Surgeon vs Pathologist for Prediction of Pancreatic Fistula: Results from the Randomized Multicenter RECOPANC Study
Bibliographic record
Abstract
BACKGROUND: Surgically assessed pancreatic texture has been identified as the strongest predictor of postoperative pancreatic fistula. However, texture is a subjective parameter with no proven reliability or validity. Therefore, a more objective parameter is needed. In this study, we evaluated the fibrosis level at the pancreatic neck resection margin and correlated fibrosis and all clinico-pathologic parameters collected over the course of the Pancreatogastrostomy vs Pancreatojejunostomy for RECOnstruction (RECOPANC) study. STUDY DESIGN: The RECOPANC trial was a multicenter randomized prospective trial of patients undergoing pancreatoduodenectomy. There were 261 hematoxylin and eosin-stained slides allocated for histopathologic analyses. Pancreatic fibrosis was scored from 0 to III (no fibrosis up to severe fibrosis) by 2 blinded independent pathologists. All variables possibly associated with POPF were entered into a generalized linear model for multivariable analysis. RESULTS: The fibrosis grade and pancreatic texture were scored in all 261 patients. In POPF B/C (postoperative pancreatic fistula grade B or C) patients, 71% had a soft pancreas, and fibrosis grades were distributed as follows: 48% with score 0, 28% with score I, 20% with score II, and 7% with score III, respectively. Fibrosis grading showed substantial inter-rater reliability (kappa = 0.74) and correlated positively with hard pancreatic texture (p < 0.05). In univariable analysis, area under the curve (AUC) for POPF B/C prediction was higher for fibrosis grade than for pancreatic texture (0.71 vs 0.59). In multivariate analysis, the following predictors were selected: sex, surgeon volume, pancreatic texture, and fibrosis grade. However, the addition of pancreatic texture only led to an incremental improvement (AUC 0.794 vs 0.819). CONCLUSIONS: Histologically evaluated pancreatic fibrosis is an easily applicable and highly reproducible POPF predictor and superior to surgically evaluated pancreatic texture. Future studies might use fibrosis grade for risk stratification in pancreatoduodenectomy.
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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 | 0.016 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".