Arthritis autoantibodies in individuals without rheumatoid arthritis: follow-up data from a Dutch population-based cohort (Lifelines)
Bibliographic record
Abstract
OBJECTIVES: To assess whether the presence of arthritis autoantibodies alongside IgG ACPA predicts clinically suspect arthralgia in ACPA-positive subjects without RA. METHODS: In the population-based Lifelines cohort (n = 40 136), 308 IgG ACPA-positive individuals without RA were present. Serum levels of IgA ACPA, IgA and IgM RF, and IgG anti-carbamylated antibodies were measured at baseline. Individuals were divided based on the Connective tissue disease Screening Questionnaire after 2 years follow-up. Antibodies to Porphyromonas gingivalis were determined at baseline and related to presence of periodontitis and joint complaints at 2 years follow-up. RESULTS: Of 308 subjects 53.6% were also seropositive for IgA ACPA, 42.2% for IgM RF, 23.7% for IgA RF and 13.6% for anti-carbamylated antibodies. We defined 75 persons with clinically suspect arthralgia at risk for RA based on CTD Screening Questionnaire at follow-up. Significantly more seropositivity for IgM RF and higher levels of IgG ACPA, IgA ACPA and IgM RF were found in clinically suspect arthralgia compared with no-clinically suspect arthralgia. In multivariate logistic regression correcting for age, gender and never smoking, positivity for three or more extra autoantibodies was significantly associated with clinically suspect arthralgia. Although levels of anti-P. gingivalis were not different between groups, they were significantly correlated to levels of both RFs, and both ACPAs in clinically suspect arthralgia. CONCLUSIONS: ACPA-positive individuals without RA who develop clinically suspect arthralgia have more and higher levels of other arthritis autoantibodies at baseline. Levels of anti-P. gingivalis are not related to self-reported periodontitis or clinically suspect arthralgia, but are correlated to arthritis autoantibodies in clinically suspect arthralgia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".