Emergency Colorectal Surgery in Those with Cirrhosis: A Population-based Study Assessing Practice Patterns, Outcomes and Predictors of Mortality
Bibliographic record
Abstract
Abstract Background Those with cirrhosis who require emergency colorectal surgery are at risk for poor outcomes. Although risk predictions models exists, these tools are not specific to colorectal surgery, nor were they developed in a contemporary setting. Thus, the objective of this study was to assess the outcomes in this population and determine whether cirrhosis etiology and/or the Model for End Stage Liver Disease (MELD-Na) is associated with mortality. Methods This population-based study included those with cirrhosis undergoing emergent colorectal surgery between 2009 and 2017. All eligible individuals in Ontario were identified using administrative databases. The primary outcome was 90-day mortality. Results Nine hundred and twenty-seven individuals (57%) (male) were included. The most common cirrhosis etiology was non-alcoholic fatty liver disease (NAFLD) (50%) and alcohol related (32%). Overall 90-day mortality was 32%. Multivariable survival analysis demonstrated those with alcohol-related disease were at increased risk of 90-day mortality (hazards ratio [HR] 1.53, 95% confidence interval [CI] 1.2–2.0 vs. NAFLD [ref]). Surgery for colorectal cancer was associated with better survival (HR 0.27, 95%CI 0.16–0.47). In the subgroup analysis of those with an available MELD-Na score (n = 348/927, 38%), there was a strong association between increasing MELD-Na and mortality (score 20+ HR 6.6, 95%CI 3.9–10.9; score 10–19 HR 1.8, 95%CI 1.1–3.0; score <10 [ref]). Conclusion Individuals with cirrhosis who require emergent colorectal surgery have a high risk of postoperative complications, including mortality. Increasing MELD-Na score is associated with mortality and can be used to risk stratify individuals.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".