Common Data Elements for Unruptured Intracranial Aneurysms and Aneurysmal Subarachnoid Hemorrhage: Recommendations from the Working Group on Hospital Course and Acute Therapies-Proposal of a Multidisciplinary Research Group.

ABSTRACT

INTRODUCTION: The Common Data Elements (CDEs) initiative is a National Institute of Health/National Institute of Neurological Disorders and Stroke (NINDS) effort to standardize naming, definitions, data coding, and data collection for observational studies and clinical trials in major neurological disorders. A working group of experts was established to provide recommendations for Unruptured Aneurysms and Aneurysmal Subarachnoid Hemorrhage (SAH) CDEs. METHODS: This paper summarizes the recommendations of the Hospital Course and Acute Therapies after SAH working group. Consensus recommendations were developed by assessment of previously published CDEs for traumatic brain injury, stroke, and epilepsy. Unruptured aneurysm- and SAH-specific CDEs were also developed. CDEs were categorized into "core", "supplemental-highly recommended", "supplemental" and "exploratory". RESULTS: We identified and developed CDEs for Hospital Course and Acute Therapies after SAH, which included surgical and procedure interventions; rescue therapy for delayed cerebral ischemia (DCI); neurological complications (i.e. DCI; hydrocephalus; rebleeding; seizures); intensive care unit therapies; prior and concomitant medications; electroencephalography; invasive brain monitoring; medical complications (cardiac dysfunction; pulmonary edema); palliative comfort care and end of life issues; discharge status. The CDEs can be found at the NINDS Web site that provides standardized naming, and definitions for each element, and also case report form templates, based on the CDEs. CONCLUSION: Most of the recommended Hospital Course and Acute Therapies CDEs have been newly developed. Adherence to these recommendations should facilitate data collection and data sharing in SAH research, which could improve the comparison of results across observational studies, clinical trials, and meta-analyses of individual patient data.