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Observational analysis of musculoskeletal adverse events during walking training for chronic stroke.

Observational analysis of musculoskeletal adverse events during walking training for chronic stroke.
Photo by Giuseppe Argenziano / Unsplash
Key Takeaway
Consider that baseline clinical characteristics may help identify chronic stroke patients at elevated risk for musculoskeletal adverse events during walking training.

This is an observational analysis of participants (n=100) from the HIT-Stroke Trials 1 and 2 with chronic stroke undergoing a 12-week moderate- to high-intensity walking training (M-HIT) program. The primary focus was musculoskeletal adverse events, which occurred in 32.0% of participants (32 out of 100).

The authors synthesized associations between baseline characteristics and adverse event risk. A prior orthopedic condition was associated with higher odds (OR 3.02, 95% CI 1.14-8.64). A better Fugl-Meyer lower extremity motor score was also associated with higher odds (OR 1.14, 95% CI 1.02-1.28). Conversely, self-reported participation in regular walking exercise was associated with lower odds (OR 0.17, 95% CI 0.05-0.49).

The authors note limitations, including that the model is based on baseline clinical characteristics only and requires external validation. The predictive model showed moderate discrimination (cross-validated C-statistic = 0.74).

Practice relevance suggests baseline characteristics may help identify individuals at elevated risk for musculoskeletal adverse events during M-HIT, who may warrant closer monitoring. However, the authors caution that this is an observational study; associations are reported, not causation, and findings may not generalize beyond the chronic stroke population.

Study Details

Sample sizen = 100
EvidenceLevel 5
PublishedApr 2026
View Original Abstract ↓
Background: Moderate- to high-intensity walking training (M-HIT) is an established intervention for improving walking capacity in chronic stroke. Musculoskeletal (MSK) adverse events commonly occur during M-HIT, yet tools to identify individuals at higher risk are limited. Baseline clinical characteristics may provide insight into susceptibility to training-related MSK adverse events during M-HIT. Thus, this study aimed to develop and internally validate a model for predicting MSK adverse events during a 12-week M-HIT program in chronic stroke using baseline clinical characteristics. Methods: Participants (n=100) from HIT-Stroke Trials 1 and 2 were included. Baseline clinical characteristics included measures of orthopedic history, pre-existing pain, motor function, recent exercise history, demographics and health characteristics, stroke chronicity, and psychological health. Logistic regression models evaluated all possible combinations of baseline characteristics with up to three predictors. Leave-one-out cross-validation was used for internal validation to mitigate overfitting. Predictive performance was quantified using the C-statistic, and the candidate model with the highest cross-validated C-statistic was selected as the final model. Results: MSK adverse events occurred in 32.0% of participants. The optimal three-variable model included prior orthopedic condition (Odds ratio [OR] 3.02 [95% CI 1.14-8.64]), Fugl-Meyer lower extremity motor score (OR 1.14 [95% CI 1.02-1.28]), and self-reported participation in regular walking exercise (OR 0.17 [95% CI 0.05-0.49]) at baseline. This model demonstrated moderate discrimination (cross-validated C-statistic = 0.74; apparent C-statistic = 0.78). Conclusions: Participants reporting at least one pre-existing lower extremity or lumbar spine orthopedic condition and those with better lower-extremity motor function exhibited greater odds of experiencing MSK adverse events during M-HIT, while participants reporting participation in regular walking exercise had lower odds. These findings suggest that baseline clinical characteristics may help identify individuals at elevated risk for MSK adverse events during M-HIT who may warrant closer monitoring or risk-reduction strategies. Future studies are needed for external validation. Clinical Trial Registration: https://ClinicalTrials.gov; Unique identifiers: NCT03760016, NCT06268041
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