Visceral to subcutaneous fat area ratio predicts early postoperative small bowel obstruction after total gastrectomy for cardia cancer
Bibliographic record
Abstract
OBJECTIVE: We aimed to investigate the relationship between the visceral to subcutaneous fat area ratio (V/S ratio) and incidence of early postoperative small bowel obstruction (EPSBO) following total gastrectomy for cardia cancer. METHODS: We conducted a retrospective analysis among patients with cardia cancer who underwent elective total gastrectomy with esophagojejunostomy Roux-en-Y anastomosis at Nanjing Yimin Hospital between November 2019 and April 2024. Preoperative, intraoperative, and postoperative factors were meticulously monitored. The V/S ratio was calculated using computed tomography scans at the umbilical level with Slice-O-Matic software (Tomovision, Montreal, Canada). Statistical analyses included logistic regression and receiver operating characteristic (ROC) curve analysis. RESULTS: Among 175 patients, 27 (15.4%) developed EPSBO. The V/S ratio was significantly higher in the EPSBO group (1.76 ± 1.05 vs. 1.01 ± 0.54). Logistic regression identified the V/S ratio as a significant predictor of EPSBO (odds ratio [OR] = 1.612, 95% [CI]: 1.102-1.605). ROC curve analysis demonstrated high sensitivity (92%) and specificity (100%) for the V/S ratio in predicting EPSBO, with a 0.83 AUC. CONCLUSIONS: Our findings indicated a higher V/S ratio was a significant predictor of EPSBO following total gastrectomy for cardia cancer. Preoperative assessment of the V/S ratio can inform risk stratification and guide targeted interventions to improve postoperative outcomes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".