Effectiveness of therapeutic exercise and platelet-rich plasma in the case of knee osteoarthritis
Bibliographic record
Abstract
[Purpose] Osteoarthritis is the most common form of arthritis worldwide and has detrimental effects on an individual's quality of life. We compared two interventions-an exercise program alone and an exercise program combined with the intra-articular platelet-rich plasma (PRP) injection-focusing on pain and functionality in patients with mild knee osteoarthritis. [Participants and Methods] A total of 76 patients (41 men and 35 women) participated in the study. They were divided equally into the control and intervention groups. To assess knee functionality in both groups, we used state-of-the-art assessment tools, namely the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Knee Injury and Osteoarthritis Outcome Score (KOOS). [Results] The results revealed that following the eight-week exercise program, the intervention group showed significantly better values in the WOMAC scale and in three of the four components of the KOOS scale (pain, symptoms, and activities of daily living). Additionally, we observed that the improvement in WOMAC and KOOS scores was significantly better in the intervention group than in the control group. [Conclusion] Combining PRP and exercise therapy can help improve patients' quality of life. However, PRP preparation protocols and exercise prescriptions must be optimized and tailored to individual patient needs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".