Variable Endoscopist performance in proximal and distal adenoma detection during colonoscopy: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Adenoma Detection Rate (ADR) is a validated colonoscopy quality indicator. In addition to overall ADR, Distal and Proximal Adenoma Detection Rates may provide important colonoscopy quality information. The goal of this study is to determine the association between distal and proximal adenoma detection (AD) and to identify factors contributing to overall, distal, and proximal AD. METHODS: This is a retrospective cohort study of patients with a noted family history of CRC or positive fecal occult blood test who underwent a screening colonoscopy at a regional colorectal cancer (CRC) screening center between May 2009 and December 2011. Data regarding patient demographics, procedure details, endoscopist characteristics and polyp histology were captured. The main outcomes measured were overall, distal, and proximal AD. RESULTS: 1907 patients were included. The median age was 60 years and 42% were male. Endoscopist median overall ADR was 25% (30% male, 21% female). Endoscopist distal ADR was only modestly associated with their proximal ADR (Spearman Rank: 0.51 p = 0.11). Highest overall ADR (29 to 45%) was found for endoscopists whose distal and proximal ADRs were above the group median. In multivariate analysis, factors associated with overall, distal, and proximal AD included age, sex, and endoscopist practicing experience. CONCLUSION: Inclusion of distal and proximal ADRs, in addition to overall ADR, in colonoscopy quality assessment provides the more accurate feedback on endoscopist performance.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".