Pancreaticoduodenectomy with multivisceral resection: Is it worthwhile? A 10-year experience at a tertiary care centre
Bibliographic record
Abstract
Background: Patients with pancreatic cancer only have a chance of a cure through a curative resection. However, this is not performed in most patients because the tumour is widespread, multivisceral involvement is thought to be incurable, or the procedure is too risky. Aims: To evaluate the outcomes of pancreaticoduodenectomy with and without multi-visceral resections in patients with locally advanced pancreatic cancer, specifically examining short-term outcomes and long-term survival rates. The study seeks to determine if patients who undergo more extensive surgery involving adjacent organs have a survival benefit despite higher operative mortality. Materials and Methods: We examined, from our prospectively maintained database, the outcome of patients between 2010 and 2020 who had undergone pancreatectomy for locally advanced lesions that also needed resection of one or more adjacent involved organs and compared their short-term outcome with those who underwent pancreatectomy alone and whether any of them survived years. Results: There were a total of 360 patients who underwent Whipple’s pancreaticoduodenectomy (WP) during the study period, of whom 343 patients (95%) had standard procedures and 17 patients (5%) had additional multivisceral resections (MVRs). The colon was the most frequently resected organ in 11 (65%) of the patients who had Whipples pancreaticoduodenectomy with multivisceral (WPMVR) resections. The overall mortality (in-hospital and long-term) was higher in the WPMVR group compared to the WP group (5/17, 30%) versus (22/343, 6%) ( P ≤ 0.05), and the morbidity was found to be comparable in both groups: 3 (18%) versus 158 (44%) ( P ≤ 0.05). However, of the 12 patients who had undergone WPMVR, to our surprise, seven survived for 5 years. Conclusions: Although patients with pancreatic cancer who undergo MVRs have higher operative mortality, a number, albeit small, may have long-term survival.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".