Assessment of clinical activity and severity using serum ANCA and ASCA antibodies in patients with ulcerative colitis
Bibliographic record
Abstract
Abstract Background Ulcerative colitis (UC) is a chronic, non-specific inflammatory bowel disease (IBD) with unknown etiology. The lack of specific clinical manifestations, standard diagnostic criteria, objective and accurate indicators to the severity of the disease and the efficacy of the treatment, often results in difficulties in diagnosis and timely treatment of UC. Therefore, there is a need to develop a clinically suitable serum biomarker assay with high specificity and sensitivity. Objective and methods To explore the significance of anti-neutrophil cytoplasmic antibodies (ANCA) and anti-saccharomyces cerevisiae antibodies (ASCA) in the diagnosis, differential diagnosis and treatment assessment in patients with ulcerative colitis (UC). Serum levels of ANCA-IgG, ASCA-IgA and ASCA-IgG were measured by an enzyme-linked immunosorbent assay (ELISA) in 105 UC patients, 52 non-UC patients and 100 healthy controls. Results (1) Both the ANCA-IgG level and its positive rate in UC patients were significantly higher than those in non-UC controls and healthy controls (p < 0.01). However, the levels of ASCA-IgA, ASCA-IgG and the positive rates in UC patients had no statistical differences when compared with those in non-UC controls or healthy controls (p > 0.05). (2) The sensitivity of ANCA+ and ANCA+/ASCA− in detecting UC patients was 61.90% and 55.24%, respectively, whereas the specificity was 91.45% and 94.08%, respectively. The sensitivity of ASCA+ and ASCA+/ANCA− in non-UC disease controls was 5.33% and 3.85%, respectively, and specificity was 83.9% and 88.78%, respectively. (3) When UC patients were grouped into mild, moderate or severe subtypes, the ANCA-IgG levels were correlated with the severity of UC, and the differences of the ANCA-IgG levels were statistically different among the three subtypes (p < 0.05). There was no correlation between the levels of ANCA-IgG and the disease locations of UC. Conclusions (1) Serum levels of ANCA may be useful in the diagnosis of UC. (2) Dynamic quantitation of ANCA-IgG levels may be helpful in determining the severity of UC and therefore, may guide treatment of UC.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".