Consensus Recommendations for Standardized Data Elements, Scales, and Time Segmentations in Studies of Human Circadian/Diurnal Biology and Stroke

Abstract

Increasing evidence indicates that circadian and diurnal rhythms robustly influence stroke onset, mechanism, progression, recovery, and response to therapy in human patients. Pioneering initial investigations yielded important insights but were often single-center series, used basic imaging approaches, and used conflicting definitions of key data elements, including what constitutes daytime versus nighttime. Contemporary methodologic advances in human neurovascular investigation have the potential to substantially increase understanding, including the use of large multicenter and national data registries, detailed clinical trial data sets, analysis guided by individual patient chronotype, and multimodal computed tomographic and magnetic resonance imaging. To fully harness the power of these approaches to enhance pathophysiologic knowledge, an important foundational step is to develop standardized definitions and coding guides for data collection, permitting rapid aggregation of data acquired in different studies, and ensuring a common framework for analysis. To meet this need, the Leducq Consortium International pour la Recherche Circadienne sur l'AVC (CIRCA) convened a Consensus Statement Working Group of leading international researchers in cerebrovascular and circadian/diurnal biology. Using an iterative, mixed-methods process, the working group developed 79 data standards, including 48 common data elements (23 new and 25 modified/unmodified from existing common data elements), 14 intervals for time-anchored analyses of different granularity, and 7 formal, validated scales. This portfolio of standardized data structures is now available to assist researchers in the design, implementation, aggregation, and interpretation of clinical, imaging, and population research related to the influence of human circadian/diurnal biology upon ischemic and hemorrhagic stroke.

Keywords: biology; chronotype; common data elements; humans; registries.