Clinical, imaging, and serum biomarker predictors of malignant cerebral infarction

Malignant cerebral infarction (MCI) is rare but often fatal. Early identification helps guide monitoring and decompressive surgery. This study evaluated whether serum biomarkers add predictive value beyond clinical and imaging data in severe stroke patients with anterior circulation large vessel occ...

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Detalles Bibliográficos
Autores: Rodríguez Vázquez, Alejandro, Rudilosso, Salvatore, Doncel Moriano, Antonio, Cabero Arnold, Andrea, Laredo Gregorio, Carlos, Ramis, Darío, Moraleja, David, Serrano Clerencia, Mònica, Gonzalez Romero, Yolanda, Renú, Arturo, Bartolomé Arenas, Inés, Rosa Batlle, Irene, Dolz Alvarez de la Ballina, Guillem, Torné, Ramón, Vargas, Martha, Urra, Xabier, Chamorro Sánchez, Ángel
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/225013
Acceso en línea:https://hdl.handle.net/2445/225013
Access Level:acceso abierto
Palabra clave:Infart cerebral
Marcadors bioquímics
Cerebral infarctio
Biochemical markers
Descripción
Sumario:Malignant cerebral infarction (MCI) is rare but often fatal. Early identification helps guide monitoring and decompressive surgery. This study evaluated whether serum biomarkers add predictive value beyond clinical and imaging data in severe stroke patients with anterior circulation large vessel occlusion (LVO). In this prospective study, 73 acute severe LVO stroke patients underwent whole-brain CT perfusion (CTP) with rCBV-based core measurement at admission and follow-up MRI at 24 ± 12 h for infarct and edema volume assessment. Serum biomarkers (s100b, NSE, VEGF, ICAM1) were sampled a median of 20.5 h after baseline imaging. Logistic regression models predicted MCI using baseline variables (NIHSS, ASPECTS, rCBV < 30%), adding treatment data (rtPA, mTICI, NIHSS posttreatment), and adding serum biomarkers. Performance was assessed by AUC, accuracy, F1, and cross-validated R2. MCI occurred in 18/73 (24%) patients. Baseline models showed an AUC of 0.72; adding treatment improved the AUC to 0.88. Biomarkers slightly increased the AUC (0.90) but did not improve F1. Higher s100b was associated with more severe injury but did not enhance the prediction of MCI. Models with baseline imaging and treatment best explained infarct (R2 ≈ 0.27) and edema (R2 ≈ 0.58). In conclusion, admission severity, CTP, and early treatment response are the main predictors of MCI and aid early risk stratification of patients. Despite their pathophysiologic relevance, serum biomarkers do not add substantial predictive value.

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