A133 QUALITY INDICATOR ADHERENCE FOR BARRETT’S ESOPHAGUS: A RETROSPECTIVE ANALYSIS
Bibliographic record
Abstract
Abstract Background Consensus guidelines advocate for quality indicator adherence in patients with Barrett’s Esophagus (BE). This includes documentation of landmarks/extent of BE, adherence to biopsy protocols and recommended surveillance intervals. Aims Evaluate adherence to established quality indicators for patients with BE in a tertiary referral centre. Methods Between 01/2012 - 01/2024, consecutive patients with intestinal metaplasia with goblet cells on esophageal biopsies were identified using a validated histopathology registry at St. Paul’s Hospital (Vancouver, BC, Canada). After confirming the diagnosis of BE (≥ 1cm of columnar epithelium above the top of the gastric folds on index esophagogastroduodenoscopy), quality indicator adherence was evaluated (documentation of landmarks/extent of BE (Prague Classification), adherence to biopsy protocols (Seattle Protocol) and recommended surveillance intervals). Continuous variables were summarised using median (IQR). Categorical variables were summarised as frequencies (%). Results Preliminary analysis between 01/2012 - 03/2015 identified 253 patients with BE. Median age was 61 years (IQR 17), with 196 (77.5%) being male. Of these, 81 patients were diagnosed with neoplastic BE (33.3% referred for neoplastic BE management; 24.7% at index esophagogastroduodenoscopy; 42.0% during surveillance). The median time to low-grade dysplasia, high-grade dysplasia and esophageal adenocarcinoma from BE diagnosis was 12 months (IQR 48 months), 13 months (IQR 47 months) and 48 months (IQR 33 months), respectively. At index or follow-up evaluation, landmark delineation/extent of BE was documented in 23.3%. Biopsy protocol adherence was 86.6%. Adherence to surveillance recommendations was 57.7%. Conclusions Quality Indicators for BE are poorly adhered to, outside of established biopsy protocols. Programmatic BE management may carry the potential to improve patient outcomes and resource utilization. Funding Agencies 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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".