Endoscopy in Barrett’s oesophagus: adherence to standards and neoplasia detection in the community practice versus hospital setting
Bibliographic record
Abstract
OBJECTIVE: Potential process differences between hospital and community-based endoscopy for Barrett's oesophagus have not been examined. We aimed at comparing adherence to guidelines and neoplasia detection rates in medical centres (MC) and community practices (CP). DESIGN: Retrospective analysis. SETTING: All histologically confirmed Barrett cases seen over a 3-year period in six MC and 19 CP covering a third of all upper gastrointestinal endoscopies (n = 126,000) performed annually in Berlin, Germany. MAIN OUTCOME MEASURE: Rate of relevant neoplasia (high-grade intraepithelial neoplasia or more) in both settings in relation to adherence to standards. RESULTS: Of 1317 Barrett cases, 66% were seen in CP. CP patients had a shorter mean Barrett length (2.6 cm vs. 3.8 cm; P < 0.001) with fewer biopsies taken during an examination (2.5 vs. 4.1 for Barrett length <or=2 cm; P < 0.001). CPs also provided fewer complete esophagogastroduodenoscopy documentation (25.1% vs. 57.8%, P < 0.001). Neoplasias were found more commonly in MCs compared to CPs (9.2% vs. 0.8%; P < 0.001). However, on exclusion of all referred patients with known neoplasia (65%) or those examined for other reasons (27.5%), the detection rate at MCs decreased to 1.3%, not different from the one seen at CPs (0.8%, P = 0.43). Only 13% were found during surveillance, but 57% were diagnosed at an early stage. CONCLUSIONS: Referral bias and not better adherence to guidelines could explain the higher neoplasia prevalence in Barrett's oesophagus at hospital centres. Despite a generally poor adherence to guidelines, most neoplasias found were at an early and potentially curable stage.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".