Impact of Course Configuration on 6-Minute Walk Test Performance of People with Lower Extremity Amputations
Bibliographic record
Abstract
Purpose: The configuration of the 6-minute walk test (6MWT) may influence the distance walked and comparability of results among subjects and across programmes. The purpose of this study was to evaluate the relative and absolute test–retest reliability of two 6MWT configurations and to evaluate the agreement between these two configurations in users of lower extremity prosthetics. Methods: A cross-sectional design was used to analyze data from 25 subjects completing in-patient prosthetic rehabilitation (mean age 63.12 [SD 13.77] y; 72% male). Two configurations of the 6MWT were examined, and relative and absolute test–retest reliabilities were calculated. Bland–Altman plots were constructed to evaluate agreement between configurations. Results: The relative test–retest reliability was excellent for both Configuration 1 and Configuration 2: ICC 0.97, 95% CI: 0.93, 0.98, and ICC 0.97, 95% CI: 0.94, 0.99, respectively. Comparable values for absolute test–retest reliability were also found. The Bland–Altman plot demonstrated a difference of ±63.92 meters between configurations. Conclusions: The two 6MWT configurations had excellent relative and absolute test–retest reliability, but the results from each configuration do not agree sufficiently to make them interchangeable or directly comparable. This highlights the importance of explicitly indicating the test configuration for the 6MWT when reporting results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".