Inflammatory ultrasound features as prognostic factors of pain and functional outcomes following intra‐articular platelet‐rich plasma in knee osteoarthritis
Bibliographic record
Abstract
AIM: To explore inflammatory ultrasound predictors of improvements in pain and function over 2, 6, and 12 months following administration of intra-articular platelet-rich plasma (PRP) in knee osteoarthritis (OA). METHOD: Patients with painful mild-moderate radiographic knee OA from a subset of the RESTORE RCT underwent ultrasound assessment according to the standardized OMERACT scanning protocol to detect inflammatory features such as synovitis, synovial hypertrophy, and effusion with power Doppler. The study knee was treated with 3 once-weekly PRP injections obtained after centrifugation at 1500 g for 5 min. Numerical Rating Score (NRS), Intermittent and Constant Osteoarthritis Pain (ICOAP) questionnaire, and the Western Ontario and McMaster Universities Arthritis Index (WOMAC) function sub-score were used to measure pain and functional severity. Separate linear regression models were performed to determine whether baseline ultrasound-detected features of inflammation predicted the improvement in pain and function following PRP injection in both unadjusted and adjusted models for confounders. RESULTS: Forty-four participants were included, with 25 (56.8%) being female. In an unadjusted model, higher OMERACT scores for inflammatory features such as global synovitis and/or effusion were significantly associated with greater improvement in all outcomes measured at 2 months but not at 6 and 12 months for pain measures. Only global synovitis showed significant association with functional improvement at 2 and 12 months. Similar findings were observed in the adjusted model. CONCLUSION: Ultrasound indices of knee inflammation predicted short-term improvements in pain severity and both short- and longer-term improvements in function following intra-articular PRP injection.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".