Pilot Study of the Quality Initiative in Rectal Cancer Strategy
Bibliographic record
Abstract
INTRODUCTION: Total mesorectal excision vs. traditional surgical techniques may lead to improved rates of permanent colostomy, local tumor recurrence, and survival for patients undergoing major rectal cancer operations. We developed the surgeon-directed, multipronged Quality Initiative in Rectal Cancer strategy to encourage surgeons to use total mesorectal excision techniques. METHODS: The Quality Initiative in Rectal Cancer strategy interventions included a workshop, an operative demonstration of total mesorectal excision, and a postoperative questionnaire. The design of the strategy was informed by the industrial theory principles of continuous quality improvement. We assessed the logistics of implementing the strategy and the attitudes of surgeons toward the strategy through a pilot study at three community hospitals in the Central-West region of Ontario. RESULTS: Seventeen of 19 surgeons participated in a workshop, and 12 of 17 workshop participants received at least one operative demonstration of total mesorectal excision. Ten of 11 surgeons who completed a postoperative questionnaire indicated their traditional approach to rectal cancer surgery varied with that of the operative demonstration. The attitudes of surgeons toward the Quality Initiative in Rectal Cancer strategy were positive. For the time periods before and after the pilot study, there was a trend toward a lower rate of permanent colostomy among patients treated by surgeons who participated in both the workshop and an operative demonstration of total mesorectal excision. CONCLUSION: The Quality Initiative in Rectal Cancer strategy may be an effective method of introducing optimal rectal cancer surgery techniques to a large group of practicing surgeons.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".