Development of a physical mobility prediction model to guide prosthetic rehabilitation.

BACKGROUND

Prosthetic rehabilitation decisions depend on estimating a patient's mobility potential. However, no validated prediction models of mobility outcomes exist for people with lower-limb amputation (LLA).

OBJECTIVES

To develop and test predictions for self-reported mobility after LLA, using the Prosthetic Limb Users Survey of Mobility (PLUS-M).

STUDY DESIGN

This is a retrospective cohort analysis.

METHODS

Eight hundred thirty-one patient records (1,860 PLUS-M observations) were used to develop and test a neighbors-based prediction model, using previous patient data to predict the 6-month PLUS-M T-score trajectory for a new patient (based on matching characteristics). The prediction model was developed in a training data set (n = 552 patients) and tested in an out-of-sample data set of 279 patients with later visit dates. Prediction performance was assessed using bias, coverage, and precision. Prediction calibration was also assessed.

RESULTS

The average prediction bias for the model was 0.01 SDs, average coverage was 0.498 (ideal proportion within the 50% prediction interval = 0.5), and prediction interval was 8.4 PLUS-M T-score points (40% improvement over population-level estimates). Predictions were well calibrated, with the median predicted scores falling within the standard error of the median of observed scores, across all deciles of the data.

CONCLUSIONS

This neighbors-based prediction approach allows for accurate estimates of PLUS-M T-score trajectories for people with LLA.