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Rapid Evaluation of Coronavirus Illness Severity (RECOILS) in intensive care: Development and validation of a prognostic tool for in-hospital mortality.
Plecko, Drago; Bennett, Nicolas; Mårtensson, 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.
  • Plecko D; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands.
  • Bennett N; Department of Mathematics, Seminar for Statistics, ETH Zürich, Zurich, Switzerland.
  • Mårtensson J; Department of Mathematics, Seminar for Statistics, ETH Zürich, Zurich, Switzerland.
  • Dam TA; Department of Physiology and Pharmacology, Section of Anaesthesia and Intensive Care, Karolinska Institutet, Stockholm, Sweden.
  • Entjes R; Department of Perioperative Medicine and Intensive Care, Karolinska University Hospital, Stockholm, Sweden.
  • Rettig TCD; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands.
  • Dongelmans DA; Department of Intensive Care, Admiraal De Ruyter Ziekenhuis, Goes, The Netherlands.
  • Boelens AD; Department of Intensive Care, Amphia Ziekenhuis, Breda, The Netherlands.
  • Rigter S; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands.
  • Hendriks SHA; Antonius Ziekenhuis Sneek, Sneek, The Netherlands.
  • de Jong R; Department of Anesthesiology and Intensive Care, St. Antonius Hospital, Nieuwegein, The Netherlands.
  • Kamps MJA; Intensive Care, Albert Schweitzerziekenhuis, Dordrecht, The Netherlands.
  • Peters M; Intensive Care, Bovenij Ziekenhuis, Amsterdam, The Netherlands.
  • Karakus A; Intensive Care, Catharina Ziekenhuis Eindhoven, Eindhoven, The Netherlands.
  • Gommers D; Intensive Care, Canisius Wilhelmina Ziekenhuis, Nijmegen, The Netherlands.
  • Ramnarain D; Department of Intensive Care, Diakonessenhuis Hospital, Utrecht, The Netherlands.
  • Wils EJ; Department of Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands.
  • Achterberg S; Intensive Care, ETZ Tilburg, Tilburg, The Netherlands.
  • Nowitzky R; Department of Intensive Care, Franciscus Gasthuis & Vlietland, Rotterdam, The Netherlands.
  • van den Tempel W; ICU, Haaglanden Medisch Centrum, Den Haag, The Netherlands.
  • de Jager CPC; Intensive Care, HagaZiekenhuis, Den Haag, The Netherlands.
  • Nooteboom FGCA; Department of Intensive Care, Ikazia Ziekenhuis Rotterdam, Rotterdam, The Netherlands.
  • Oostdijk E; Department of Intensive Care, Jeroen Bosch Ziekenhuis, Den Bosch, The Netherlands.
  • Koetsier P; Intensive Care, Laurentius Ziekenhuis, Roermond, The Netherlands.
  • Cornet AD; ICU, Maasstad Ziekenhuis Rotterdam, Rotterdam, The Netherlands.
  • Reidinga AC; Intensive Care, Medisch Centrum Leeuwarden, Leeuwarden, The Netherlands.
  • de Ruijter W; Department of Intensive Care, Medisch Spectrum Twente, Enschede, The Netherlands.
  • Bosman RJ; ICU, SEH, BWC, Martiniziekenhuis, Groningen, The Netherlands.
  • Frenzel T; Department of Intensive Care Medicine, Northwest Clinics, Alkmaar, The Netherlands.
  • Urlings-Strop LC; ICU, OLVG, Amsterdam, The Netherlands.
  • de Jong P; Department of Intensive Care Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Smit EGM; Intensive Care, Reinier de Graaf Gasthuis, Delft, The Netherlands.
  • Cremer OL; Department of Anesthesia and Intensive Care, Slingeland Ziekenhuis, Doetinchem, The Netherlands.
  • Mehagnoul-Schipper DJ; Intensive Care, Spaarne Gasthuis, Haarlem en Hoofddorp, The Netherlands.
  • Faber HJ; Intensive Care, UMC Utrecht, Utrecht, The Netherlands.
  • Lens J; Intensive Care, VieCuri Medisch Centrum, Venlo, The Netherlands.
  • Brunnekreef GB; ICU, WZA, Assen, The Netherlands.
  • Festen-Spanjer B; ICU, ICU, IJsselland Ziekenhuis, Capelle aan den IJssel, The Netherlands.
  • Dormans T; Department of Intensive Care, Ziekenhuisgroep Twente, Almelo, The Netherlands.
  • de Bruin DP; Intensive Care, Ziekenhuis Gelderse Vallei, Ede, The Netherlands.
  • Lalisang RCA; Intensive care, Zuyderland MC, Heerlen, The Netherlands.
  • Vonk SJJ; Pacmed, Amsterdam, Amsterdam, The Netherlands.
  • Haan ME; Pacmed, Amsterdam, Amsterdam, The Netherlands.
  • Fleuren LM; Pacmed, Amsterdam, 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; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Amsterdam, The Netherlands.
Acta Anaesthesiol Scand ; 66(1): 65-75, 2022 01.
Article in English | MEDLINE | ID: covidwho-1462715
ABSTRACT

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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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Limits: Adult / Aged / Humans / Male Language: English Journal: Acta Anaesthesiol Scand Year: 2022 Document Type: Article Affiliation country: Aas.13991

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Limits: Adult / Aged / Humans / Male Language: English Journal: Acta Anaesthesiol Scand Year: 2022 Document Type: Article Affiliation country: Aas.13991