Context While perioperative mortality after pancreaticoduodenectomy is decreasing, key factors remain to be elucidated. Objective The purpose of this study was to investigate inpatient mortality after pancreaticoduodenectomy in the Nationwide Inpatient Sample (NIS), a representative inpatient database in the USA. Methdos Patient discharge data (diagnostic and procedure codes) and hospital characteristics were investigated for years 2009 and 2010. The inclusion criteria were a procedure code for pancreaticoduodenectomy, elective procedure, and a pancreatic or peripancreatic cancer diagnosis. Chisquare test determined statistical significance. A logistic regression model for mortality was created from significant variables. Results Two-thousand and 958 patients were identified with an average age of 65±12 years; 53% were male. The mean length of stay was 15±12 days with a mortality of 4% and a complication rate of 57%. Eighty-six percent of pancreaticoduodenectomy occurred in teaching hospitals. Pancreaticoduodenectomy performed in teaching hospitals in the first half of the academic year were associated with higher mortality than in the latter half (5.5% vs. 3.4%, P=0.005). On logistic regression analysis, non-surgical complications are the largest predictor of death (P<0.001) while operations in the latter half of the academic year are associated with decreased mortality (P<0.01). Conclusions The timing of pancreaticoduodenectomy for cancer remained more predictive of mortality than age or length of stay; only complications were more predictive of death than time of year. This suggests that there remains a clinically and statistically significant learning curve for trainees in identifying complications; further study is needed to prove that identification of complications leads to a decrease in mortality rate by taking corrective actions.
|Original language||English (US)|
|Number of pages||6|
|Journal||Journal of the Pancreas|
|Publication status||Published - 2013|
- Intraoperative complications
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism