Predicting survival after extracorporeal membrane oxygenation for severe acute respiratory failure. The Respiratory Extracorporeal Membrane Oxygenation Survival Prediction (RESP) score

Matthieu Schmidt, Michael John Bailey, Jayne Sheldrake, Carol Lynette Hodgson, Cecile Aubron, Peter T Rycus, Carlos Scheinkestel, David James Cooper, Daniel Brodie, Vincent Pellegrino, Alain Combes, David V Pilcher

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Rationale: Increasing use of extracorporeal membrane oxygenation (ECMO) for acute respiratory failure may increase resource requirements and hospital costs. Better prediction of survival in these patients may improve resource utilisation, allow risk-adjusted comparison of center-specific outcomes and help clinicians to target patients most likely to benefit from ECMO. Objectives: To create a model for predicting hospital survival at initiation of ECMO for respiratory failure. Methods: Adult patients with severe acute respiratory failure treated by ECMO from 2000 to 2012 were extracted from the Extracorporeal Life Support Organization (ELSO) international registry. Multivariable logistic regression was used to create the Respiratory ECMO Survival Prediction score (RESP-score) using bootstrapping methodology with internal and external validation. Main results: Of the 2355 patients included in the study, 1338 patients (57 ) were discharged alive from hospital. The RESP-score was developed using pre-ECMO variables independently associated with hospital survival on logistic regression which included: age, immunocompromised status, duration of mechanical ventilation prior to ECMO, diagnosis, central nervous system dysfunction, acute associated non-pulmonary infection, neuro-muscular blockade agents or nitric oxide use, bicarbonate infusion, cardiac arrest, PaCO2 and peak inspiratory pressure. The ROC curve analysis of the RESP score was c=0.74, 95 Confidence Interval (0.72 ? 0.76). External validation, performed on 140 patients, exhibited excellent discrimination (c=0.92 [95 CI 0.89 ? 0.97]). Conclusions: The RESP-score is a relevant and validated tool to predict survival for patients receiving ECMO for respiratory failure. Read More: rfr_dat=cr_pub 3dpubmed .U36zm51--70
Original languageEnglish
Pages (from-to)1374 - 1382
Number of pages9
JournalAmerican Journal of Respiratory and Critical Care Medicine
Issue number11
Publication statusPublished - 2014

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