Subclinical Synovitis Assessed by Ultrasound Predicts Flare and Progressive Bone Erosion in Rheumatoid Arthritis Patients with Clinical Remission: A Systematic Review and Metaanalysis
Bibliographic record
Abstract
Objective. Subclinical synovitis can be detected by ultrasound in patients with rheumatoid arthritis (RA) who are in clinical remission. We aimed to confirm its predictive value for flare and progressive bone erosion. Methods. A systematic literature search was performed in Pubmed, Web of Science, Embase, and Cochrane Library on September 7, 2014. Baseline clinical and ultrasonographic characteristics were collected. Methodological quality was assessed. Pooled OR were calculated using Mantel-Haenszel model. We explored the source of heterogeneity through subgroup analysis and completed a cumulative metaanalysis. Results. Thirteen articles were included (8 with flare, 4 with bone erosion, 1 with both flare and bone erosion). Metaanalysis revealed an association between power Doppler (PD) positivity and the risk of flare (OR 4.52, 95% CI 2.61–7.84, p < 0.00001, I2 = 21%), the risk of progressive bone erosion on patient level (OR 12.80, 95% CI 1.29–126.81, p = 0.03, I2 = 52%) and the risk of progressive bone erosion on joint level (OR 11.85, 95% CI 5.01–28.03, p < 0.00001, I2 = 0%). Further subgroup analysis showed a higher risk of flare in patients with a study period < 1 year (OR 19.98 vs 3.41). No significant differences were observed in the subgroup analysis in duration of remission, disease duration, and medications. Moreover, cumulative metaanalysis indicated the validation and an increasing accuracy of PD positivity in predicting flare since 2012. Conclusion. Ultrasound-detected subclinical synovitis can predict the risk of flare and progressive bone erosion in RA patients with clinical remission. Additionally, the flare of RA tends to occur within a followup of 1 year.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.038 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".