Related Experiment Video
Updated: May 27, 2026

Technical Detail for Robot Assisted Pancreaticoduodenectomy
Published on: September 28, 2019
Predicting the risk of perioperative mortality in patients undergoing pancreaticoduodenectomy: a novel scoring system
Raghunandan Venkat1, Milo A Puhan, Richard D Schulick
1Department of Surgery, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Objective:
To develop and validate a risk score to predict the 30- and 90-day mortality after a pancreaticoduodenectomy or total pancreatectomy on the basis of preoperative risk factors in a high-volume program.
Design:
Data from a prospectively maintained institutional database were collected. In a random subset of 70% of patients (training cohort), multivariate logistic regression was used to develop a simple integer score, which was then validated in the remaining 30% of patients (validation cohort). Discrimination and calibration of the score were evaluated using area under the receiver operating characteristic curve and Hosmer-Lemeshow test, respectively.
Setting:
Tertiary referral center.
Patients:
The study comprised 1976 patients in a prospectively maintained institutional database who underwent pancreaticoduodenectomy or total pancreatectomy between 1998 and 2009.
Main Outcome Measures:
The 30- and 90-day mortality.
Results:
In the training cohort, age, male sex, preoperative serum albumin level, tumor size, total pancreatectomy, and a high Charlson index predicted 90-day mortality (area under the curve, 0.78; 95% CI, 0.71-0.85), whereas all these factors except Charlson index also predicted 30-day mortality (0.79; 0.68-0.89). On validation, the predicted and observed risks were not significantly different for 30-day (1.4% vs 1.0%; P = .62) and 90-day (3.8% vs 3.4%; P = .87) mortality. Both scores maintained good discrimination (for 30-day mortality, area under the curve, 0.74; 95% CI, 0.54-0.95; and for 90-day mortality, 0.73; 0.62-0.84).
Conclusions:
The risk scores accurately predicted 30- and 90-day mortality after pancreatectomy. They may help identify and counsel high-risk patients, support and calculate net benefits of therapeutic decisions, and control for selection bias in observational studies as propensity scores.
