Objectives: Extracorporeal cardiopulmonary resuscitation (ECPR) can save patients with refractory cardiac arrest; however, according to recent meta-analyses, only 20% of patients achieve favorable outcomes (Modified Rankin Scale 0-3). We aimed to develop and validate an ECPR prediction model to improve patient selection.
Design: Prognostic model development and internal validation study.
Setting: Single-center study.
Participants: All 120 normothermic ECPR patients treated at Sahlgrenska University Hospital between January 2010 and October 2021.
Interventions: None.
Measurements and main results: Multivariable logistic regression was used to develop the PRognostic Evaluation of ECPR (Pre-ECPR) score. Model performance was assessed through the area under curve (AUC) and compared with the Extracorporeal Life Support Organization (ELSO) "Example of selection criteria for ECPR" for 1-year survival with favorable outcomes. The positive predictive value (PPV) was calculated. Favorable outcomes occurred in 27.5% of the patients. The Pre-ECPR score, incorporating age, no-flow/initial rhythm (a composite variable), total cardiac arrest time, signs of life, pupil dilation, regional cerebral oxygen saturation, arterial pH, and end-tidal CO2, demonstrated an AUC of 0.87 (95% confidence interval [CI] 0.77-0.93). In internal cross-validation, the AUC of 0.79 (95% CI 0.67-0.88) significantly outperformed the ELSO criteria AUC of 0.63 (95% CI 0.54-0.72, p = 0.012). Pre-ECPR score probabilities >6.4% showed 100% sensitivity and a PPV of 40.5% for favorable outcomes.
Conclusions: The Pre-ECPR score combines multiple weighted predictors to provide a single balanced probability of favorable outcomes in ECPR patient selection. In cross-validation, it demonstrated significantly more favorable discriminatory performance than that of the ELSO criteria.
Keywords: cardiac arrest; cardiopulmonary resuscitation; decision support system, clinical; extracorporeal membrane oxygenation; hypoxia, brain; predictive value of tests.
Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.