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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
Author(s) -
Plečko 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.,
Jong Remko,
Kamps Marlijn J. A.,
Peters Marco,
Karakus Attila,
Gommers Diederik,
Ramnarain Dharmanand,
Wils EvertJan,
Achterberg Sefanja,
Nowitzky Ralph,
Tempel Walter,
Jager Cornelis P. C.,
Nooteboom Fleur G. C. A.,
Oostdijk Evelien,
Koetsier Peter,
Cornet Alexander D.,
Reidinga Auke C.,
Ruijter Wouter,
Bosman Rob J.,
Frenzel Tim,
UrlingsStrop Louise C.,
Jong Paul,
Smit Ellen G.M.,
Cremer Olaf L.,
MehagnoulSchipper D. Jannet,
Faber Harald J.,
Lens Judith,
Brunnekreef Gert B.,
FestenSpanjer Barbara,
Dormans Tom,
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
Publication year - 2022
Publication title -
acta anaesthesiologica scandinavica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.738
H-Index - 107
eISSN - 1399-6576
pISSN - 0001-5172
DOI - 10.1111/aas.13991
Subject(s) - medicine , glasgow coma scale , logistic regression , intensive care , observational study , severity of illness , sofa score , renal replacement therapy , emergency medicine , saps ii , covid-19 , apache ii , intensive care medicine , intensive care unit , surgery , disease , infectious disease (medical specialty)
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.