Characterization and individual-level prediction of cognitive state in the first year after 'mild' stroke.
Juan Pablo Saa, Tamara Tse, Gerald Choon-Huat Koh, Philip Yap, Carolyn M Baum, David E Uribe-Rivera, Saras M Windecker, Henry Ma, Stephen M Davis, Geoffrey A Donnan, Leeanne M Carey
Author Information
Juan Pablo Saa: Occupational Therapy, School of Allied Health, Human Services and Sport, College of Science Health and Engineering, La Trobe University, Melbourne, Australia. ORCID
Tamara Tse: Occupational Therapy, School of Allied Health, Human Services and Sport, College of Science Health and Engineering, La Trobe University, Melbourne, Australia.
Gerald Choon-Huat Koh: Saw-Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore. ORCID
Carolyn M Baum: School of Public Health, Washington University School of Medicine, Saint Louis, MO, United States of America.
David E Uribe-Rivera: Commonwealth Scientific and Industrial Research Organisation (CSIRO) of Australia, Brisbane, Queensland, Australia.
Saras M Windecker: Telethon Kids institute, Perth, Australia.
Henry Ma: Department of Medicine, Monash Health, Monash University, Clayton, Australia.
Stephen M Davis: Departments of Medicine and Neurology, Melbourne Brain Centre, Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia.
Geoffrey A Donnan: Departments of Medicine and Neurology, Melbourne Brain Centre, Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia.
Leeanne M Carey: Occupational Therapy, School of Allied Health, Human Services and Sport, College of Science Health and Engineering, La Trobe University, Melbourne, Australia.
BACKGROUND: Mild stroke affects more than half the stroke population, yet there is limited evidence characterizing cognition over time in this population, especially with predictive approaches applicable at the individual-level. We aimed to identify patterns of recovery and the best combination of demographic, clinical, and lifestyle factors predicting individual-level cognitive state at 3- and 12-months after mild stroke. METHODS: In this prospective cohort study, the Montreal Cognitive Assessment (MoCA) was administered at 3-7 days, 3- and 12-months post-stroke. Raw changes in MoCA and impairment rates (defined as MoCA<24 points) were compared between assessment time-points. Trajectory clusters were identified using variations of ≥1 point in MoCA scores. To further compare clusters, additional assessments administered at 3- and 12-months were included. Gamma and Quantile mixed-effects regression were used to predict individual MoCA scores over time, using baseline clinical and demographic variables. Model predictions were fitted for each stroke survivor and evaluated using model cross-validation to identify the overall best predictors of cognitive recovery. RESULTS: Participants' (n = 119) MoCA scores improved from baseline to 3-months (p<0.001); and decreased from 3- to 12-months post-stroke (p = 0.010). Cognitive impairment rates decreased significantly from baseline to 3-months (p<0.001), but not between 3- and 12-months (p = 0.168). Nine distinct trajectory clusters were identified. Clinical characteristics between clusters at each time-point varied in cognitive outcomes but not in clinical and/or activity participation outcomes. Cognitive performance at 3- and 12-months was best predicted by younger age, higher physical activity levels, and left-hemisphere lesion side. CONCLUSION: More than half of mild-stroke survivors are at risk of cognitive decline one year after stroke, even when preceded by a significantly improving pattern in the first 3-months of recovery. Physical activity was the only modifiable factor independently associated with cognitive recovery. Individual-level prediction methods may inform the timing and personalized application of future interventions to maximize cognitive recovery post-stroke.
References
Int J Mol Sci. 2022 Jan 06;23(2):
[PMID: 35054785]
Int J Stroke. 2015 Jun;10(4):636-44
[PMID: 24206623]
