Practice recommendations for the use of sedation in routine hospital-based colonoscopy
Bibliographic record
Abstract
Objective: Although sedation improves patient experience during colonoscopy, there is great jurisdictional variability in sedative practices. The objective of this study was to develop practice recommendations for the use of moderate and deep sedation in routine hospital-based colonoscopy to facilitate standardisation of practice. Design: We recruited 32 multidisciplinary panellists to participate in a modified Delphi process to establish consensus-based recommendations for the use of sedation in colonoscopy. Panel members participated in a values assessment survey followed by two rounds of anonymous online voting on preliminary practice recommendations. An inperson meeting was held between voting rounds to facilitate consensus-building. Consensus was defined as >60% agreement/disagreement with recommendation statements; >80% agreement/disagreement was considered indicative of strong consensus. Results: Twenty-nine panellists participated in the values assessment survey. Panellists ranked all factors presented as important to the development of practice recommendations. The factor considered most important was patient safety. Patient satisfaction, procedural efficiency, and cost were considered less important. Strong consensus was achieved for all nine practice recommendations presented to the panel. These recommendations included that all endoscopists be able to perform colonoscopy with moderate sedation, that an endoscopist and a single trained nurse are sufficient for performing colonoscopy with moderate sedation, and that anaesthesia-provided deep sedation be used for select patients. Conclusion: The recommendations presented in this study were agreed on by a multidisciplinary group and provide guidance for the use of sedation in routine hospital-based colonoscopy. Standardised sedation practices will promote safe, effective, and efficient colonoscopy for all patients.
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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 | 0.063 | 0.133 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".