Perioperative intraperitoneal chemotherapy for advanced gastric cancer
Bibliographic record
Abstract
Background-Aims: Perioperative intraperitoneal chemotherapy either under normothermia during the early postoperative period (EPIC) or intraoperatively combined with heat (HIPEC) has been shown to improve survival after radical resection of advanced gastric cancer. The purpose of the study is to compare the effect of EPIC and HIPEC in patients undergoing D 2 gastrectomy for advanced gastric cancer. Patients-Methods: Patients that received EPIC after D 2 gastrectomy were retrospectively compared to those that received HIPEC after D 2 gastrectomy. The end point of the study was the assessment of survival, and recurrences. Results: The groups were comparable for age, gender, performance status, tumor anatomic distribution, stage, degree of differentiation, Lauren classification, hospital mortality, morbidity, and type of surgery. 5-year survival rate for HIPEC group was 68% and for EPIC group was 14% ( p =0.0054).The recurrence rate in EPIC group was 57.9% and in HIPEC group 17.4% ( p =0.001). Conclusions: Patients with advanced gastric cancer undergoing D 2 gastrectomy in combination with HIPEC have improved survival and lower recurrence rate as compared to those undergoing D 2 gastrectomy in combination with EPIC.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".