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  4. Vol 7, Issue 3, 2026

Neurological Prognostication after Extracorporeal Cardiopulmonary Resuscitation: From Pathophysiology to Multimodal Integration

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DOI: 10.23977/medsc.2026.070318 | Downloads: 1 | Views: 73

Author(s)

Xinyu Tang 1, Lin Zhao 1

Affiliation(s)

1 Department of Emergency, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China

Corresponding Author

Lin Zhao

ABSTRACT

Extracorporeal cardiopulmonary resuscitation (ECPR) has emerged as a salvage strategy for refractory cardiac arrest, yet hypoxic-ischemic brain injury (HIBI) remains the predominant determinant of poor long-term outcomes. This review systematically examines the pathophysiological mechanisms of HIBI following ECPR—including primary ischemic injury and secondary reperfusion injury mediated by excitotoxicity, neuroinflammation, oxidative stress, and cerebral edema—and identifies key prognostic factors such as age, arrest location, initial rhythm, low-flow time, intracranial hemorrhage, and hemodynamic targets. We critically evaluate current assessment modalities including bedside ultrasound (TCD, ONSD), cerebral oxygenation monitoring (rSO₂, SjvO₂), electrophysiological tools (EEG, aEEG, BIS), biomarkers (NSE, S100B, NfL, GFAP, UCH-L1), and neuroimaging (CT, MRI, low-field POC-MRI). Recognizing the inherent limitations of single-modality approaches, multicenter validation is warranted to establish its clinical utility across diverse settings. Future directions include artificial intelligence-driven dynamic prediction models, validation of emerging biomarkers in ECPR-specific cohorts, and standardized international registries to advance evidence-based neuroprognostication in this challenging population.

KEYWORDS

Extracorporeal Cardiopulmonary Resuscitation; Cardiac Arrest; Hypoxic-Ischemic Brain Injury; Neurological Prognostication; Multimodal Monitoring

CITE THIS PAPER

Xinyu Tang, Lin Zhao. Neurological Prognostication after Extracorporeal Cardiopulmonary Resuscitation: From Pathophysiology to Multimodal Integration. MEDS Clinical Medicine (2026). Vol. 7, No. 3, 139-148. DOI: http://dx.doi.org/10.23977/medsc.2026.070318.

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