The role of early cerebral edema and hematoma assessment in aneurysmal subarachnoid hemorrhage (a-SAH) in predicting early brain injury (EBI) and cognitive impairment: a case controlled study

• Published in: International journal of surgery (London, England) Vol. 110; no. 6; pp. 3166 - 3177
• Main Authors: Wang, Ming-Dong, Fu, Qian-Hui, Ni, Andrew, Yuan, Yun-Peng, Li, Chun-Hui, Wang, Zhan-Xiang, Wang, Hong
• Format: Journal Article
• Language: English
• Published: United States Lippincott Williams & Wilkins 01.06.2024
• Subjects: Adult; Aged; Brain Edema - diagnostic imaging; Brain Edema - etiology; Brain Injuries - complications; Brain Injuries - diagnostic imaging; Case-Control Studies; Cognitive Dysfunction - diagnosis; Cognitive Dysfunction - diagnostic imaging; Cognitive Dysfunction - etiology; Female; Hematoma - diagnostic imaging; Hematoma - etiology; Humans; Magnetic Resonance Imaging; Male; Middle Aged; Original Research; Subarachnoid Hemorrhage - complications; Subarachnoid Hemorrhage - diagnostic imaging; Tomography, X-Ray Computed
• ISSN: 1743-9159; 1743-9191; 1743-9159
• DOI: 10.1097/JS9.0000000000001244

Early assessment and management of cerebral edema and hematoma following aneurysmal subarachnoid hemorrhage (a-SAH) can significantly impact clinical cognitive outcomes. However, current clinical practices lack predictive models to identify early structural brain abnormalities affecting cognition. To address this gap, the authors propose the development of a predictive model termed the a-SAH Early Brain Edema/Hematoma Compression Neural (Structural Brain) Networks Score System (SEBE-HCNNSS). In this study, 202 consecutive patients with spontaneous a-SAH underwent initial computed tomography (CT) or MRI scans within 24 h of ictus with follow-up 2 months after discharge. Using logistic regression analysis (univariate and multivariate), the authors evaluated the association of clinically relevant factors and various traditional scale ratings with cognitive impairment (CI). Risk factors with the highest area under the curve (AUC) values were included in the multivariate analysis and least absolute shrinkage and selection operator (LASSO) analysis or Cox regression analysis. A total of 177 patients were enrolled in the study, and 43 patients were classified with a high SEBE-HCNNSS grade (3-5). After a mean follow-up of 2 months, 121 individuals (68.36%) with a-SAH and three control subjects developed incident CI. The CT interobserver reliability of the SEBE-HCNNSS scale was high, with a Kappa value of 1. Furthermore, ROC analysis identified the SEBE-HCNNSS scale (OR 3.322, 95% CI: 2.312-7.237, P =0.00025) as an independent predictor of edema, CI, and unfavorable prognosis. These results were also replicated in a validation cohort. Overall, the SEBE-HCNNSS scale represents a simple assessment tool with promising predictive value for CI and clinical outcomes post-a-SAH. Our findings indicate its practical utility as a prognostic instrument for risk evaluation after a-SAH, potentially facilitating early intervention and treatment.