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Updated: Jan 24, 2026

A Murine Model of Subarachnoid Hemorrhage
Published on: November 21, 2013
Common Data Element for Unruptured Intracranial Aneurysm and Subarachnoid Hemorrhage: Recommendations from
Rahul Damani1, Stephan Mayer2, Raj Dhar3
1Department of Neurology, Baylor College of Medicine, Houston, TX, USA.
Background:
Clinical studies of subarachnoid hemorrhage (SAH) and unruptured cerebral aneurysms lack uniformity in terms of variables used for assessments and clinical examination of patients which has led to difficulty in comparing studies and performing meta-analyses. The overall goal of the National Institute of Health/National Institute of Neurological Disorders and Stroke Unruptured Intracranial Aneurysms (UIA) and subarachnoid hemorrhage (SAH) Common Data Elements (CDE) Project was to provide common definitions and terminology for future unruptured intracranial aneurysm and SAH research.
Methods:
This paper summarizes the recommendations of the subcommittee on SAH Assessments and Clinical Examination. The subcommittee consisted of an international and multidisciplinary panel of experts in UIA and SAH. Consensus recommendations were developed by reviewing previously published CDEs for other neurological diseases including traumatic brain injury, epilepsy and stroke, and the SAH literature. Recommendations for CDEs were classified by priority into "core," "supplemental-highly recommended," "supplemental" and "exploratory."
Results:
We identified 248 variables for Assessments and Clinical Examination. Only the World Federation of Neurological Societies grading scale was classified as "Core." The Glasgow Coma Scale was classified as "Supplemental-Highly Recommended." All other Assessments and Clinical Examination variables were categorized as "Supplemental."
Conclusion:
The recommended Assessments and Clinical Examination variables have been collated from a large number of potentially useful scales, history, clinical presentation, laboratory, and other tests. We hope that adherence to these recommendations will facilitate the comparison of results across studies and meta-analyses of individual patient data.
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