Many prognostic models for gait independence post stroke have been published in the literature.
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None had been externally validated and evaluated for clinical impact, therefore limiting translation into clinical practice.
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We systematically searched for models predicting independent gait post stroke, appraised the level of bias, and summarized their predictive performance.
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The present study is the first external validation of a prognostic model obtained for post stroke gait independence using a large Danish cohort. To improve performance of the model, recalibration and updates were performed and the updated model was corrected for overfitting by internal validation.
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The updated model uses easy to obtain parameters and should now undergo validation in a separate dataset before being tested for clinical impact.
Abstract
Objective
To externally validate recent prognostic models that predict independent gait following stroke.
Study Design and Setting
A systematic search identified recent models (<10 years) that predicted independent gait in adult stroke patients, using easily obtainable predictors. Predictors from the original models were assigned proxies when required, and model performance was evaluated in the validation cohort (n = 957). Models were updated to determine if performance could be improved.
Results
Three prognostic models met our criteria, all with high Risk of Bias. Validation data was only available for the Australian model. This model used National Institute of Health Stroke Scale (NIHSS) and age to predict independent gait, using Motor Assessment Scale (MAS) walking item. For validation, Scandinavian Stroke Scale (SSS) was a proxy for NIHSS, and Functional Independence Measure (FIM) locomotion item was a proxy for MAS. The Area Under the Curve was 0.77 (0.74–0.80) and had good calibration in the validation dataset. Adjustment of the intercept and regression coefficients slightly improved discrimination. By adding paretic leg strength, the model further improved (AUC 0.82).
Conclusion
External validation of the Australian model with proxies showed fair discrimination and good calibration. Updating the model by adding paretic leg strength further improved model performance.
