Interplay of Postpancreatectomy Acute Pancreatitis, Postoperative Pancreatic Fistula, and Mortality after Pancreatoduodenectomy: Insight from a Comprehensive Cohort Study of 1,594 Patients and Development of Predictive Nomograms.

Bhandare, Manish S; Nandy, Kunal; Parray, Amir M; Pawar, Akash; Padhy, Amita; Menon, Vishnu; Chopde, Amit; Chaudhari, Vikram et al. · J Am Coll Surg · 2026

retrospective_cohort · Level III

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Abstract

Postoperative pancreatic fistula (POPF) and postpancreatectomy acute pancreatitis (PPAP) remain the chief obstacles to optimal outcomes after pancreatoduodenectomy. The mechanistic link between PPAP, clinically relevant POPF (CR-POPF), and mortality resulting from the inability to rescue patients after complications has not been fully elucidated. This study retrospectively analyzed 1,594 consecutive pancreatoduodenectomies performed at a high-volume dedicated pancreatic surgery unit between January 2013 and July 2024. Predictors of PPAP, CR-POPF, and 90-day mortality were determined, and corresponding risk prediction nomograms were developed. A total of 571 patients (35.8%) experienced major morbidity. CR-POPF occurred in 24.3% (grade B 18.4%, grade C 5.9%), and 90-day mortality was 3.4% overall and 9.0% among patients with CR-POPF. PPAP was diagnosed in 10.8% and emerged as the dominant independent predictor of CR-POPF (odds ratio [OR] 11.76, p < 0.001), grade C POPF (OR 5.25, p < 0.001), and 90-day mortality (OR 4.88, p < 0.001). PPAP development was linked to preoperative cholangitis, soft gland texture, and duct diameter less than 3 mm. In the CR-POPF subgroup, failure to -rescue was driven by systemic inflammatory response syndrome (OR 15.05, p = 0.002), fungal sepsis, gram-negative contamination, bile leak, hemorrhage, and pulmonary complications. The dedicated failure-to-rescue nomogram showed an area under the curve of 0.973. PPAP is the pivotal trigger in the CR-POPF-mortality cascade after pancreatoduodenectomy. Refinements to existing fistula risk scores and incorporating PPAP into risk models will enable precise stratification. The developed high-fidelity nomograms can effectively identify patients at imminent risk of mortality, thereby facilitating rescue interventions, after external validation across diverse institutions.

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