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Observational analysis of musculoskeletal adverse events during walking training for chronic strokeNew Tool Predicts Injury Risk in Stroke Walking Programs

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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.

Why walking therapy can be risky

Musculoskeletal pain is common during rehabilitation. It happens when the body is asked to do too much. This pain is not just uncomfortable. It can make people afraid to move again.

Fear of pain leads to less exercise. Less exercise means slower recovery. This cycle is frustrating for everyone involved. Patients want to heal, but injuries get in the way.

Doctors need a way to prevent this. They need to know who is at risk before starting. Guessing is not enough anymore. We need data to guide safe training.

The surprising risk factors found

For a long time, experts did not know why injuries happened. They assumed everyone was at the same risk. This was not true. Some people got hurt easily. Others did not.

This new research changes that view. Scientists built a model to predict risk. It uses simple information from the start. No complex scans are needed.

How doctors can use this data

Think of this model like a weather forecast. It predicts rain before it falls. This tool predicts pain before it starts. It looks at your history and strength.

The model checks three main things. It looks at past orthopedic conditions. It checks your leg movement ability. It asks about your walking habits.

The research included 100 stroke survivors. They trained for 12 weeks at a time. Scientists tracked every injury carefully. They recorded pain and movement limits.

This was a controlled environment. It allowed for close monitoring. The data was very detailed. This helped build a strong prediction tool.

About one-third of the participants got hurt. That is 32 percent of the group. This number is higher than expected. It shows the risk is real.

Three factors stood out clearly. People with prior joint pain were at higher risk. Those with better leg strength were also at higher risk.

This doesn’t mean this treatment is available yet.

The last factor was regular walking. People who walked often before had lower risk. This suggests familiarity with movement helps. It protects the body from strain.

Experts see this as a major step forward. It moves us from guessing to knowing. Doctors can now plan safer workouts. They can watch high-risk patients closely.

This does not stop training. It just makes it smarter. The goal is to keep people moving. We want to avoid pain without stopping progress.

You should talk to your doctor first. Do not start high-intensity walking on your own. Ask if this risk model applies to you.

If you have past joint pain, be careful. If you walk regularly, you may be safer. Listen to your body during training. Stop if you feel sharp pain.

The group was relatively small. It included only 100 people. Results might change with more data. We need to test this in different places.

This model was built internally. It has not been tested on new patients yet. More research is needed to confirm it. Science takes time to get right.

More studies are coming soon. Researchers will test this model on new groups. They want to see if it works everywhere.

Approval takes time and proof. Doctors need to trust the tool. They will wait for official guidelines.

We are moving toward safer rehabilitation. The future looks promising for stroke survivors. Walking therapy will be more personalized. Safety will always come first.

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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