A Mortality Prediction Score for Patients With Veno-Venous Extracorporeal Membrane Oxygenation (VV-ECMO): The PREDICT VV-ECMO Score

Author:

Rilinger Jonathan12ORCID,Book Rebecca1,Kaier Klaus3,Giani Marco45,Fumagalli Benedetta45,Jäckel Markus12,Bemtgen Xavier1,Zotzmann Viviane1,Biever Paul M.1,Foti Giuseppe45,Westermann Dirk2,Lepper Philipp M.6,Supady Alexander16,Staudacher Dawid L.1,Wengenmayer Tobias1

Affiliation:

1. Department of Interdisciplinary Medical Intensive Care, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany

2. Department of Cardiology and Angiology, Heart Center Freiburg University, Faculty of Medicine, University of Freiburg, Freiburg, Germany

3. Institute of Medical Biometry and Statistics, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany

4. Department School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy

5. Department of Emergency and Intensive care, Azienda Socio Sanitaria Territoriale Monza, Monza, Italy

6. Department of Internal Medicine V – Pneumology, Allergology and Critical Care Medicine, Saarland University Medical Center and University of Saarland, Homburg, Germany

Abstract

Mortality prediction for patients with the severe acute respiratory distress syndrome (ARDS) supported with veno-venous extracorporeal membrane oxygenation (VV-ECMO) is challenging. Clinical variables at baseline and on day 3 after initiation of ECMO support of all patients treated from October 2010 through April 2020 were analyzed. Multivariate logistic regression analysis was used to identify score variables. Internal and external (Monza, Italy) validation was used to evaluate the predictive value of the model. Overall, 272 patients could be included for data analysis and creation of the PREDICT VV-ECMO score. The score comprises five parameters (age, lung fibrosis, immunosuppression, cumulative fluid balance, and ECMO sweep gas flow on day 3). Higher score values are associated with a higher probability of hospital death. The score showed favorable results in derivation and external validation cohorts (area under the receiver operating curve, AUC derivation cohort 0.76 [95% confidence interval, CI, 0.71–0.82] and AUC validation cohort 0.74 [95% CI, 0.67–0.82]). Four risk classes were defined: I ≤ 30, II 31–60, III 61–90, and IV ≥ 91 with a predicted mortality of 28.2%, 56.2%, 84.8%, and 96.1%, respectively. The PREDICT VV-ECMO score suggests favorable performance in predicting hospital mortality under ongoing ECMO support providing a sound basis for further evaluation in larger cohorts.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Biomedical Engineering,General Medicine,Biomaterials,Bioengineering,Biophysics

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