Pre-endoscopic serological test with duodenal biopsy in high risk patients had high sensitivity and low specificity for coeliac disease
Bibliographic record
Abstract
Hopper AD, Cross SS, Hurlstone DP, et al . Pre-endoscopy serological testing for coeliac disease: evaluation of a clinical decision tool. BMJ 2007;334:729. [OpenUrl][1][Abstract/FREE Full Text][2] Q Does a clinical decision tool (CDT) based on pre-endoscopic serological testing with duodenal biopsy for high risk patients accurately diagnose coeliac disease? Clinical impact ratings Gastroenterology ★★★★★☆☆ IM/Ambulatory care ★★★★★☆☆ ### ![Graphic][3]</img>Design: 2 cohort studies, 1 for derivation and 1 for validation. ### ![Graphic][4]</img>Setting: endoscopy department at the Royal Hallamshire Hospital, Sheffield, UK. ### ![Graphic][5]</img>Patients: 1464 patients in the retrospective derivation cohort and 2000 patients 16–94 years of age (mean age 56 y, 58% women) in the prospective validation cohort who were referred for gastroscopy. Exclusion criteria were previously known coeliac disease, coagulopathy (international normalised ratio >1.3 or platelets <80 x 109/l), active gastrointestinal bleeding, or suspected cancer. ### ![Graphic][6]</img>Description of prediction guide: the CDT combined pre-endoscopic serological testing (tissue transglutaminase [TTG] antibody) and assessment of symptoms to identify patients at high or low risk of coeliac disease. The CDT was modified in the validation … [1]: {openurl}?query=rft.jtitle%253DBMJ%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmj.39133.668681.BE%26rft_id%253Dinfo%253Apmid%252F17383983%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=bmj&resid=334/7596/729&atom=%2Febmed%2F12%2F5%2F155.atom [3]: /embed/inline-graphic-1.gif [4]: /embed/inline-graphic-2.gif [5]: /embed/inline-graphic-3.gif [6]: /embed/inline-graphic-4.gif
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".