Risk prediction models for difficult cholecystectomy
Gan Chen1, Min Li2, Baoqiang Cao2
1Department of Vascular Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
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 (χ 2 = 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.
More Related Videos
03:05Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
Published on: February 16, 2024
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
