Synoptic operative reports enhance documentation of best practices for rectal cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Implementation of best practices surgical checklists improves patient safety and outcomes. However, documenting performance of these practices can be challenging. The American Society of Colon and Rectal Surgeons developed a Best Practices for Rectal Cancer Checklist (RCC) to standardize and improve the quality of rectal cancer surgery. This study compared the degree to which synoptic (SR) and narrative (NR) operative reports document RCC items. METHODS: Two reviewers independently reviewed a cohort of prospectively collected SR for rectal cancer surgery and a case-matched historical cohort of NR. Reports were reviewed for documentation of performance of operative items on the RCC. Abstraction time and inter-rater agreement were also measured. RESULTS: SR scored significantly higher than NR on the overall checklist score (mean adjusted score ± standard deviation 12.4 ± 0.9 vs. 5.7 ± 1.9, maximum possible score 18, P < 0.001). Reviewers abstracted data significantly faster from SR. Inter-rater agreement between reviewers was high for both types of reports. CONCLUSIONS: SR were associated with reliable and more complete and reliable documentation of items on the RCC. Use of an SR system standardizes operative reporting, providing the opportunity to enhance checklist compliance, and enable timely feedback to improve surgical outcomes for rectal cancer patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it