Effect of McConnell Patellofemoral Pain Syndrome Protocol on Pain and Functional Disability in Tibiofemoral Osteoarthritis
Bibliographic record
Abstract
Introduction: Osteoarthritis (OA) being a common condition is one of the leading causes of musculoskeletal pain and functional disability. Purpose: This purpose of this study was to find the effect of McConnell patellofemoral pain syndrome (PFPS) protocol in participants with Grade 2 tibiofemoral OA. Settings and Design: This was an experimental pilot study and on participants above 40 years of age. Fifteen patients with Grade 2 tibiofemoral OA of knee were included. Subjects and Methods: The participants were screened on the basis of diagnosed case by orthopedician with the help of X-ray. Participants above 40 years of age were selected including both male and female. The changes in the subject's pain and functional disability were evaluated by the Visual Analog Scale (VAS) and The Western Ontario and McMaster Universities OA Index (WOMAC) scale. Statistical Analysis Used: Shapiro − Wilk test was used to check the normality of data and as it was found to be normally distributed, paired t -test used to analyze within group differences by comparing pre- and postreadings of WOMAC and VAS. Results: Participants with grade 2 tibiofemoral OA of knee had a significant decrease in pain and functional disability as seen in VAS scale, P value was 0.0005 and for WOMAC, P value was 0.0001. Conclusion: This study concludes that McConnell PFPS protocol had an upper hand in reducing functional disability and pain in Grade-2 tibiofemoral OA of knee.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".