Safety and efficacy of physician-administered balanced-sedation for the endoscopic mucosal resection of large non-pedunculated colorectal polyps
Bibliographic record
Abstract
Abstract Background and study aims Because of concerns about peri-procedural adverse events (AEs), guidelines recommend anesthetist-managed sedation (AMS) for long and complex endoscopic procedures. The safety and efficacy of physician-administered balanced sedation (PA-BS) for endoscopic mucosal resection (EMR) of large non-pedunculated colorectal polyps (LNPCPs) ≥20 mm is unknown. Patients and methods We compared PA-BS with AMS in a retrospective study of prospectively collected data from consecutive patients referred for management of LNPCPs (NCT01368289; NCT02000141). A per-patient propensity analysis was performed following a 1:2 nearest-neighbor (Greedy-type) match, based on age, gender, Charlson comorbidity index, and lesion size. The primary outcome was any peri-procedural AE, which included hypotension, hypertension, tachycardia, bradycardia, hypoxia, and new arrhythmia. Secondary outcomes were unplanned admissions, 28-day re-presentation, technical success, and recurrence. Results Between January 2016 and June 2020, 700 patients underwent EMR for LNPCPs, of whom 638 received PA-BS. Among them, the median age was 70 years (interquartile range [IQR] 62–76 years), size 35 mm (IQR 25–45 mm), and duration 35 minutes (IQR 25–60 minutes). Peri-procedural AEs occurred in 149 (23.4%), most commonly bradycardia (116; 18.2%). Only five (0.8%) required an unplanned sedation-related admission due to AEs (2 hypotension, 1 arrhythmia, 1 bradycardia, 1 hypoxia), with a median inpatient stay of 1 day (IQR 1–3 days). After propensity-score matching, there were no differences between PA-BS and AMS in peri-procedural AEs, unplanned admissions, 28-day re-presentation rates, technical success or recurrence. Conclusions Physician-administered balanced sedation for the EMR of LNPCPs is safe. Peri-procedural AEs are infrequent, transient, rarely require admission (<1%), and are experienced in similar frequencies to those receiving anesthetist-managed sedation.
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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 | 0.002 | 0.008 |
| 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) | 0.001 | 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".