Lasting Improvement of Patient-Reported Outcomes 6 Months After Patellofemoral Pain Rehabilitation
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: Hip- and knee-muscle-strengthening programs are effective in improving short-term patient-reported and disease-oriented outcomes in individuals with patellofemoral pain (PFP), but few to no data exist on moderate- to long-term postrehabilitative outcomes. The first purpose of the study was to assess differences in pain, function, strength, and core endurance in individuals with PFP before, after, and 6 mo after successful hip- or knee-muscle-strengthening rehabilitation. The second purpose was to prospectively follow these subjects for PFP recurrence at 6, 12, and 24 mo postrehabilitation. METHODS: For 24 mo postrehabilitation, 157 physically active subjects with PFP who reported treatment success were followed. At 6 mo postrehabilitation, pain, function, hip and knee strength, and core endurance were measured. At 6, 12, 18, and 24 mo, PFP recurrence was measured via electronic surveys. RESULTS: Sixty-eight subjects (43%) returned to the laboratory at 6 mo. Regardless of rehabilitation program, subjects experienced significant improvements in pain and function, strength, and core endurance pre- to postrehabilitation and maintained improvements in pain and function 6 mo postrehabilitation (Visual Analog Scale/Pain-pre 5.12 ± 1.33, post 1.28 ± 1.14, 6 mo 1.68 ± 2.16 cm, P < .05; Anterior Knee Pain Scale/Function-pre 76.38 ± 8.42, post 92.77 ± 7.36, 6 mo 90.27 ± 9.46 points, P < .05). Over the 24 mo postrehabilitation, 5.10% of subjects who responded to the surveys reported PFP recurrence. CONCLUSIONS: The findings support implementing a hip-or knee-muscle-strengthening program for the treatment of PFP. Both programs improve pain, function, strength, and core endurance in the short term with moderate- and long-term benefits of improved pain and function and low PFP recurrence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".