Visceral obesity and anastomotic leakage rates in colorectal cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Numberous studies have heatedly discussed whether obesity is a risk factor for anastomotic leakage (AL) because of the increasing number of colorectal cancer (CRC) cases and high incidence of CRC in patients with obesity. Objective We aimed to explore the relationship between visceral obesity(VO) and AL after CRC surgery. The databases of Pubmed, Embase, and the Cochrane Library were searched for relevant data and articles published until November 1, 2022. We identified the difference in the incidence of AL after CRC surgery between patients with and without VO. The quality of included studies was evaluated using the Newcastle- Ottawa Scale, and odds ratio (OR) and 95% CI were used to assess the association between VO and AL. Results This meta-analysis included 7 studies with 2,136 patients. The OR of patients with VO versus those without VO was 2.15 (95%CIs = 1.46–3.15, test for heterogeneity: P = 0.29, I2 = 18%) based on the fixed-effect model in seven studies. Notably, the difference between the two groups was statistically significant (Z = 3.91 P < 0.0001). Patients with VO in the colon cancer group exhibited a higher incidence of AL (OR = 2.88, 95% CIs = 1.38–5.99, test for heterogeneity: P = 0.27, I2 = 20%) than those in the rectal cancer group (OR = 2.74, 95% CIs = 1.13–6.65, test for heterogeneity: P = 0.20, I2 = 38%). In the studies in the relevant literature, heterogeneity was low. Regarding patients with VO, four Asian studies reported increased morbidity due to AL (OR = 2.79, 95% CIs = 1.35–5.78, test for heterogeneity: P = 0.35, I2 = 9%) compared with three non-Asian studies. Conclusions Our findings confirmed the significant relationship between VO and AL. Thus, VO could be considered a reliable risk factor of surgery for colon cancer.
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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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.036 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".