Multimodal Prediction of Progression Toward Brain Death After Out-of-Hospital Cardiac Arrest

Background/Objectives: Some patients with severe hypoxic–ischemic brain injury after out-of-hospital cardiac arrest (OHCA) progress toward brain death, a trajectory not adequately captured by the conventional classification of favorable versus unfavorable neurological outcomes. We developed and internally evaluated a multimodal model combining quantitative brain computed tomography (CT), serum neuron-specific enolase (NSE) at 48 h, and clinical variables to predict operationally defined progression toward brain death (PTBD). Methods: This multicenter retrospective secondary analysis used prospectively collected data from the Korean Hypothermia Network registry. Adult comatose OHCA survivors treated with targeted temperature management between October 2015 and December 2020 were included. Multivariable logistic regression models were developed in the total cohort and in patients with poor neurological outcomes. Model performance was assessed using discrimination, calibration, the Brier score, and bootstrap internal validation. Results: Of 468 patients assessed, 376 were included; their mean age was 58.7 years, and 269 (71.5%) were male. Seventy-four patients (19.7%) met the operational definition of PTBD. In the total cohort, younger age, non-shockable rhythm, low gray-to-white matter ratio (GWR ≤ 1.19), and higher NSE at 48 h were independently associated with PTBD. Among 288 patients with poor neurological outcomes, younger age, low GWR, and higher NSE at 48 h remained independent predictors. The total-cohort model had an AUC of 0.895 and an optimism-corrected AUC of 0.890. Its AUC was higher than that of NSE at 48 h (p < 0.001) but not significantly different from that of GWR alone (p = 0.054). In the poor-outcome subgroup, the model had an AUC of 0.864 and an optimism-corrected AUC of 0.858 and significantly outperformed both GWR (p = 0.012) and NSE at 48 h (p < 0.001). Conclusions: PTBD represents a clinically distinguishable trajectory among patients with poor neurological outcomes after OHCA. A multimodal model using information available within 48 h demonstrated good internally validated performance and may support early risk stratification before definitive neuroprognostication. External validation is required before clinical implementation.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Medicine
Published
2026-07-22
DOI
https://doi.org/10.3390/jcm15145751
Primary Topic
Cardiac Arrest and Resuscitation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multimodal Prediction of Progression Toward Brain Death After Out-of-Hospital Cardiac Arrest

Hwan Song, Seung Pill Choi, Jae‐Joong Kim, Jong Ho Zhu et al.
Journal of Clinical Medicine
Cardiac Arrest and Resuscitation
article

Multimodal Prediction of Progression Toward Brain Death After Out-of-Hospital Cardiac Arrest

Hwan Song, Seung Pill Choi, Jae‐Joong Kim, Jong Ho Zhu, Mi Kyong Kwon, Ki Wook Kim, Jae Hun Oh, Hyo Joon Kim, Soo Hyun Kim
article en

Abstract

Background/Objectives: Some patients with severe hypoxic–ischemic brain injury after out-of-hospital cardiac arrest (OHCA) progress toward brain death, a trajectory not adequately captured by the conventional classification of favorable versus unfavorable neurological outcomes. We developed and internally evaluated a multimodal model combining quantitative brain computed tomography (CT), serum neuron-specific enolase (NSE) at 48 h, and clinical variables to predict operationally defined progression toward brain death (PTBD). Methods: This multicenter retrospective secondary analysis used prospectively collected data from the Korean Hypothermia Network registry. Adult comatose OHCA survivors treated with targeted temperature management between October 2015 and December 2020 were included. Multivariable logistic regression models were developed in the total cohort and in patients with poor neurological outcomes. Model performance was assessed using discrimination, calibration, the Brier score, and bootstrap internal validation. Results: Of 468 patients assessed, 376 were included; their mean age was 58.7 years, and 269 (71.5%) were male. Seventy-four patients (19.7%) met the operational definition of PTBD. In the total cohort, younger age, non-shockable rhythm, low gray-to-white matter ratio (GWR ≤ 1.19), and higher NSE at 48 h were independently associated with PTBD. Among 288 patients with poor neurological outcomes, younger age, low GWR, and higher NSE at 48 h remained independent predictors. The total-cohort model had an AUC of 0.895 and an optimism-corrected AUC of 0.890. Its AUC was higher than that of NSE at 48 h (p < 0.001) but not significantly different from that of GWR alone (p = 0.054). In the poor-outcome subgroup, the model had an AUC of 0.864 and an optimism-corrected AUC of 0.858 and significantly outperformed both GWR (p = 0.012) and NSE at 48 h (p < 0.001). Conclusions: PTBD represents a clinically distinguishable trajectory among patients with poor neurological outcomes after OHCA. A multimodal model using information available within 48 h demonstrated good internally validated performance and may support early risk stratification before definitive neuroprognostication. External validation is required before clinical implementation.

Journal of Clinical MedicineVol. 15(14)
The Catholic University of Korea St. Vincent's Hospital (KR), The Catholic University of Korea Uijeongbu St. Mary's Hospital (KR), The Catholic University of Korea Seoul St. Mary's Hospital (KR), Catholic University of Korea (KR)
Openalex Percentile: Top 6%
Cardiac Arrest and Resuscitation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.