Analysis of mortality in colorectal surgery in the Bi‐National Colorectal Cancer Audit
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: In the last decade, there has been a significant increase in interest for public reporting of outcome data and performance comparison across institutions and surgeons. This study aims at comparing postoperative mortality after colorectal cancer surgery across units and individual consultants in Australia and New Zealand using funnel plots. METHODS: The Bi-National Colorectal Cancer Audit database was used. Unadjusted and adjusted funnel plots of inpatient mortality were constructed. Risk adjustment was based upon multivariable logistic regression models using purposeful covariate selection. RESULTS: A total of 10 008 patients undergoing surgery for colorectal cancer from 56 surgical units and 90 consultants were identified. Overall inpatient mortality was 1.51%, corresponding to 1.1% for elective and 3.9% for urgent cases. Logistic regression identified age, American Society of Anesthesiologists score, urgent surgery and open surgery to be independently associated with inpatient mortality. Unadjusted and adjusted funnel plot analysis identified three (5.3%) units exceeding the inner limit and none exceeding the outer limit. Six (6.6%) consultants had inpatient mortality between the upper inner and outer limits and one (1.1%) between the inferior inner and outer limits. Upon adjustment, seven (7.7%) consultants had inpatient mortality between the inner and outer limit. Potential limitations of this study include: residual confounding being responsible for the association of open surgery and mortality; incomplete case-mix adjustment resulting in outlier identification; and bias towards inclusion of larger institutions. CONCLUSION: Mortality figures in Australia and New Zealand are comparable to recently reported international data. The vast majority of units and consultants are performing within the expected boundaries.
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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it