Efficacy of Intra-articular Platelet-rich Plasma in patients of Knee Osteoarthritis
Bibliographic record
Abstract
Objective: To evaluate the efficacy of autologous intra-articular platelet-rich plasma (PRP) injections in patients of knee osteoarthritis. Methodology: This was a prospective study carried out on 50 patients (10 males & 40 females) visiting the outpatient department of Orthopedic Surgery, Sharif Medical City Hospital, Lahore. The study was approved by the ethical committee of the institution. The patients fulfilling the inclusion criteria were asked to fill Western Ontario and McMaster Osteoarthritis criteria (WOMAC) questionnaire. Informed written consent was taken from the patients. Using aseptic techniques, PRP was injected intra-articularly in the affected knee. Three PRP injections were given intra-articularly at 1 week intervals. Patients were regularly followed up after 3 weeks, 6 weeks, 3 months, 6 months and 1 year of the last PRP injection. Each parameter of the WOMAC index was compared with the baseline score at each follow-up. The data obtained was analyzed using SPSS software version 25. Results: The mean age of the patients was 50.82±8.6 years; male to female ratio was 1:4. According to the Kellgren-Lawrence scale, 5(10%) patients had grade I, 16(32%) patients had grade II and 29(58%) patients had grade III osteoarthritis. The mean score of all WOMAC parameters improved significantly as compared to the baseline score before the treatment. There was a significant improvement in joint pain, stiffness and functional ability after PRP injections. Conclusion: Intra-articular injections of autologous platelet-rich plasma in osteoarthritic knee joint are effective in relieving joint pain & stiffness and improve the functional capacity in the patients of knee osteoarthritis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".