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.

Prognostic model development and internal validation study.

Single-center study.

All 120 normothermic ECPR patients treated at Sahlgrenska University Hospital between January 2010 and October 2021.

None.

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.

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.