Does liver cirrhosis affect the surgical outcome of primary colorectal cancer surgery? A meta-analysis
Bibliographic record
Abstract
PURPOSE: The purpose of this meta-analysis was to evaluate the effect of liver cirrhosis (LC) on the short-term and long-term surgical outcomes of colorectal cancer (CRC). METHODS: The PubMed, Embase, and Cochrane Library databases were searched from inception to March 23, 2021. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of enrolled studies, and RevMan 5.3 was used for data analysis in this meta-analysis. The registration ID of this current meta-analysis on PROSPERO is CRD42021238042. RESULTS: In total, five studies with 2485 patients were included in this meta-analysis. For the baseline information, no significant differences in age, sex, tumor location, or tumor T staging were noted. Regarding short-term outcomes, the cirrhotic group had more major complications (OR=5.15, 95% CI=1.62 to 16.37, p=0.005), a higher re-operation rate (OR=2.04, 95% CI=1.07 to 3.88, p=0.03), and a higher short-term mortality rate (OR=2.85, 95% CI=1.93 to 4.20, p<0.00001) than the non-cirrhotic group. However, no significant differences in minor complications (OR=1.54, 95% CI=0.78 to 3.02, p=0.21) or the rate of intensive care unit (ICU) admission (OR=0.76, 95% CI=0.10 to 5.99, p=0.80) were noted between the two groups. Moreover, the non-cirrhotic group exhibited a longer survival time than the cirrhotic group (HR=2.96, 95% CI=2.28 to 3.85, p<0.00001). CONCLUSION: Preexisting LC was associated with an increased postoperative major complication rate, a higher rate of re-operation, a higher short-term mortality rate, and poor overall survival following CRC surgery.
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How this classification was reachedexpand
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.019 | 0.026 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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; both teacher heads agree on what is shown here.
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".