Given® Capsule Endoscopy in Celiac Disease: Evaluation of Diagnostic Accuracy and Interobserver Agreement
Bibliographic record
Abstract
BACKGROUND AND AIMS: Capsule endoscopy (CE) has been increasingly used for diagnosing diseases of the small bowel. It is an attractive technique for assessing celiac disease (CD) because it is noninvasive and provides a close and magnified view of the mucosa of the entire small bowel. In this study, we evaluated the accuracy of CE and interobserver agreement in recognizing villous atrophy (VA) using histopathology as the reference. We also explored the extent of small bowel involvement with CD and the relationship between the length of the affected bowel and the clinical presentation. METHODS: Ten CD patients with histologically proven VA and the same number of controls were subjected to CE. Four, blinded to histology findings, investigators (two with and two without prestudy CE experience) were asked to diagnose VA on CE images. RESULTS: Based on assessment of all four investigators, the overall sensitivity, specificity, PPV, and NPV of CE in diagnosing VA were 70%, 100%, 100%, and 77%, respectively. The sensitivity and the specificity of the test was 100% when the reports of experienced capsule endoscopists only were analyzed. The interobserver agreement was perfect (kappa= 1.0) between investigators with prestudy CE experience and poor (kappa= 0.2) between the investigators who had limited prestudy exposure to CE. Celiac patients with extensive small bowel involvement had typical symptoms of malabsorption (diarrhea, weight loss) as opposed to mild and nonspecific symptoms in patients whose disease was limited to the proximal small bowel. CE was tolerated well by all study participants with 95% reporting absence of any discomfort. CONCLUSIONS: Although based on a small sample size, the study suggests that CE may be useful in assessing patients with CD. Familiarity with CE technology appears to be a critical factor affecting the accuracy of the test. Larger studies are warranted to more precisely define the advantages and limitations of CE in CD.
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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 | 0.064 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".