Reduction of multitasking distractions underlies the higher adenoma detection rate of water exchange compared to air insufflation – blinded analysis of withdrawal phase videos
Bibliographic record
Abstract
Background: Experts have hypothesized that a reduction of multitasking distractions and improved bowel cleanliness can explain why insertion water exchange enhances adenoma detection rate. Objective: The purpose of this study was to test the role of both distractions during withdrawal and bowel cleanliness in enhancing adenoma detection rate using coded video records of colonoscopy. Methods: The withdrawal phase of videos of 299 consecutive colonoscopies from two randomized controlled trials comparing water exchange versus air insufflation at a regional hospital in Taiwan were coded. The primary outcome was distractions; activities that preclude full attention being paid to inspection of the mucosa for polyps. A single blinded reviewer collected the data. Results: There were significant agreements in inter-rater reliability indexes. Compared to air insufflation, water exchange had significantly fewer distractions; higher diagnostic yield (intervention time and number), adenoma detection rate, and Boston Bowel Preparation Scale score. Water exchange had a higher withdrawal technique score (predominantly adequacy of cleaning). The association between increased adenoma detection rate and water exchange was mediated by the number of distractions and withdrawal time, but not the Boston Bowel Preparation Scale score. Conclusion: The speculation by experts that a reduction of multitasking distractions underlies the significantly higher adenoma detection rate of water exchange is supported by the current study. Increased bowel cleanliness did not contribute to the increased adenoma detection rate by use of water exchange.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".