Incidence of Postoperative Diabetes Mellitus After Roux-en-Y Reconstruction for Gastric Cancer: Retrospective Single-Center Cohort Study
Bibliographic record
Abstract
Background: Sleeve gastrectomy is an effective surgical option for morbid obesity, and it improves glucose homeostasis. In patients with gastric cancer and type 2 diabetes mellitus (DM), gastrectomy, including total gastrectomy, is beneficial for glycemic control. Objective: This study aims to clarify the effects of gastrectomy and different reconstructive techniques on the incidence of postoperative DM in patients with gastric cancer. Methods: This retrospective, single-center, cohort study included 715 patients without DM who underwent total gastrectomy at the Tokyo Metropolitan Bokutoh Hospital between August 2005 and March 2019. Patients underwent reconstruction by Roux-en-Y (RY) gastric bypass or other surgical techniques (OT), with DM onset determined by hemoglobin A1c levels or medical records. Analyses included 2-sample, 2-tailed t tests; χ2 tests; and the Kaplan-Meier method with log-rank tests to compare the onset curves between the RY and OT groups, along with additional curves stratified by sex. A Swimmer plot for censoring and new-onset DM was implemented. Results: Stratified data analysis compared the RY and OT reconstruction methods. The hazard ratio was 1.52 (95% CI 1.06-2.18; P=.02), which indicated a statistically significant difference in the incidence of new-onset diabetes between the RY and OT groups in patients with gastric cancer. The hazard ratio after propensity score matching was 1.42 (95% CI 1.09-1.86; P=.009). Conclusions: This first-of-its-kind study provides insight into how different methods of gastric reconstruction affect postoperative diabetes. The results suggest significant differences in new-onset DM after surgery based on the reconstruction method. This research highlights the need for careful surgical planning to consider potential postoperative DM, particularly in patients with a family history of DM. Future studies should investigate the role of gut microbiota and other reconstructive techniques, such as laparoscopic jejunal interposition, in developing postoperative DM.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".