Effect of Pancreatic Fistula on Recurrence and Long-Term Prognosis of Periampullary Adenocarcinomas after Pancreaticoduodenectomy
Bibliographic record
Abstract
Pancreatic fistula (PF) is common after pancreaticoduodenectomy (PD). Its effect on recurrence and survival is not known. Retrospective study of patients undergoing PD for periampullary adenocarcinomas (2000-2012). Standard statistical analyses were performed to determine the impact of PF on disease-free survival (DFS) and overall survival (OS). There were 634 PDs (pancreatic adenocarcinoma: 347, other periampullary adenocarcinomas: 287). Any-grade PF developed in 81/634 (13%). Perioperative mortality rate was 1.7 per cent (11/634), higher in patients with PF (10 vs 0.5%, P < 0.001). In multivariable analysis, PF significantly reduced DFS in pancreatic [hazard ratio (HR) = 1.6, 95% confidence-interval (CI): 1.1-2.6, P = 0.043] but not in other periampullary adenocarcinomas [HR = 1.3 (95% CI: 0.8-2.2), P = 0.45]. Positive lymph nodes, margins, and high-grade histology were associated with decreased DFS and OS. Adjuvant therapy was associated with improved OS in pancreatic [HR = 0.7 (95% CI: 0.5-0.9), P = 0.02] but not in other periampullary adenocarcinomas [HR = 1.14 (95% CI: 0.8-1.7), P = 0.49]. PF did not alter OS in either group. After PD, PF is associated with decreased DFS in pancreatic but not in other periampullary adenocarcinomas. This decrease DFS did not alter OS. Tumor grade, lymph nodes, and resection margin status are associated with DFS and OS.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".