Sung Bum Park1, Jeong Hoon Yang2, Taek Kyu Park3, Yang Hyun Cho4, Kiick Sung4, Chi Ryang Chung5, Chi Min Park5, Kyeongman Jeon6, Young Bin Song3, Joo-Yong Hahn3, Jin-Ho Choi3, Seung-Hyuk Choi3, Hyeon-Cheol Gwon3, Gee Young Suh6. 1. Department 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. 2. Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Division of Cardiology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, South Korea. Electronic address: jhysmc@gmail.com. 3. Division of Cardiology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, South Korea. 4. Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea. 5. Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea. 6. Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Abstract
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.
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 arrestpatients 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.
Authors: Christian Jung; Kyra Janssen; Mirko Kaluza; Georg Fuernau; Tudor Constantin Poerner; Michael Fritzenwanger; Ruediger Pfeifer; Holger Thiele; Hans Reiner Figulla Journal: Clin Res Cardiol Date: 2015-08-25 Impact factor: 5.460
Authors: Jeong-Am Ryu; Taek Kyu Park; Chi Ryang Chung; Yang Hyun Cho; Kiick Sung; Gee Young Suh; Tae Rim Lee; Min Seob Sim; Jeong Hoon Yang Journal: PLoS One Date: 2017-01-23 Impact factor: 3.240
Authors: Eunmi Gil; Soo Jin Na; Jeong-Am Ryu; Dae-Sang Lee; Chi Ryang Chung; Yang Hyun Cho; Kyeongman Jeon; Kiick Sung; Gee Young Suh; Jeong Hoon Yang Journal: PLoS One Date: 2017-04-19 Impact factor: 3.240
Authors: Clément Delmas; Jean-Marie Conil; Simon Sztajnic; Bernard Georges; Caroline Biendel; Camille Dambrin; Michel Galinier; Vincent Minville; Olivier Fourcade; Stein Silva; Bertrand Marcheix Journal: Indian J Crit Care Med Date: 2017-03