Presence of Autoantibodies in Erosive Hand Osteoarthritis and Association with Clinical Presentation
Bibliographic record
Abstract
OBJECTIVE: To investigate whether 3 rheumatoid arthritis-associated antibodies [rheumatoid factor (RF) and anticitrullinated protein antibodies (ACPA) or anticarbamylated protein (anti-CarP) antibodies] are present in hand osteoarthritis (HOA) and associate with erosive OA (EOA). METHODS: Anti-CarP IgG was measured by ELISA in baseline sera of patients with HOA from 3 cohorts: HOSTAS (n = 510, 27.2% EOA), ECHO (n = 47), and EHOA (n = 23), and in sera of healthy controls (HC; n = 196, mean age 44.1 yrs, 51.0% women). Moreover, ACPA-IgG and RF-IgM were additionally determined in HOSTAS and HC. The prevalence of autoantibodies was compared between HOA and HC and between erosive and nonerosive HOA. In HOSTAS, hand radiographs were scored (Kellgren-Lawrence, Osteoarthritis Research Society International osteophyte and joint space narrowing) and C-reactive protein (CRP) levels, representing inflammation, were assessed. Groups were compared using nonparametric tests. RESULTS: The prevalence of anti-CarP was low and not significantly different between the total HOA group and HC (6.6% vs 3.6%, p = 0.12). In HOSTAS, the prevalence of all tested autoantibodies was low (anti-CarP 7.1%, ACPA 0.8%, RF 6.1%), and there were no significant differences observed between HOA patients and HC or between erosive and nonerosive HOA. Further, radiographic damage and CRP levels were similar in anti-CarP+ and anti-CarP-, and RF+ and RF- HOSTAS patients. CONCLUSION: The prevalence of autoantibodies is similar in HOA patients and HC, and these autoantibodies are not associated with erosive disease, structural damage, or inflammation in patients with HOA, indicating that another mechanism is driving erosive disease.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".