Jeong-Am Ryu1, Chi Ryang Chung2, Yang Hyun Cho3, Kiick Sung3, Kyeongman Jeon4, Gee Young Suh4, Taek Kyu Park5, Joo Myung Lee5, Young Bin Song5, Joo-Yong Hahn5, Jin-Ho Choi5, Seung-Hyuk Choi5, Hyeon-Cheol Gwon5, Keumhee C Carriere6, Joonghyun Ahn7, Jeong Hoon Yang8. 1. Department of Critical Care Medicine, Samsung Medical Center, Seoul, Korea; Department of Neurosurgery, Samsung Medical Center, Seoul, Korea. 2. Department of Critical Care Medicine, Samsung Medical Center, Seoul, Korea. 3. Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Seoul, Korea. 4. Department of Critical Care Medicine, Samsung Medical Center, Seoul, Korea; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Seoul, Korea. 5. Division of Cardiology, Department of Medicine, Samsung Medical Center, Seoul, Korea. 6. Biostatistics and Clinical Epidemiology Center, Samsung Medical Center, Seoul, Korea; Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Canada. 7. Biostatistics and Clinical Epidemiology Center, Samsung Medical Center, Seoul, Korea. 8. Department of Critical Care Medicine, Samsung Medical Center, Seoul, Korea; Division of Cardiology, Department of Medicine, Samsung Medical Center, Seoul, Korea. Electronic address: jhysmc@gmail.com.
Abstract
BACKGROUND: This study aimed to develop a risk prediction model for neurologic outcomes in patients who underwent extracorporeal cardiopulmonary resuscitation (ECPR). METHODS: Between May 2004 and April 2016, a total of 274 patients who underwent ECPR were included in this analysis. The primary outcome was neurologic status on discharge from the hospital, as assessed by Cerebral Performance Categories (CPC) scale. To develop a new predictive scoring system, backward stepwise elimination and a z-score-based scoring scheme were used on the basis of logistic regression analyses. RESULTS: A total of 95 patients (34.7%) survived until discharge. Of these, 78 patients (28.5%) had favorable neurologic outcomes (CPC scores of 1 or 2). In the multivariable logistic regression analysis, significant predictors of poor neurologic outcome included age older than 65 years, initial Sequential Organ Failure Assessment score greater than 13 points, first monitored arrest rhythm, low-flow time longer than 30 minutes, initial pulse pressure less than 25 mm Hg, initial mean arterial pressure less than 70 mm Hg, and serum glucose level greater than 300 mg/dL. There was also a significant interaction between age and low-flow time. The newly developed neurologic outcome score after ECPR (nECPR) more effectively predicted poor neurologic outcome (C-statistic, 0.867; 95% confidence interval, 0.823 to 0.912) than the former ECPR score (p = 0.019) and the survival after venoarterial ECMO score (p < 0.001). CONCLUSIONS: The investigators created a risk prediction model for neurologic outcomes using independent predictors and the interaction between age and low-flow time, and this new scoring system could predict early neurologic prognosis more effectively in ECPR-treated patients. It may be help guide decisions in ECPR management for intensivists, cardiovascular surgeons, or cardiologists.
BACKGROUND: This study aimed to develop a risk prediction model for neurologic outcomes in patients who underwent extracorporeal cardiopulmonary resuscitation (ECPR). METHODS: Between May 2004 and April 2016, a total of 274 patients who underwent ECPR were included in this analysis. The primary outcome was neurologic status on discharge from the hospital, as assessed by Cerebral Performance Categories (CPC) scale. To develop a new predictive scoring system, backward stepwise elimination and a z-score-based scoring scheme were used on the basis of logistic regression analyses. RESULTS: A total of 95 patients (34.7%) survived until discharge. Of these, 78 patients (28.5%) had favorable neurologic outcomes (CPC scores of 1 or 2). In the multivariable logistic regression analysis, significant predictors of poor neurologic outcome included age older than 65 years, initial Sequential Organ Failure Assessment score greater than 13 points, first monitored arrest rhythm, low-flow time longer than 30 minutes, initial pulse pressure less than 25 mm Hg, initial mean arterial pressure less than 70 mm Hg, and serum glucose level greater than 300 mg/dL. There was also a significant interaction between age and low-flow time. The newly developed neurologic outcome score after ECPR (nECPR) more effectively predicted poor neurologic outcome (C-statistic, 0.867; 95% confidence interval, 0.823 to 0.912) than the former ECPR score (p = 0.019) and the survival after venoarterial ECMO score (p < 0.001). CONCLUSIONS: The investigators created a risk prediction model for neurologic outcomes using independent predictors and the interaction between age and low-flow time, and this new scoring system could predict early neurologic prognosis more effectively in ECPR-treated patients. It may be help guide decisions in ECPR management for intensivists, cardiovascular surgeons, or cardiologists.
Authors: Emily E Naoum; Andrew Chalupka; Jonathan Haft; Mark MacEachern; Cosmas J M Vandeven; Sarah Rae Easter; Michael Maile; Brian T Bateman; Melissa E Bauer Journal: J Am Heart Assoc Date: 2020-06-24 Impact factor: 5.501
Authors: Jonathan Rilinger; Antonia M Riefler; Xavier Bemtgen; Markus Jäckel; Viviane Zotzmann; Paul M Biever; Daniel Duerschmied; Christoph Benk; Georg Trummer; Klaus Kaier; Christoph Bode; Dawid L Staudacher; Tobias Wengenmayer Journal: Clin Res Cardiol Date: 2021-03-29 Impact factor: 5.460
Authors: Richard T Carrick; Jinny G Park; Hannah L McGinnes; Christine Lundquist; Kristen D Brown; W Adam Janes; Benjamin S Wessler; David M Kent Journal: J Am Heart Assoc Date: 2020-08-13 Impact factor: 5.501