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Updated: Apr 20, 2026
Point-of-Care Ultrasound for Peripheral Veno-Arterial Extracorporeal Membrane Oxygenation Without Left Ventricular Venting
Published on: January 17, 2025
Developing a risk prediction model for survival to discharge in cardiac arrest patients who undergo extracorporeal
Sung Bum Park1, Jeong Hoon Yang2, Taek Kyu Park3
1Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Department of Medicine, Korean Armed Forces Capital Hospital, Seongnam, South Korea.
Background:
Limited data are available on a risk model for survival to discharge after extracorporeal membrane oxygenation (ECMO)-assisted cardiopulmonary resuscitation (ECPR). We aimed to develop a risk prediction model for survival to discharge in cardiac arrest patients who undergo ECMO.
Methods:
Between January 2004 and December 2012, 505 patients supported by ECMO were enrolled in a retrospective, observational registry. Among those, we studied 152 adult patients with in-hospital cardiac arrest. The primary outcome was survival to discharge. A new predictive scoring system, named the ECPR score, was developed to monitor survival to discharge using the β coefficients of prognostic factors from the logistic model, which were internally validated.
Results:
In-hospital death occurred in 104 patients (68.4%). In multivariate logistic regression, age ≤ 66, shockable arrest rhythm, CPR to ECMO pump-on time ≤ 38 min, post-ECMO arterial pulse pressure > 24 mmHg, and post-ECMO Sequential Organ Failure Assessment score ≤ 14 were independent predictors for survival to discharge. Survival to discharge was predicted by the ECPR score with a c-statistics of 0.8595 (95% confidence interval [CI], 0.80-0.92; p<0.001) which was similar to the c-statistics obtained from internal validation (training vs. test set; c-statistics, 0.86 vs. 0.86005; 95% CI, 0.80-0.92 vs. 0.77-0.94). The sensitivity and specificity for prediction of survival to discharge were 89.6% and 75.0%, respectively, when the ECPR score was >10.
Conclusions:
The new risk prediction model might be helpful for decisions about ECPR management and could provide better information regarding early prognosis.
