Relationship between body mass index and short-term postoperative prognosis in patients undergoing colorectal cancer surgery
Bibliographic record
Abstract
BACKGROUND: Obesity is a state in which excess heat is converted into excess fat, which accumulates in the body and may cause damage to multiple organs of the circulatory, endocrine, and digestive systems. Studies have shown that the accumulation of abdominal fat and mesenteric fat hypertrophy in patients with obesity makes laparoscopic surgery highly difficult, which is not conducive to operation and affects patient prognosis. However, there is still controversy regarding these conclusions. AIM: To explore the relationship between body mass index (BMI) and short-term prognosis after surgery for colorectal cancer. METHODS: PubMed, Embase, Ovid, Web of Science, CNKI, and China Biology Medicine Disc databases were searched to obtain relevant articles on this topic. After the articles were screened according to the inclusion and exclusion criteria and the risk of literature bias was assessed using the Newcastle-Ottawa Scale, the prognostic indicators were combined and analyzed. RESULTS: = 0.08]. Subgroup analysis revealed that the geographical location of the institute was one of the sources of heterogeneity. Robot-assisted surgery was not significantly different from traditional laparoscopic resection in terms of the incidence of complications. CONCLUSION: Obesity increases the overall complication and SSI rates of patients undergoing colorectal cancer surgery but has no influence on the incidence of anastomotic leak, reoperation rate, and short-term mortality rate.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".