A272 PERFORMANCE OF TISSUE TRANSGLUTAMINASE ANTIBODIES FOR A DIAGNOSIS OF CELIAC DISEASE IS DECREASED IN ADULTS WITH OTHER COMORBIDITIES
Bibliographic record
Abstract
Tissue transglutaminase antibodies(tTG) is a first step for detection of celiac disease(CeD). However, in a pediatric population, an increase of <3 times UNL was poorly predictive of CeD. In adults, discrepancies between tTG and histology were reported with liver disorders and how these and other comorbidities influence the performance of tTG remains unknown. To determine the positive predictive value(PPV) of the degree of increase of tTG for newly diagnosed biopsy-proven CeD(BxCeD) in adults with and without other comorbidities. Retrospective study based on chart review from August 2003 to June 2016. Inclusion criteria: all patients with a dosage of tTG at the Centre Hospitalier de l’Université de Montréal and duodenal biopsies done three months before to six months after tTG. Exclusion criteria: inadequate histologic specimen, CeD already known or being on a gluten free diet. Patients were identified as BxCeD if histology corresponded to Marsh type 1 up to 3c. Medical records were reviewed for comordibities at the time of the dosage of tTG, namely liver disorders, auto-immune, infectious diseases and inflammatory states. Patients with and without these comorbidities were classified as Dis+ or Dis- groups. ROC curve analysis was performed to determine the UNL threshold where sensitivity(Sn) and specificity(Sp) are optimized for diagnosis of BxCeD in both groups. PPVs below and above these thresholds were calculated and compared with Fisher’s exact tests. 206 patients were included; 63% of women; mean age(±SD) 48(±16)years. BxCeD was identified in 80% of patients(n=164). Overall, 73 patients were found with ≥1 relevant comorbidities(Dis+ group), mainly liver diseases(n=32), connective tissue diseases(n=11), and inflammatory bowel diseases(n=7). BxCeD was found in 60% of them while this proportion was of 90% in the Dis- group. ROC curve in the Dis- group revealed that Sp/Sn were optimized at 2.74 times UNL. When PPV were calculated according to this threshold (Table), PPVs were significantly lower in the Dis+ group vs. the Dis- group. In the Dis+ group, the threshold optimizing the Sp/Sn of the tTg test was 3.83 times UNL, which increased the PPV to 88% among these patients. The performance of the tTG test for detecting biopsy-proven CeD is decreased significantly by the presence of comorbidities such as liver disorders, other auto-immune diseases, infections, and inflammatory states. PPV of the tTG for BxCeD according to the presence of other comorbidities Dis +: either liver, auto-immune, infectious or inflammatory disease at the time of tTG None
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".