Use of warm carbon dioxide insufflators does not affect intra-colonic gas temperature and has no effect on polyp detection rate during colonoscopy – a randomized controlled trial
Bibliographic record
Abstract
Abstract Background and study aims Methods to improve polyp detection during colonoscopy have been investigated, with conflicting results for warm water irrigation. Carbon Dioxide (CO2) warmed to 37 °C may have similar or more pronounced effects on bowel motility. This study aimed to assess whether warmed CO2 would improve polyp detection compared to room temperature air insufflation. Patients and methods This was a double-blind, randomized controlled trial that enrolled 204 patients undergoing screening or surveillance outpatient colonoscopy. The primary outcome was polyp per patient detection rate. Secondary outcomes included adenoma per patient detection rates, bowel spasm, and patient comfort. Results The trial was terminated after an interim analysis determined futility. Between the warmed CO2 and room air groups, no significant differences were found in the per-colonoscopy polyp detection rate (P = 0.57); overall polyp detection rate (P = 0.69); or adenoma detection rates (P = 0.74). More patients in the room temperature group had lower spasm scores (p = 0.02); however, there was a trend towards greater patient comfort in the warmed CO2 group (P = 0.054). An ex-vivo study showed a significant difference between exiting CO2 temperature at the insufflator end vs. delivered CO2 temperature at the colonoscope tip end. The temperature of insufflation at the tip of the colonoscope was not different when using warmed vs. unwarmed insufflation (P = 0.62). Conclusion When compared with room air insufflation, warmed CO2 insufflation did not affect polyp detection rates.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".