PREDICTIVE RISK MODEL FOR POSTOPERATIVE PANCREATIC FISTULA AFTER PANCREATODUODENECTOMY
DOI:
https://doi.org/10.11603/2414-4533.2025.2.15362Keywords:
pancreatoduodenectomy, postoperative pancreatic fistula, computed tomography, prediction, risk stratification, pancreatic density, main pancreatic duct, body mass indexAbstract
The aim of the work: to develop and validate a predictive scoring system for assessing the risk of clinically relevant postoperative pancreatic fistula (CR-POPF) based on objective computed tomography (CT) characteristics of the pancreas and patient clinical parameters.
Materials and Methods. This prospective study included 234 patients who underwent pancreatoduodenectomy (PD) at the Shalimov National Institute of Surgery and Transplantology between January 2022 and November 2023. All patients underwent preoperative multiphase contrast-enhanced CT of the abdominal organs. Pancreatic parenchymal density was measured in Hounsfield units (HU) on non-contrast images, and the duct-to-parenchyma (D/P) ratio was assessed in ventrodorsal and craniocaudal planes. POPF was diagnosed according to the International Study Group on Pancreatic Fistula (ISGPF) criteria, and only clinically relevant cases (types B and C) were analyzed. ROC analysis was used to evaluate the predictive value of variables, including AUC calculation, optimal threshold determination, and multivariate logistic regression.
Results. Clinically relevant POPF was diagnosed in 44 patients (18.8 %), with 28 cases (63.6 %) of type B and 16 cases (36.4 %) of type C. Univariate analysis revealed statistically significant differences between patients with and without POPF. The median pancreatic density was significantly lower in the POPF group (22 vs. 39.65 HU; p<0.00001), and the D/P ratio was also significantly lower in both planes. Patients who developed POPF had smaller main duct diameters and higher BMI values (p<0.01). Based on multivariate analysis, a 6-point predictive model was developed that includes five independent predictors: pancreatic density ≤30 HU (2 points), D/P ratio ≤0.2 in ventrodorsal and craniocaudal planes (1 point each), main duct diameter <3 mm (1 point), and BMI ≥25 kg/m² (1 point). The model demonstrated high discriminatory ability (AUC=0.89) and allowed for effective patient risk stratification: low risk (0–2 points, 4.6 %), moderate risk (3 points, 27.8 %), high risk (4 points, 50 %), and very high risk (5–6 points, 82.5 %).
Conclusions. The proposed system is an effective tool for individualized preoperative risk assessment, enabling tailored surgical planning based on the patient’s risk profile. Depending on the risk level, differentiated management strategies may be applied–from standard techniques in low-risk patients to complex approaches in high-risk patients, including modified anastomotic techniques, external drainage, duct stenting, and pharmacologic prophylaxis.
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