Utility of intraoperative pathology consultations of whipple resection specimens and their impact on final margin status
Bibliographic record
Abstract
The resection margin status is a significant surgical prognostic factor for the long-term outcomes of patients undergoing pancreaticoduodenectomy (Whipple procedure). As a result, surgeons frequently rely on intraoperative consults (IOCs) involving frozen sections to evaluate margin clearance during these resections. Nevertheless, the impact of this practice on final margin status and long-term outcomes remains a topic of debate. This study aimed to assess the impact of IOCs on the clearance rate of resection margins following Whipple procedure and distal pancreatectomy. A retrospective database review of all patients who underwent Whipple procedure or distal pancreatectomy at our institution between 2018 and 2020 was performed to evaluate the utility of IOCs by gastrointestinal surgeons and its correlation with final postoperative surgical margin status. A significant variation in the frequency of IOC requests for margins among surgeons was noted. However, the use of frozen section analysis for intraoperative margin assessment was not significantly associated with the clearance rate of final post-operative margins. More frequent use of IOC did not result in higher final margin clearance rate, an important prognostic factor following Whipple procedure.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".