Do we really need an anesthesiologist for routine colonoscopy in American Society of Anesthesiologist 1 and 2 patients?
Bibliographic record
Abstract
PURPOSE OF REVIEW: In an era where healthcare costs are being heavily scrutinized, every expenditure is reviewed for medical necessity. Multiple national gastroenterology societies have issued statements regarding whether an anesthesiologist is necessary for routine colonoscopies in American Society of Anesthesiologist (ASA) 1 and 2 patients. RECENT FINDINGS: A large percentage of patients are undergoing screening colonoscopy without any sedation at all, which would not require an independent practitioner to administer medications. Advances in technique and technology are making colonoscopies less stimulating. Advantages to administering sedation, including propofol, have been seen even when not administered under the direction of an anesthesiologist and complications seem to be rare. The additional cost of having monitored anesthesia care appears to be a driving factor in whether a patient receives it or not. SUMMARY: A large multiinstitutional randomized control trial would be necessary to rule out potential confounders and to determine whether there is a safety benefit or detriment to having anesthesiologist-directed care in the setting of routine colonoscopies in ASA 1 and 2 patients. Further discussion would be necessary regarding what the monetary value of that effect is if a small difference were to be detected.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".