The effectiveness of combined spinal manipulation and patella mobilization compared to patella mobilization alone in the conservative management of patellofemoral pain syndrome
Bibliographic record
Abstract
Purpose. Patellofemoral pain syndrome (PFPS) refers to a syndrome associated with the following signs and symptoms: anterior knee pain, inflammation, imbalance, instability, or any combination thereof (Wood 1998). The purpose of this investigation was to evaluate whether spinal manipulation, as an adjunct to patella mobilization, contributed significantly to the improvement of patients diagnosed with PFPS. A prospective trial using convenient sampling was implemented using the first 60 volunteers that met the requirements. These were randomly divided into two groups. Participants in group 2 received combined patella mobilization and spinal manipulative therapy, while those in group 1 received patella mobilization only. Each patient selected for the study was required to complete an informed consent form. The selected patients underwent a general medical case history, lower back and knee orthopaedic regional examinations. 8 clinical experiments were done: pain threshold (ALGI), pain tolerance (ALG2), the mean least pain experienced (NRS 1), the mean worst pain experienced (NRS2), the mean pain experienced (NRS3), pain quality (McGill), patellofemoral joint evaluation scale (PFJE) and a patient specific functional scale (PSFS). All were continuous variables except McGill, which was a categorical variable. For each clinical experiment, readings were taken 3 times, i.e. at the first, third and sixth consultations
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".