A Metaanalysis of the Increased Risk of Rheumatoid Arthritis-related Pulmonary Disease as a Result of Serum Anticitrullinated Protein Antibody Positivity
Bibliographic record
Abstract
OBJECTIVE: An inconsistent association has been reported between the serum anticitrullinated protein antibodies (ACPA) level and rheumatoid arthritis (RA)-related pulmonary disease risk. We conducted a metaanalysis to reveal the association between them. METHODS: An electronic search was performed in PubMed, ScienceDirect, and SpringerLink databases for studies published up to August 2013. The distributions of the serum ACPA level in cases and controls were obtained from eligible studies. The risk of RA-related pulmonary disease associated with serum ACPA positivity was estimated by OR and 95% CI. According to the heterogeneity results, a fixed-effects model or a random-effects model was used to calculate the pooled OR. Publication bias and sensitivity analyses were conducted. RESULTS: Overall, 243 patients with RA-related pulmonary disease and 1442 RA controls were included in the metaanalysis. The results showed that the pooled OR was 2.621 (95% CI, 1.561-4.403, p < 0.001) for the increased risk of RA-related pulmonary disease due to the serum ACPA positivity. In the white population subgroup, an increased OR was 3.453 (95% CI 1.798-6.630, p < 0.001), whereas no association was found in the Asian population subgroup. Additionally, we further revealed that serum ACPA positivity indicated a higher risk for interstitial lung disease (ILD) and interstitial pulmonary fibrosis (IPF) among patients with RA (OR 4.679, 95% CI 2.071-10.572, p < 0.001). The heterogeneity, publication bias, and sensitivity analyses had no statistical significance in any group. CONCLUSION: To our knowledge, this is the first metaanalysis to reveal that serum ACPA positivity is highly associated with the risk of RA-related pulmonary disease, particularly in RA-related ILD and IPF.
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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 | 0.018 | 0.032 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.064 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 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".