Comparison of Speeds Used for the 15.2-Meter and 6-Minute Walks Over the Year After an Incomplete Spinal Cord Injury: The SCILT Trial
Bibliographic record
Abstract
BACKGROUND: Timed walking speed for 6 to 15 m and the distance walked in 2 to 12 minutes are frequently used outcome measures in rehabilitation trials, presumably reflecting different aspects of walking ability. The database from the Spinal Cord Injury Locomotor Trial (SCILT), which tested 2 interventions for mobility upon admission for initial rehabilitation of an incomplete traumatic spinal cord injury (SCI), was used to compare the walking speed employed for each test. METHODS: From 66 to 70 patients with upper motor neuron lesions from C-5 to T-10 performed a 15.2-m and a 6-minute walk as fast as the patient deemed safe at 3 months (end of the trial intervention) and 6 and 12 months after entry. The means, standard errors, and quartiles were calculated for the speed used for each task. RESULTS: The mean speed for the 15.2-m walk did not differ from that used for the 6-minute walk at 3 and 6 months but was significantly faster at 12 months. Differences became apparent at each assessment in patients in the highest quartiles (>1.0 m/s) for the 15.2-m walk. Their speed was from 14% to 24% higher than the speed used for the 6-minute walk. CONCLUSION: The speed of the 15.2-m walk as a measure of walking ability compared to the distance walked in 6 minutes may not represent separable domains of mobility. Differences were apparent only in the most highly functional patients, who could ambulate in the community. Any difference in the walking speed used for these 2 tasks does not make enough of a clinical distinction to encourage including both a 6-minute walk and a 15.2-m walk as outcome measures in clinical trials of locomotor interventions for SCI.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".