Quality of Capsule Endoscopy Reporting in Patients Referred for Double Balloon Enteroscopy
Bibliographic record
Abstract
Background: Abnormal video capsule endoscopy (VCE) findings often require intervention with double balloon enteroscopy (DBE). Accurate VCE reporting is important for procedural planning. In 2017 the American Gastroenterological Association (AGA) published a guideline that included recommended elements for VCE reporting. The aim of this study was to examine adherence to the AGA reporting guidelines for VCE. Methods: The medical records of all patients who underwent DBE at a tertiary academic center between February 1, 2018, and July 1, 2019, were retrospectively reviewed to identify the VCE report that prompted DBE. Data were collected on the presence of each reporting element recommended by the AGA. Differences in reporting between academic and private practices were compared. Results: A total of 129 VCE reports were reviewed (84 private practice and 45 academic practice). Reports consistently included indication, date, endoscopist, findings, diagnosis, and management recommendations. Timing of anatomic landmarks and abnormalities were included in only 87.6% of reports and preparation quality in only 26.2%. Reports from private practice groups were significantly more likely to include the type of capsule (P < 0.001). VCE reports from academic centers were more likely to include adverse outcomes (P < 0.001), pertinent negatives (P = 0.0015), extent of exam (P = 0.009), previous investigations (P = 0.045), medications (P < 0.001), and document communication to patient/referring physician (P = 0.001). Conclusions: Most VCE reports in both private and academic settings included the important elements recommended by the AGA; however only 87% listed the times of landmarks and abnormal findings, which are crucial in determining the type and direction of approach for subsequent interventions. It is unclear whether the quality of VCE reporting influences the outcome of subsequent DBE.
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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 | 0.014 | 0.115 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 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".