BACKGROUND

Robotic pancreatoduodenectomy (RPD) technology is developing rapidly, but there is still a lack of a specific and objective difficulty evaluation system in the field of application and training of RPD surgery.

METHODS

The clinical data of patients who underwent RPD in our hospital from November 2014 to October 2020 were analyzed retrospectively. Univariate and multivariate logistic regression analyses were used to determine the predictors of operation difficulty and convert into a scoring system.

RESULTS

A total of 72 patients were enrolled in the group. According to the operation time (25%), intraoperative blood loss (25%), conversion to laparotomy, and major complications, the difficulty of operation was divided into low difficulty (0-2 points) and high difficulty (3-4 points). The multivariate logistic regression model included the thickness of mesenteric tissue (P1) ( = 0.035), the thickness of the abdominal wall (B1) ( = 0.017), and the preoperative albumin ( = 0.032), and the nomogram was established. AUC = 0.773 (0.645-0.901).

CONCLUSIONS

The RPD difficulty evaluation system based on the specific anatomical relationship between da Vinci's laparoscopic robotic arm and tissues/organs in the operation area can be used as a predictive tool to evaluate the surgical difficulty of patients before operation and guide clinical practice.