pANCA, ASCA, and OmpC Antibodies in Patients with Ankylosing Spondylitis without Inflammatory Bowel Disease
Bibliographic record
Abstract
OBJECTIVE: Patients with ankylosing spondylitis (AS) can suffer concurrently from inflammatory bowel disease (IBD), as ulcerative colitis (UC) or Crohn's disease (CD). Serological markers have been described to diagnose IBD. We investigated IBD serological markers in AS patients without IBD and whether these antibodies enable differentiating patients with AS and IBD from those without IBD. METHODS: Frequencies of perinuclear antineutrophil cytoplasmic antibodies (pANCA), antibodies to the cell-wall mannan of Saccharomyces cerevisiae (ASCA), and antibodies to porin protein C of Escherichia coli (OmpC) were evaluated in 179 patients: 52 with AS, 50 with UC, 51 with CD, and 26 with IBD and AS. Patient groups were matched for age and sex. All AS patients fulfilled the 1984 modified New York criteria. IBD was ascertained by clinical, endoscopic, and microscopic findings. RESULTS: In 55% of the AS patients without manifest IBD at least one antibody associated with IBD was observed. pANCA, ASCA (IgA and/or IgG), and OmpC antibodies were found in 21%, 30%, and 19% of the AS patients, respectively. pANCA was more frequently present in AS with concurrent UC than in AS alone (OR 8.2, 95% CI 1.2-55.6), thus being an indicator for UC in AS patients. CONCLUSION: Antibodies associated with IBD are detectable in more than half of AS patients without symptoms or signs of IBD. A relatively recent marker in this setting, OmpC antibodies, does not contribute to the differentiation between AS and type of IBD. Presence of pANCA, however, is significantly increased in AS patients who also have UC, and is an indicator to perform endoscopy. These results corroborate a pathophysiological link between AS and IBD.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".