Impact of the introduction of formal D2 lymphadenectomy for gastric cancer in a Western setting
Bibliographic record
Abstract
Background: Two members from an academic tertiary hospital went to the National Cancer Institute in Tokyo, Japan, to learn how to perform an adequate D2 lymphadenectomy and to then introduce this technique in the surgical care of patients undergoing surgery for gastric cancer at a Western hospital. We aimed to compare the perioperative outcomes and long-term survival of Western patients who underwent gastric resection, performed by these 2 surgeons, before and after the surgeons' shortcourse technical training in Japan. Methods: We conducted a retrospective comparative study of all patients (n = 27 before training and n = 79 after training) who underwent gastric resection for cancer by the same 2 surgeons between September 2007 and December 2017 at the Centre Hospitalier Universitaire de Québec - Université Laval (Québec, Canada). We collected data on patient demographic, clinical, surgical, pathological and treatment characteristics, as well as long-term survival and complications. Results: In the post-training group, the number of sampled lymph nodes was higher (median 33 v. 14, p < 0.0001), but this increase did not result in a higher number of histologically positive lymph nodes (p = 0.35). The rate of complications was lower in the post-training group (15.2% v. 48.2%, p = 0.002). The hospital stay was shorter in the post-training group (11 [standard deviation (SD) 7] v. 23 [SD 45] d, p = 0.03). The median survival was higher in the post-training group (47 v. 29 mo, p = 0.03). Conclusion: These results suggest that a short-course technical training in D2 lymphadenectomy, completed in Japan, improved lymph node sampling, decreased postoperative complications and improved survival of patients undergoing surgery for gastric cancer in a Western setting.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".