The effect of axillary crutch length on upper limb kinematics during swing‐through gait
Bibliographic record
Abstract
BACKGROUND: Axillary crutches are commonly used in rehabilitation. Inappropriately fit crutches may result in upper limb pain or injury. OBJECTIVE: To investigate the effects of axillary crutch length on upper limb kinematics to better understand potential injury mechanisms. It was hypothesized that crutches that were longer or shorter than standard-fit crutches would alter upper limb kinematics. DESIGN: Cross-sectional. SETTING: Gait laboratory. PARTICIPANTS: Fifteen healthy males with no prior crutch experience. INTERVENTIONS: ) with all crutch lengths in randomized order. Kinematics were recorded using an optical motion-tracking system and joint angles for the scapula, shoulder, elbow, and wrist were computed. MAIN OUTCOME MEASURES: ; α = .025) and simultaneous confidence intervals (CI). RESULTS: The long-standard crutch fit comparison showed effects across all joints (ROM p = .009; initial contact p < .001). Longer crutches resulted in greater scapular upward rotation (mean difference [95% CI] ROM: 1.0 [-0.2 to 2.2]; initial contact: -2.7 [-4.4, -1.1]) and shoulder abduction (ROM: 0.8 [-0.1 to 1.8]; initial contact: -1.9 [-4.1 to 0.3]). Crutch length also had effects across all joints for the short-standard fit comparison (ROM p = .004; initial contact p = .016). Shorter crutches resulted in greater scapula downward rotation (2.2 [-0.4 to 4.8]) and greater shoulder adduction (2.5 [-0.6 to 5.6]) at initial contact. Shorter crutches also reduced shoulder flexion/extension ROM (-2.5 [-4.4 to -0.6]). CONCLUSIONS: Altered crutch length results in scapular and shoulder kinematic deviations that may present risk factors for upper limb injury with crutch-walking. This may underline the importance of appropriate device fitting to reduce injury risk in crutch users.
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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 | 0.004 |
| 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 | 0.000 |
| 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".