O49 Synovial Lymphocytic Aggregates Associate with Highly Active RA and Predict Erosive Disease Progression at 12 Months: Results from the Pathobiology of Early Arthritis Cohort
Bibliographic record
Abstract
Background: The inflammatory cell infiltrate in RA synovial tissue has long been recognized to organize into lymphocytic aggregates, with data suggesting that these structures are immunologically competent and can support chronic inflammation. However, their clinical significance has been controversial, with conflicting publications reporting diverse associations with disease outcome. Therefore the aim of this study was to determine in an early RA cohort whether synovial pathotypes associate with clinical phenotype and predict radiographic damage at 12 months. Methods: A cohort of 119 consecutive DMARD-naive early RA patients (<12 months duration, 2010 ACR/EULAR criteria) were recruited as part of the Medical Research Council–funded Pathobiology of Early Arthritis Cohort (PEAC; http://www.peac-mrc.mds.qmul.ac.uk/) at Barts and the London Hospital and underwent a pretreatment baseline US-guided synovial biopsy. Baseline demographics [including ESR, CRP, RF, ACPA and 28-joint DAS (DAS28)] and US score [0–3, synovial thickness (ST) and power Doppler (PD) of biopsied joint and 12-joint total US score (10 MCP and 2 wrist joints)] at baseline were determined (Table 1). Furthermore, baseline and 12-month hand and foot radiographs underwent Sharp/van der Heijde scoring (SvH). All patients were treated with DMARD combination therapy with or without oral steroids with a treat-to-target approach (DAS28, CD68+, +/- grade 1 aggregates). Finally, significant differences in clinical parameters at baseline and progression in SvH (≥1) score at 12 months between synovial pathotypes was determined.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".