Assessment of the effectiveness and satisfaction of platelet-rich plasma compared with hyaluronic acid in knee osteoarthritis at minimum 7-year follow-up: A post hoc analysis of a randomized controlled trial
Bibliographic record
Abstract
Background: Knee osteoarthritis (KOA) can be effectively treated conservatively using platelet-rich plasma (PRP) injections into the affected joints. While the short-term therapeutic clinical benefits were well documented, the mid-term results remain undetermined. To clarify its efficacy, the mid-term clinical outcomes of intra-articular injections of either PRP or hyaluronic acid (HA) in KOA were compared. Methods: One hundred patients who complied with the inclusion criteria were randomized to undergo once a week 3 weeks, intra-articular injections of either PRP or HA. Patients were evaluated before the injection, at 3, 6, and a mean of 78.9 months of follow-up. Eighty-five patients reached the final evaluation. Data on survival, re-intervention, pain, function, imaging, and satisfaction were collected and analyzed. Results: With surgery for any reason as the endpoint, the cumulative survival rate of the PRP group was 90%, while that of the HA group was 74%. There was a significant difference between the two groups in the total re-intervention rate (56.7% vs 16.2%, p < 0.05). The comparative analyses showed significant intergroup differences in the visual analog scale (VAS) and the Western Ontario and McMaster Universities Arthritis Index (WOMAC) (p < 0.01, p < 0.05, respectively) at the final follow-up. And base on the regression analyses, the type of treatment, age, and Kellgren-Lawrence (K-L) grade served as statistically an independent determinants of VAS (p < 0.001, p = 0.034, p < 0.001, respectively). Likewise, those variables independently determined WOMAC in our study. However, no difference was observed in the imaging evaluation, containing the K-L grade and Cartilage Lesion Score, between the two groups (p > 0.05). Besides, the satisfaction treated by the PRP was 78.6%, with a superiority compared with HA (55.8%, p < 0.05), and no complications were noted in the whole treatment process among patients who participated. Conclusion: PRP was more effective than HA in survival and re-intervention rates, VAS, and WOMAC, although there were no significant differences in the imaging evaluation between the two groups. Furthermore, patients treated with PRP were associated with higher satisfaction compared with HA.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".