Is combining gait retraining or an exercise programme with education better than education alone in treating runners with patellofemoral pain?A randomised clinical trial
Bibliographic record
Abstract
Design Single-blind randomised clinical trial. Objective To compare the effects of three 8-week rehabilitation programmes on symptoms and functional limitations of runners with patellofemoral pain (PFP). Methods Sixty-nine runners with PFP were randomly assigned to one of three intervention groups: (1) education on symptoms management and training modifications (education); (2) exercise programme in addition to education (exercises); (3) gait retraining in addition to education (gait retraining). Symptoms and functional limitations were assessed at baseline (T0), and after 4, 8 and 20 weeks (T4, T8and T20) using the Knee Outcome Survey of the Activities of Daily Living Scale (KOS-ADLS) and visual analogue scales (VASs) for usual pain, worst pain and pain during running. Lower limb kinematics and kinetics during running, and isometric strength were also evaluated at T0and T8. The effects of rehabilitation programmes were assessed using two-way analysis of variance. Results No significant group × time interactions (p<0.447) were found for KOS-ADLS and VASs. All three groups showed similar improvements at T4, T8and T20compared with T0(p<0.05). Only the exercises group increased knee extension strength following rehabilitation (group × time: p<0.001) and only the gait retraining group (group × time: p<0.001) increased step rate (+7.0%) and decreased average vertical loading rate (−25.4%). Conclusion Even though gait retraining and exercises improved their targeted mechanisms, their addition to education did not provide additional benefits on symptoms and functional limitations. Appropriate education on symptoms and management of training loads should be included as a primary component of treatment in runners with PFP. Trial registration number ClinicalTrials.gov ( NCT02352909 ).
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".