A147 FACTORS ASSOCIATED WITH PATIENT COMFORT DURING ENDOSCOPIC RESECTION OF LARGE NON-PEDUNCULATED COLORECTAL POLYPS
Bibliographic record
Abstract
Abstract Background Patient comfort is an important quality indicator in endoscopy, as it relates to patient satisfaction and adherence with endoscopic surveillance recommendations. Endoscopic resection techniques are now the primary treatment strategy for LNPCPs. However, factors associated with patient comfort are unknown. Aims To assess patient comfort during endoscopic resection of LNPCPs and factors associated with discomfort. Methods Consecutive patients ampersand:003E 18 years of age who underwent endoscopic resection for a LNPCP were enrolled in a prospective single center observation cohort study (clinicaltrials.gov ID: NCT05402696). The St. Paul’s Endoscopic Comfort Scale (SPECS) was used to assess patient comfort (total score; vocalization, body language, anxiety sub-scores). Patient discomfort was defined as a SPECS total or sub-score above 0. Results Between 06/2022 - 07/2023, 258 patients underwent 276 procedures to remove 318 LNPCPs. Median age was 67.0 years and 126 (48.9%) were female. Most patients were ASA II (168, 57.3%) and 268 (97.1%) received conscious sedation with midazolam and/or fentanyl. Median SPECS score was 0 (IQR 1) with a range of 0 (145, 56.6%) to 5 (2, 0.8%). Challenging access and proximal LNPCP location were associated with overall discomfort and vocalization respectively (both p ampersand:003C 0.03). Highest rate of discomfort corresponded to lesions with difficult reach and easy positioning (70.6% of patients with these lesions had SPECSampersand:003E0). Lesion size, resection technique or resection duration were not associated with discomfort. Conclusions Minimally invasive endoscopic resection techniques can be performed without patient discomfort in most patients with LNPCPs. Challenging access and proximal location should be taken into consideration when administering sedation. Funding Agencies None Gastrointestinal Oncology
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".