Prospective Data Collection: Stroke Comprehensive Outcomes for Rehabilitation Excellence (SCORE)
We believe that the diversity of stroke motor outcome measures used to assess the effects of rehabilitation and recovery—and the lack of standardization of these measures—is a barrier to stroke rehabilitation research.
We believe there is great potential in pooling together data across studies/research sites, and this potential has not been realized due to the heterogeneity in outcome measures collected across studies in different research labs. Standardized outcome measures could allow us to 1) directly compare results of different interventions across studies, 2) to better assess the reproducibility and reliability of interventions, and 3) meta-analyze data across studies for greater power, among other benefits.
In the absence of any formal, standardized outcome measure lists, we’ve created our own battery of assessments that we plan to use for our future prospective studies. We’ve conducted literature reviews and organized these by the categories mentioned above (function, impairment, global disability and more). We also thank Dr. Catherine E. Lang for very insightful feedback.
We’ve generated short, medium, and long batteries that can be used, depending on the time and goals of each project: SCORE batteries
We selected these assessments based on our analysis of the data from ENIGMA Stroke Recovery, in which the Fugl-Meyer and Wolf Motor Function Test/ARAT are the most commonly used assessments in the research setting, and the modified Rankin, NIHSS, and FIM/Barthel in the clinical setting. We weighed the time to complete each assessment with its utility in measuring different aspects of recovery as well as its ability to allow us to compare across clinical and research settings.
In collaboration with Dr. Keith Lohse at the University of Utah, we’ve started generating forms for reproducible, easily combinable data collection for measures such as the Fugl-Meyer, Wolf Motor Function Test, and NIHSS. This data format can be used in any reproducible pipeline using R or python; more measures to come but they can be found here: https://github.com/keithlohse/SCORE_test_batteries
We just wanted to share our steps forward with the community, and we welcome feedback and thoughts to make this even better. We would love for you to join us so we can potentially all work together to improve stroke rehabilitation.
Please do not hesitate to contact us regarding this issue, and we look forward to future productive conversations to enhance the quality of stroke rehabilitation research.
We are also pleased to highlight Dr. Keith Lohse’s SCOAR - the Centralized Open-Access Rehabilitation Database for Stroke, which is a tool that stroke therapy researchers can use to better understand the relationships among variables, efficiently share data, generate hypotheses, and streamline clinical trial design. Visit SCOAR to find out more!