Predicting walking capacity, walking performance, and life space mobility using socket comfort in lower-limb prosthesis users
Bibliographic record
Abstract
Objective To determine if socket comfort predicts walking capacity, walking performance, and life-space mobility. Design Observational exploratory study involving a secondary cross-sectional analysis using multiple regression of data collected from an exercise intervention trial. Setting Laboratory setting for clinical assessments; community setting for walking performance. Participants Community-dwelling lower-limb prosthesis users over 50 years old ( n = 72). Main measures Socket Comfort Score, 2-Minute Walk Test, step count, Life Space Assessment, and control variables including demographics, Short Physical Performance Battery, Four Square Step Test, and Walking While Talking. Results Regression modeling showed Socket Comfort Score as a statistically significant predictor of 2-Minute Walk Test ( B = 6.9 m, 95% CI [2.7, 11.1] m) alongside amputation level, Walking While Talking test, and Short Physical Performance Battery (greatest contribution to the model); the model accounted for 61% of the variance. Socket Comfort Score was not a statistically significant predictor of step count. Socket Comfort Score was the only statistically significant predictor of Life Space Assessment ( B = 4.9, 95% CI [1.1, 8.8]); the model accounted for 12% of the variance. Conclusions Socket comfort played a notable role in predicting walking capacity and life space mobility, but not in walking performance. Improving lower extremity function may have greater impact on walking overall. While this study provides context regarding socket comfort that clinicians may consider when planning holistic prosthetic rehabilitation, mixed findings in the literature suggest that further research on how socket comfort relates to walking outcomes in the community is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".