Planned<i>versus</i>unplanned portal vein resections during pancreaticoduodenectomy for adenocarcinoma
Bibliographic record
Abstract
BACKGROUND: The management of portal vein (PV) involvement by pancreatic adenocarcinoma during pancreaticoduodenectomy (PD) is controversial. The aim of this study was to compare the outcomes of unplanned and planned PV resections as part of PD. METHODS: An analysis of PD over 11 years was performed. Patients who had undergone PV resection (PV-PD) were identified, and categorized into those who had undergone planned or unplanned resection. Postoperative and oncological outcomes were compared. RESULTS: Of 249 patients who underwent PD for pancreatic adenocarcinoma, 66 (26·5 per cent) had PV-PD, including 27 (41 per cent) planned and 39 (59 per cent) unplanned PV resections. Twenty-five of 27 planned PV resections were circumferential PV-PD, whereas 25 of 39 unplanned PV resections were partial PV-PD. Planned PV resections were performed in slightly younger patients (mean(s.d.) 60(9) versus 65(10) years; P = 0·031), and associated with longer operating times (mean(s.d.) 602(131) versus 458(83) min; P < 0·001) and more major complications (26 versus 5 per cent; P = 0·026). Planned PV resections were associated with a lower rate of positive margins (4 versus 44 per cent; P < 0·001) despite being carried out for larger tumours (mean(s.d.) 3·9(1·4) versus 2·9(1·0) cm; P = 0·002). There was no difference in survival between the two groups (P = 0·998). On multivariable analysis, margin status was a significant predictor of survival. CONCLUSION: Although planned PV resections for pancreatic adenocarcinoma were associated with higher rates of postoperative morbidity than unplanned resections, R0 resection rates were better.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".