Palindromic Rheumatism with Positive Anticitrullinated Peptide/Protein Antibodies Is Not Synonymous with Rheumatoid Arthritis. A Longterm Followup Study
Bibliographic record
Abstract
OBJECTIVE: To analyze longterm progression to rheumatoid arthritis (RA) and the predictive value of anticitrullinated peptide/protein antibodies (ACPA) in palindromic rheumatism (PR). METHODS: We selected all patients in our clinic with PR who had at least 1 ACPA measurement. We included only patients with pure PR, defined as no evidence of associated rheumatic disease at the first serum ACPA measurement. Clinical characteristics, serum ACPA levels, duration of PR until serum ACPA measurement, and total followup time were recorded. The outcome variable was the definitive diagnosis of RA. The prognostic value of ACPA status in pure PR for a definite diagnosis of RA was analyzed by different statistical methods. RESULTS: Seventy-one patients (54 women/17 men) with a PR diagnosis were included. Serum ACPA were positive in 52.1%. After a mean followup of 7.6 ± 4.7 years since the first ACPA measurement, 24 patients (33.8%) progressed to chronic disease: 22% RA, 5.6% systemic lupus erythematosus, and 5.6% other diseases. The positive likelihood ratio of ACPA status for RA was 1.45, and the area under the receiver-operating characteristic curve of ACPA titers was 0.60 (95% CI 0.45-0.75). Progression to RA was more frequently seen in ACPA-positive than in ACPA-negative patients (29.7% vs 14.7%), but the difference was not significant (hazard ratio 2.46, 95% CI 0.77-7.86). Mean ACPA levels of patients with pure PR did not differ significantly from those of patients who progressed to RA. CONCLUSION: ACPA are frequently found in the sera of patients with PR, and a significant proportion of these patients do not progress to RA in the long term.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".