Coaching Experienced and Trainee Colonoscopists in Insertion Water Exchange Colonoscopy in Female and Male Patients: A Process With Important Clinical and Academic Implications
Bibliographic record
Abstract
Introduction: Water exchange (WE), an innovative method to minimize insertion pain, serendipitously enhanced adenoma detection especially in the right colon. Concerns over initial data limited to males, long insertion time and potential to disrupt standard sedation practice, hampered its adoption in the U.S. Nevertheless, some experienced and trainee colonoscopists worldwide were willing to perform WE in a few cases each, supervised by a colonoscopist with experience in the method. Methods: Each coached colonoscopist handled the scope and performed the examination, while listening to real-time description of WE and its practical nuances. Ancillary procedures were based on local standards. Variables listed in Table 1, research projects and publications by participants since the beginning of these coaching exercises were tabulated (Table 2).Table 1: Details of Coaching ExercisesTable 2Results:Tables 1 & 2. Conclusion: Coaching of WE is feasible in both genders with comparable success rates, implying clinical benefits found in males are applicable to females. The experienced colonoscopists had significantly higher success and shorter mean cecal intubation time. A substantial proportion of patients completed without sedation, underscoring the ability of WE to minimize insertion pain, even in the hands of trainees. Funding and publication data indicate a rise in worldwide academic support of further in depth studies of WE.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".