Patient comfort scores do not affect endoscopist behavior during colonoscopy, while trainee involvement has negative effects on patient comfort
Bibliographic record
Abstract
Abstract Introduction Patient comfort is an important part of endoscopy and reflects procedure quality and endoscopist technique. Using the validated, Nurse Assisted Patient Comfort Score (NAPCOMS), this study aimed to determine whether the introduction of NAPCOMS would affect sedation use by endoscopists. Patients and methods The study was conducted over 3 phases. Phase One and Two consisted of 8 weeks of endoscopist blinded and aware data collection, respectively. Data in Phase Three was collected over a 5-month period and scores fed back to individual endoscopists on a monthly basis. Results NAPCOMS consists of 3 domains – pain, sedation, and global tolerability. Comparison of Phase One and Two, showed no significant differences in sedative use or NAPCOMS. Phase Three data showed a decline in fentanyl use between individual months (P = 0.035), but no change in overall NAPCOMS. Procedures involving trainees were found to use more midazolam (P = 0.01) and fentanyl (P = 0.01), have worse NAPCOMS scores, and resulted in longer procedure duration (P < 0.001). Data comparing gastroenterologists and general surgeons showed increased fentanyl use (P = 0.037), decreased midazolam use (P = 0.001), and more position changes (P = 0.002) among gastroenterologists. Conclusions The introduction of a patient comfort scoring system resulted in a decrease in fentanyl use, although with minimal clinical significance. Additional studies are required to determine the role of patient comfort scores in quality control in endoscopy. Procedures completed with trainees used more sedation, were longer, and had worse NAPCOMS scores, the implications of which, for teaching hospitals and training programs, will need to be further considered.
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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 | 0.005 |
| 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) | 0.003 | 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".