Prevention of postoperative pancreatic fistula after pancreatectomy: results of a Canadian RAND/UCLA appropriateness expert panel
Bibliographic record
Abstract
BACKGROUND: We aimed to define the appropriateness of interventions for the prevention of postoperative pancreatic fistulas (POPF) after pancreatectomy, given the lack of consistent data on this topic. METHODS: Using the RAND/UCLA appropriateness method, we assembled an expert panel to rate clinical scenarios for interventions to prevent POPF after pancreaticoduodenectomy (PD) and distal pancreatectomy (DP). RESULTS: The following interventions were rated appropriate: individualized risk prediction for all patients; perioperative pasireotide administration for patients undergoing PD who have a soft pancreatic gland and a pancreatic duct size of less 3 mm and for patients undergoing DP; pancreaticogastrostomy for patients undergoing PD who have a soft pancreatic gland and pancreaticojejunostomy for PD for patients with a pancreatic duct size of 6 mm or greater regardless of pancreatic gland texture; duct-to-mucosa anastomosis for all patients undergoing PD and dunking anastomosis for patients undergoing PD who have a pancreatic duct size of less than 3 mm with a firm pancreatic gland; simple stapled and reinforced stapled transection for all DP; surgical drains for PD and DP in patients with a soft pancreatic gland; and open and minimally invasive surgery for DP and open surgery for PD. The following were rated inappropriate: gastrointestinal anastomosis for stump closure in all DP and omission of surgical drain in PD for patients with a pancreatic duct diameter less than 3 mm and a soft pancreatic gland. CONCLUSION: The expert panel identified appropriate and inappropriate scenarios for POPF prevention following pancreatectomy, to provide guidance to clinicians. However, the appropriateness of the interventions in the majority of the clinical scenarios was rated as uncertain, demonstrating equipoise.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".