Going places: Does the two-minute walk test predict the six-minute walk test in lower extremity amputees?
Bibliographic record
Abstract
OBJECTIVE: Assessing a patient's ability to walk the distance required for community ambulation (at least 300 m) is important in amputee rehabilitation. During the 2-min walk test, most amputees cannot walk 300 m. Thus, the 6-min walk test may be preferred, but it has not been fully validated in this population. This study examined the convergent and discriminative validity of the 6-min walk test and assessed whether the 2-min test could predict the results of the 6-min test. METHODS: A total of 86 patients with unilateral or bilateral amputations at the Syme, transtibial, knee disarticulation or transfemoral level completed the 6-min walk test, 2-min walk test, Timed Up and Go test, Locomotor Capabilities Index version 5, Houghton Scale of Prosthetic Use, and Activity-Specific Balance Confidence scale. RESULTS: The 6-min walk test correlated with the other tests (R = 0.57-0.95), demonstrating convergent validity. It demonstrated discriminative validity with respect to age, aetiology of amputation, and K-level (p < 0.0001). The 2-min walk test was highly predictive of the 6-min walk test distance (R2 = 0.91). CONCLUSION: The 6-min walk test is a valid measure of amputee ambulation. However, the results suggest that it may not be necessary, since the 2-min walk test strongly predicts the 6-min walk test. Clinicians could therefore save time by using the shorter test.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".