Minimal clinically important difference of the L Test for individuals with lower limb amputation
Bibliographic record
Abstract
BACKGROUND: The L Test is a reliable/valid clinical evaluation of mobility that measures walking speed in seconds. It can be used with individuals with lower limb amputation. Responsiveness of the L Test is not yet determined. OBJECTIVES: The purpose of this pilot study was to determine how well the L Test identified individuals with a lower limb amputation who have/have not undergone a minimal clinically important difference. STUDY DESIGN: Prospective follow-up study. METHODS: In total, 33 individuals with lower limb amputation, deemed to require a major intervention, were recruited consecutively from a follow-up clinic. Participants completed the L Test at baseline and follow-up. A Global Rating Change scale was also completed at follow-up. RESULTS: The participants had a mean age ± standard deviation of 60 ± 13.0 years, and 81.8% had a transtibial amputation. The mean ± standard deviation for the L Test change scores was 6.0 ± 13.9. The area under the curve was 0.67, and the minimal clinically important difference was 4.5 s. CONCLUSIONS: The L Test identified individuals as having an important clinical change. Results must be interpreted with caution, as the accuracy, based on the Global Rating Change scale, is low. Further inquiry into the L Test is encouraged. CLINICAL RELEVANCE: The L Test can guide the clinical management of individuals with lower limb amputation. Results from this pilot study indicate that individuals with a lower limb amputation who improve by at least 4.5 s on the L Test after an intervention have likely undergone an important change. This result must be interpreted with caution given that the ability of the L Test to correctly identify individuals, who have and have not undergone an important change, using the Global Rating Change scale as the gold standard, is limited because this is a pilot study. It is plausible that the precision of the cut-point threshold could increase or decrease given a larger sample or when using a different method of identifying important clinical change.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".