal De Ruyter Ziekenhuis, Goes, The Netherlands., Rettig TCD; Department of Intensive Care, Amphia Ziekenhuis, Breda, The Netherlands., Dongelmans DA; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands., Boelens AD; Antonius Ziekenhuis Sneek, Sneek, The Netherlands., Rigter S; Department of Anesthesiology and Intensive Care, St. Antonius Hospital, Nieuwegein, The Netherlands., Hendriks SHA; Intensive Care, Albert Schweitzerziekenhuis, Dordrecht, The Netherlands., de Jong R; Intensive Care, Bovenij Ziekenhuis, Amsterdam, The Netherlands., Kamps MJA; Intensive Care, Catharina Ziekenhuis Eindhoven, Eindhoven, The Netherlands., Peters M; Intensive Care, Canisius Wilhelmina Ziekenhuis, Nijmegen, The Netherlands., Karakus A; Department of Intensive Care, Diakonessenhuis Hospital, Utrecht, The Netherlands., Gommers D; Department of Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands., Ramnarain D; Intensive Care, ETZ Tilburg, Tilburg, The Netherlands., Wils EJ; Department of Intensive Care, Franciscus Gasthuis & Vlietland, Rotterdam, The Netherlands., Achterberg S; ICU, Haaglanden Medisch Centrum, Den Haag, The Netherlands., Nowitzky R; Intensive Care, HagaZiekenhuis, Den Haag, The Netherlands., van den Tempel W; Department of Intensive Care, Ikazia Ziekenhuis Rotterdam, Rotterdam, The Netherlands., de Jager CPC; Department of Intensive Care, Jeroen Bosch Ziekenhuis, Den Bosch, The Netherlands., Nooteboom FGCA; Intensive Care, Laurentius Ziekenhuis, Roermond, The Netherlands., Oostdijk E; ICU, Maasstad Ziekenhuis Rotterdam, Rotterdam, The Netherlands., Koetsier P; Intensive Care, Medisch Centrum Leeuwarden, Leeuwarden, The Netherlands., Cornet AD; Department of Intensive Care, Medisch Spectrum Twente, Enschede, The Netherlands., Reidinga AC; ICU, SEH, BWC, Martiniziekenhuis, Groningen, The Netherlands., de Ruijter W; Department of Intensive Care Medicine, Northwest Clinics, Alkmaar, The Netherlands., Bosman RJ; ICU, OLVG, Amsterdam, The Netherlands., Frenzel T; Department of Intensive Care Medicine, Radboud University Medical Center, Nijmegen, The Netherlands., Urlings-Strop LC; Intensive Care, Reinier de Graaf Gasthuis, Delft, The Netherlands., de Jong P; Department of Anesthesia and Intensive Care, Slingeland Ziekenhuis, Doetinchem, The Netherlands., Smit EGM; Intensive Care, Spaarne Gasthuis, Haarlem en Hoofddorp, The Netherlands., Cremer OL; Intensive Care, UMC Utrecht, Utrecht, The Netherlands., Mehagnoul-Schipper DJ; Intensive Care, VieCuri Medisch Centrum, Venlo, The Netherlands., Faber HJ; ICU, WZA, Assen, The Netherlands., Lens J; ICU, ICU, IJsselland Ziekenhuis, Capelle aan den IJssel, The Netherlands., Brunnekreef GB; Department of Intensive Care, Ziekenhuisgroep Twente, Almelo, The Netherlands., Festen-Spanjer B; Intensive Care, Ziekenhuis Gelderse Vallei, Ede, The Netherlands., Dormans T; Intensive care, Zuyderland MC, Heerlen, The Netherlands., de Bruin DP; Pacmed, Amsterdam, Amsterdam, The Netherlands., Lalisang RCA; Pacmed, Amsterdam, Amsterdam, The Netherlands., Vonk SJJ; Pacmed, Amsterdam, Amsterdam, The Netherlands., Haan ME; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands., Fleuren LM; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands., Thoral PJ; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands., Elbers PWG; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands., Bellomo R; Australian and New Zealand Intensive Care Research Centre, School of Public Health and Preventative Medicine, Monash University, Melbourne, Australia.; Department of Critical Care, The University of Melbourne, Melbourne, Australia.; Data Analytics Research and Evaluation Centre, Department of Medicine and Radiology, The University of Melbourne.; Austin Hospital, Melbourne, Australia.
Jazyk: angličtina
Zdroj: Acta anaesthesiologica Scandinavica [Acta Anaesthesiol Scand] 2022 Jan; Vol. 66 (1), pp. 65-75. Date of Electronic Publication: 2021 Oct 15.
DOI: 10.1111/aas.13991
Abstrakt: 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.
(© 2021 The Authors. Acta Anaesthesiologica Scandinavica published by John Wiley & Sons Ltd on behalf of Acta Anaesthesiologica Scandinavica Foundation.)
Databáze: MEDLINE
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