Bilateral Patellofemoral Pain Syndrome and the Effects of Physical Therapy in the Outpatient Setting: A Case Study
Bibliographic record
Abstract
Background and Purpose: Patellofemoral pain syndrome (PFPS) is characterized by musculoskeletal-related knee pain localized to the anterior retropatellar and/or peripatellar area of the knee. This case study describes the physical therapy management of bilateral PFPS. The results can be used to understand examination, evaluation, and interventions to treat PFPS. Case Description: The patient was a 76-year-old female that reported progressive pain in both knees. She demonstrated weak hip abductors and extensors, tenderness upon palpation to bilateral pes anserine, bilateral ITB, and bilateral medial joint line with increased lateral tibial torsion on the left and a positive Hamstring 90-90 test. Intervention: Therapy emphasized functional hip and knee targeted exercises in weight bearing and non-weightbearing positions. Exercises included strengthening and stretching of the lower extremities that would facilitate the patient’s return to prior level of function. Outcomes: Upon discharge, the patient had increased hip and knee strength bilaterally, decreased pain, and improved her functional mobility as indicated by her decrease in disability score on the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Discussion: Interventions aimed at increasing posterolateral hip musculature and improving functional mobility However, more research must be done regarding specific modes of exercise in order to develop and distinguish the best treatment protocol for PFPS. 1 CHAPTER I BACKGROUND AND PURPOSE Patellofemoral pain syndrome (PFPS) is a clinical diagnosis that is characterized b
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".