Laparoscopic versus Open Total Gastrectomy for Locally Advanced Gastric Cancer: Short and Long-Term Results
Bibliographic record
Abstract
BACKGROUND: Laparoscopic gastrectomy for early gastric cancer is widely accepted and routinely performed. However, it is still debated whether the laparoscopic approach is a valid alternative to open gastrectomy in advanced gastric cancer (AGC). The aim of this study is to compare short-and long-term outcomes of laparoscopic (LG) and open (OG) total gastrectomy with D2 lymphadenectomy in patients with AGC. METHODS: A retrospective comparative study was conducted on patients who underwent LG and OG for ACG between January 2015 and December 2021. Primary endpoints were the following: recurrence rate, 3-year disease-free survival, 3-year and 5-year overall survival. Univariate and multivariate analysis was conducted to compare variables influencing outcomes and survival. RESULTS: = 0.048). No differences in 3-year and 5-year overall survival; 3-year disease-free survival was improved in the LG group on the univariate analysis but not after the multivariate one. LG was associated with longer operative time, lower blood loss and shorter hospital stay. Lymph node yield was higher in LG. CONCLUSION: LG for AGC seems to provide satisfactory clinical and oncological outcomes in medium volume centers, improved postoperative results and possibly lower recurrence rates.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".