Risk prediction models for difficult cholecystectomy

Abstract

Introduction In some cases, laparoscopic cholecystectomy (LC) may be very difficult and easily converted to laparotomy, causing many complications to patients and prolonging the prognosis time. Thus, to evaluate the difficulty of LC before operation is extremely important. Aim To explore the risk factors of difficult cholecystectomy (DC) and to establish a risk prediction model of DC. Material and methods The data of 201patients who underwent cholecystectomy from 1 January 2018 to 10 November 2019 were analysed retrospectively. The highest quartile (P75) of cholecystectomy operation time was used as a cutting point of DC (≥ P75) and NLC (< P75). Logistic regression was used to analyse the influencing factors of DC, and its risk model was constructed for prediction. Results Multivariate logistic regression analysis showed that body mass index (BMI) > 25 kg/m2, white blood cell (WBC) > 10 × 109/l, calculus incarcerated in neck of gallbladder, frequency of acute cholecystitis in the last 2 months > 4 times, thickness of gallbladder wall > 0.5 cm, and maximum diameter of gallstone > 2 cm were independent risk factors for DC. The prediction efficiency of the logistic regression equation was 0.879 (χ2 = 1.457, p > 0.05). Conclusions Based on analysis of risk factors, a logistic risk prediction model for difficult cholecystectomy was established. This model can be used to predict the difficulty of cholecystectomy.