The utility of synovial fluid levels of ADAMTS9 and ADAMTS4 in predicting treatment responses to intraarticular steroid injections in patients with knee osteoarthritis
Bibliographic record
Abstract
Background/aim: This study aims to identify the role of synovial fluid levels of a disintegrin and metalloproteinase with thrombospondin motifs 9 (ADAMTS9) and a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS4) for the prediction of intraarticular steroid injection success in knee osteoarthritis (OA). Material and methods: A total of eighty-four advanced stage knee OA patients (42 with stage 3 OA and 42 with stage 4 OA) were enrolled in the study. Baseline and posttreatment outcomes were determined using Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Pretreatment synovial fluid ADAMTS9 and ADAMTS4 levels were measured by enzyme linked immunosorbent assay (ELISA). ‘’Total WOMAC score regression of 18% and above’’ was taken as a minimal clinically important difference (MCID) to indicate improvement. Determining the best predictors of intraarticular steroid injection success in both groups was evaluated by multiple logistic regression analyses. Results: Synovial fluid ADAMTS9 levels were significantly lower in the stage 4 OA group when compared with the stage 3 group. The level of synovial fluid ADAMTS9 was statistically significantly lower in the WOMAC score percent change ≥18% than the WOMAC score percent change <18% group in Stage 3 OA group (P = 0.026). Decreasing synovial fluid ADAMTS9 levels (odds ratio (OR): 0.625, 95% confidence interval (CI): 0.437–0.893) were found to be predictive for the WOMAC score percent change ≥18 in all OA patients (P = 0.010). Decreasing ADAMTS9 levels in synovial fluid (OR: 0.602; 95% CI = 0.372–0.974) were predictive for MCID in stage 3 OA patients (P = 0.039). Conclusion: The lower levels of ADAMTS9 in synovial fluid may be used in conjunction with high WOMAC scores in the prediction of intraarticular steroid injection success and advanced stage knee OA patients.
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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 | 0.001 | 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".