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Published on: June 24, 2022
Risk-Stratified Pancreatectomy Clinical Pathway Implementation and Delayed Gastric Emptying
Natalia Paez Arango1, Laura R Prakash1, Yi-Ju Chiang1
1Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Unit 1484, Houston, TX, 77030, USA.
Background:
Delayed gastric emptying (DGE) is a frequent complication after pancreaticoduodenectomy (PD) that impairs recovery and quality of life. The purpose of this study was to assess the impact risk-stratified pancreatectomy clinical pathways (RSPCPs) had on delayed gastric emptying (DGE) and identify factors associated with DGE in a contemporary period.
Methods:
A single-institution, prospective database was queried for consecutive PDs during July 2011-November 2019. Using international definitions, DGE rates were compared between periods before and after RSPCPs were implemented in 2016, classifying patients according to their postoperative pancreatic fistula (POPF) risk. Risk factors were analyzed to identify modifiable targets.
Results:
Among 724 elective PDs, 552 (76%) were for adenocarcinoma and 172 (24%) for other diagnoses. Of the 197 (27%) patients with DGE, 119 (16%) had type A, 41 (6%) type B, and 38 (5%) type C. In the overall cohort, DGE rates were higher with pylorus-preserving vs. classic hand-sewn reconstruction (odds ratio [OR] - 1.84; p < 0.001), postoperative abscess (OR - 2.54; p = 0.003), and non-white patients (p = 0.007), but lower after implementation of RSPCPs (OR - 0.34, p < 0.001). In the 374 patients treated with RSPCPs, only 17% (n = 65/374) developed DGE. Patients with protocol-compliant NGT removal ≤ 48 h were less likely to experience DGE (OR - 1.46, p = 0.042).
Conclusion:
Our data suggest that implementation of preoperatively assigned RSPCPs as a care bundle was the most important factor in decreasing DGE. These gains were accentuated in patients who underwent early nasogastric tube removal and had a classic hand-sewn gastro-jejunostomy reconstruction. Application of these modifiable factors is generalizable with low implementation barriers.
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