Detection of Adult Celiac Disease Using Duodenal Screening Biopsies Over a 30-Year Period
Bibliographic record
Abstract
BACKGROUND: Serological studies suggest that celiac disease may be present in approximately 0.5% to 1% of the North American population. Screening data based on small intestinal biopsy performed during routine endoscopic evaluations are not available. METHODS: Patients referred between January 1982 and December 2011 for evaluation of gastrointestinal symptoms and requiring elective investigative upper endoscopic evaluation underwent duodenal biopsies to determine whether changes of adult celiac disease were present. RESULTS: A total of 9665 patients, including 4008 (41.5%) males and 5657 (68.5%) females, underwent elective endoscopies and duodenal biopsies. Of these, 234 (2.4%) exhibited changes of celiac disease including 73 males (1.8%) and 161 females (2.8%). During the first 20 years, the number of biopsy-positive patients in five-year intervals progressively decreased and, subsequently, during the next 10 years, the number progressively increased. CONCLUSIONS: Celiac disease is far more common in specialist practice than has been suggested in the evaluation of healthy populations using serological screening studies. Endoscopic duodenal biopsy is an important method of identifying underlying celiac disease and should be routinely considered in all patients undergoing an elective endoscopic evaluation. Noninherited factors, possibly environmental, may play a role in the appearance of biopsy-defined celiac disease and alter detection over time.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".