Novel Calculator to Estimate the Risk of Clinically Relevant Postoperative Pancreatic Fistula Following Distal Pancreatectomy

Background Drain management algorithms are based on studies that predict clinically relevant postoperative pancreatic fistula (CR-POPF) using drain fluid amylase level on POD1 (DFA1). These studies are focused on pancreaticoduodenectomy which is inherently different than distal pancreatectomy. Moreover, the change of DFA between POD1 and POD3 (Delta DFA) is underutilized despite its importance in predicting CR-POPF. We sought to generate a calculator that estimates the risk of CR-POPF following distal pancreatectomy. Methods The 2014-2018 pancreas-targeted ACS-NSQIP database was used to identify patients who underwent elective distal pancreatectomy. Models to predict CR-POPF were constructed using DFA1 with/without Delta DFA. The fittest model was used to construct a calculator. Results Out of 12,042 distal pancreatectomies, 692 patients met the study's inclusion criteria. The risk of CR-POPF was 15.9% in the included cohort versus 14.8% in the excluded one (P = 0.421). The predictors of the CR-POPF were age, operative time, DFA1, and Delta DFA. Adding Delta DFA decreased the Akaike's information criterion of the model (507.7 vs 544.7)-indicating a significantly better model fit-and improved the cross-validated area under the curve from 0.731 to 0.791. An easy-to-use calculator was created for surgeons to estimate the risk of CR-POPF based on the abovementioned variables. A sensitivity/specificity table was created at various cutoffs to direct clinical decision-making with respect to early drain removal. Conclusions This study highlights the importance of Delta DFA, in addition to DFA1, in predicting CR-POPF. The provided calculator will facilitate predicting CR-POPF and postoperative drain management following distal pancreatectomy.

Automated summary

This study emphasizes the importance of Delta DFA in predicting CR-POPF following distal pancreatectomy and provides a calculator to facilitate prediction and postoperative drain management.