Yasser B Abulhasan1, Najayeb Alabdulraheem2, Gabrielle Simoneau3, Mark R Angle4, Jeanne Teitelbaum4. 1. Neurological Intensive Care Unit, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada; Faculty of Medicine, Health Sciences Center, Kuwait University, Kuwait. Electronic address: yasser.abulhasan@hsc.edu.kw. 2. Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada. 3. Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada. 4. Neurological Intensive Care Unit, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.
Abstract
OBJECTIVE: To evaluate primary causes of death after spontaneous subarachnoid hemorrhage (SAH) and externally validate the HAIR score, a prognostication tool, in a single academic institution. METHODS: We reviewed all patients with SAH admitted to our neuro-intensive care unit between 2010 and 2016. Univariate and multivariate logistic regressions were performed to identify predictors of in-hospital mortality. The HAIR score predictors were Hunt and Hess grade at treatment decision, age, intraventricular hemorrhage, and rebleeding within 24 hours. Validation of the HAIR score was characterized with the receiver operating curve, the area under the curve, and a calibration plot. RESULTS: Among 434 patients with SAH, in-hospital mortality was 14.1%. Of the 61 mortalities, 54 (88.5%) had a neurologic cause of death or withdrawal of care and 7 (11.5%) had cardiac death. Median time from SAH to death was 6 days. The main causes of death were effect of the initial hemorrhage (26.2%), rebleeding (23%) and refractory cerebral edema (19.7%). Factors significantly associated with in-hospital mortality in the multivariate analysis were age, Hunt and Hess grade, and intracerebral hemorrhage. Maximum lumen size was also a significant risk factor after aneurysmal SAH. The HAIR score had a satisfactory discriminative ability, with an area under the curve of 0.89. CONCLUSIONS: The in-hospital mortality is lower than in previous reports, attesting to the continuing improvement of our institutional SAH care. The major causes are the same as in previous reports. Despite a different therapeutic protocol, the HAIR score showed good discrimination and could be a useful tool for predicting mortality.
OBJECTIVE: To evaluate primary causes of death after spontaneous subarachnoid hemorrhage (SAH) and externally validate the HAIR score, a prognostication tool, in a single academic institution. METHODS: We reviewed all patients with SAH admitted to our neuro-intensive care unit between 2010 and 2016. Univariate and multivariate logistic regressions were performed to identify predictors of in-hospital mortality. The HAIR score predictors were Hunt and Hess grade at treatment decision, age, intraventricular hemorrhage, and rebleeding within 24 hours. Validation of the HAIR score was characterized with the receiver operating curve, the area under the curve, and a calibration plot. RESULTS: Among 434 patients with SAH, in-hospital mortality was 14.1%. Of the 61 mortalities, 54 (88.5%) had a neurologic cause of death or withdrawal of care and 7 (11.5%) had cardiac death. Median time from SAH to death was 6 days. The main causes of death were effect of the initial hemorrhage (26.2%), rebleeding (23%) and refractory cerebral edema (19.7%). Factors significantly associated with in-hospital mortality in the multivariate analysis were age, Hunt and Hess grade, and intracerebral hemorrhage. Maximum lumen size was also a significant risk factor after aneurysmalSAH. The HAIR score had a satisfactory discriminative ability, with an area under the curve of 0.89. CONCLUSIONS: The in-hospital mortality is lower than in previous reports, attesting to the continuing improvement of our institutional SAH care. The major causes are the same as in previous reports. Despite a different therapeutic protocol, the HAIR score showed good discrimination and could be a useful tool for predicting mortality.
Authors: Agnes T Stauning; Frank Eriksson; Goetz Benndorf; Anders V Holst; John Hauerberg; Trine Stavngaard; Lars Poulsgaard; Per Rochat; Vagn Eskesen; Peter Birkeland; Tiit Mathiesen; Tina N Munch Journal: Acta Neurochir (Wien) Date: 2022-07-22 Impact factor: 2.816
Authors: Chinh Quoc Luong; Hung Manh Ngo; Hai Bui Hoang; Dung Thi Pham; Tuan Anh Nguyen; Tuan Anh Tran; Duong Ngoc Nguyen; Son Ngoc Do; My Ha Nguyen; Hung Dinh Vu; Hien Thi Thu Vuong; Ton Duy Mai; Anh Quang Nguyen; Kien Hoang Le; Phuong Viet Dao; Thong Huu Tran; Luu Dang Vu; Linh Quoc Nguyen; Trang Quynh Pham; He Van Dong; Hao The Nguyen; Chi Van Nguyen; Anh Dat Nguyen Journal: PLoS One Date: 2021-08-13 Impact factor: 3.240