Clinical and functional outcomes following platelet rich plasma in the management of knee osteoarthritis: A case series in a tertiary care hospital.
Bibliographic record
Abstract
OBJECTIVE: To clinically assess the efficacy of Platelet rich Plasma (PRP) in improving the functional movement in knee osteoarthritis. METHODS: This prospective case series, on 89 patients, was studied in Sindh Rangers Hospital, Karachi, Pakistan from 1st October 2018 to 31st March 2019. The analysis involved all patients aged 30-65 years diagnosed with grade 1, 2 and 3 arthritis. PRP was administered in three doses one month apart, and patients were evaluated for outcome measures after the third month of the third dose of PRP. To measure functional improvement in knee osteoarthritis, the range of motion (ROM), McMaster University Osteoarthritis index (WOMAC), Western Ontario, and Visual analogue scale (VAS) were used. RESULTS: PRP was infused into 89 patients, with a mean age of 61.24±8.92 years. The average pre-treatment WOMAC score was 37.0 ±2.9, and it was lowered to 18.8± 5.2 after PRP (p<0.02). The pre-treatment VAS was 8.42 ±0.84, and it was reduced to 4.91±2.12, indicating mild to moderate pain. Our PRP therapy was appreciated by 63 (70.07%) patients, while 17 (19.1%) were only partly satisfied. However, 9 (10.1%) patients were dissatisfied. CONCLUSIONS: The results of this case series showed that the use of PRP injections for treating osteoarthritis (grade 1 to 3) proved to be successful in terms of improving functional outcomes and reducing pain intensity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".