Does aberrant hepatic arterial anatomy impact the complication rate or survival following resection of pancreatic adenocarcinoma?
Bibliographic record
Abstract
775 Background: Patients with aberrant hepatic arterial anatomy (AHAA) are susceptible to tumor invasion and/or ligation during resection of the pancreatic head. The purpose of this study is to determine if AHAA negatively impacts perioperative outcomes or survival. Methods: All patients who underwent either pancreaticoduodenectomy or total pancreatectomy for pancreatic ductal adenocarcinoma (PDAC) between 2005 and 2014 at our center were retrospectively reviewed. Univariate logistic regression was used to compare outcomes between patients with conventional hepatic arterial anatomy to those with AHAA. Survival analysis was performed by Kaplan-Meier method with log rank test. Results: During the study period, 330 patients underwent resection for PDAC, 69 (20.9%) with aberrant hepatic arterial anatomy. The presence of AHAA does not significantly increase operative time (p= 0.110) or length of stay (p=0.518). The overall frequency of complications (49.3% vs 37.9%, p=0.088) was higher in the AHAA group, but not significantly so. Certain postoperative complications are more common in the AHAA group, namely superficial surgical site infection (18.8% vs. 8.8%, p=0.018) and pancreatic fistula (18.8% vs. 10.0%, p=0.042). However, deep SSI, need for blood transfusion, respiratory failure, DGE, bleed from GDA/pseudoaneurysm, biliary fistula, chyle leak, PV thrombus, fascial dehiscence, and reoperation are not statistically different between the two groups. There is a trend for reduced overall survival in the AHAA group that is not statistically significant (p=0.11). Conclusions: Aberrant hepatic arterial anatomy is encountered in greater than 20% of pancreatic surgery patients, and its presence may increase the rate of certain postoperative complications such as superficial surgical site infection and pancreatic fistula.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".