The Prediction of Early Neurological Outcomes in Out-of-Hospital Cardiac Arrest Patients: A Multicenter Prospective...

Background/Objectives: Early neuroprognostication after cardiac arrest is essential for guiding treatment strategies and providing accurate prognostic information to families. While several early risk scores have been proposed, few have incorporated a wide range of variables in large cohorts. This study aimed to develop and validate a novel prognostic model, the KORHN risk score, and to compare its performance with established tools including MIRACLE, TTM, CAHP, C-GRApH, and OHCA scores; Methods: We conducted a prospective multicenter observational study using data from the KORean Hypothermia Network registry. Risk variables identified in previous studies, along with extensive data from 1371 patients in the KORHN registry, were analyzed. The primary endpoint was poor neurological outcome at 6 months; Results: Key predictors included low-flow time, diastolic shock index, cardiac etiology, bilateral absence of pupil reflex, shockable initial rhythm, Glasgow Coma Scale motor response, epinephrine use, and age. Compared with established risk scores, the KORHN score demonstrated superior performance (AUC 0.925 vs. 0.827-0.902 with all variables, and AUC 0.914 vs. 0.85-0.903 with the top five variables with identical cut-off). External validation in a non-KORHN cohort (AUC 0.890) confirmed its robustness; Conclusions: The KORHN score provides a simple, accurate tool for early neuroprognostication, supporting clinical decision-making and family communication.