A147 ENDOSCOPIST FEEDBACK IS ASSOCIATED WITH IMPROVEMENTS IN COLONOSCOPY QUALITY INDICATORS: A SYSTEMATIC REVIEW AND META-ANALYSIS
Bibliographic record
Abstract
Abstract Background Colonoscopy quality indicators such as adenoma detection rate (ADR) are surrogates for the effectiveness of screening-related colonoscopy. Endosocpist feedback may be associated with improvements in ADR and other quality indicators. Aims To conduct a systematic review and meta-analysis to determine whether an association exists between endoscopist feedback and improvements in colonoscopy quality indicators. Methods An electronic and manual search was conducted through May 2019 for studies reporting on endoscopist feedback and associations with ADR or other colonoscopy quality indicators. Studies primarily assessing the effect of audit and feedback on trainees and studies that included interventions other then feedback were excluded from the analysis. Pooled rate ratios (RR) and weighted mean differences (WMD) were calculated using DerSimonian and Laird random effects models. Subgroup, sensitivity and meta-regression analyses were performed to assess for potential methodological or clinical factors associated with outcomes. Results Of 1,326 initial studies, 12 studies were included in the meta-analysis for ADR, representing 33,184 colonoscopies. Endoscopist feedback was associated with an improvement in ADR (RR 1.21, 95% confidence interval, CI, 1.09 to 1.34). Low performers derived a greater benefit from feedback (RR 1.62, 95% CI 1.18 to 2.23) compared to moderate performers (RR 1.19, 95% CI 1.11 to 1.29), while high performers did not derive a significant benefit (RR 1.06, 95% CI 0.99 to 1.13). Feedback was not associated with increases in withdrawal time (WMD +0.43 minutes, 95% CI -0.50 to +1.36 minutes) or improvements in cecal intubation rate (RR 1.00, 95% CI 0.99 to 1.01). Conclusions Endoscopist feedback is associated with modest improvements in ADR. Routine audit and feedback may be a feasible strategy to optimize outcomes in screening colonoscopy. 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 | 0.019 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.054 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".