Experience with water-aided colonoscopy in a Canadian community population
Bibliographic record
Abstract
Purpose: Water-aided colonoscopy, immersion (WI) or exchange (We), minimizes insertion pain and reduces sedation. We improves adenoma detection rates (ADR). In a performance improvement program, we assessed water-aided methods in a busy community GI practice in c anada. Methods: Over a 13 month period patients were offered water-aided colonoscopy with an option to complete the examination with on-demand sedation. WI was used in the first 1-2 months and replaced exclusively with W e thereafter. procedural outcomes were compared to a continuous retrospective cohort of standard sedated air insufflation (AI) colonoscopy. Results: 200 (106M/94F) water-aided colonoscopies were completed. cecal intubation without air insufflation was achieved in 93%. sedation was not required in 95% of patients accepting on-demand sedation. Average insertion time was 15 min with an average withdrawal time of 6 min. 145 (87M/58F) water-aided colonoscopies, completed for screening or surveillance were compared to a cohort of 145 (77M/68F) AI colonoscopies in the immediate prior period. The overall ADR of water-aided colonoscopy was 30% (43/145) with a proximal ADR of 21%. Using AI the overall ADR was 27.6% (40/145) with a proximal ADR of 14.5% (21/145). In males, the proximal colon ADR was 25% in water-aided colonoscopies and 14.3% using AI (p=0.0397). Conclusions: Water-aided colonoscopy is feasible in a busy community practice with respectable cecal intubation rates. A large percentage of patients consenting to on-demand sedation completed without sedation. ADR in male subjects is consistent with similar prior reports of a significantly higher ADR in the proximal colon using W e when compared to AI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".