JoVE - Journal of Visualized Experiments
JoVE Visualize
Contact Us

Machine learning algorithms as early diagnostic tools for prolonged operative time in patients with fluorescent laparoscopic cholecystectomy: a retrospective cohort study

  • 0Graduate School, Hebei North University, Zhangjiakou, Hebei, China.
Frontiers in Surgery +

|

July 8, 2025

|

July 8, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

This study identified key risk factors for prolonged operative time in fluorescence laparoscopic cholecystectomy. A machine learning model accurately predicts prolonged operative times, aiding surgeons in patient management.

Area Of Science

  • Surgical Innovation
  • Medical Informatics
  • Hepatobiliary Surgery

Background

  • Fluorescence laparoscopic cholecystectomy (LC) is a common procedure for gallbladder stones.
  • Identifying factors that prolong operative time (OT) is crucial for optimizing surgical efficiency.
  • Predictive modeling can enhance patient care by anticipating potential delays.

Purpose Of The Study

  • To explore risk factors associated with prolonged operative time in fluorescence LC.
  • To develop and validate machine learning (ML) models for predicting prolonged OT.
  • To aid surgeons in identifying patients at higher risk for extended surgical duration.

Main Methods

  • Retrospective analysis of clinical data from patients undergoing fluorescence LC.
  • Utilized univariate, multifactor, and LASSO regression for parameter screening.
  • Integrated 11 ML classification models, with Light Gradient Boosting Machine (LightGBM) selected as optimal.

Main Results

  • Prolonged OT (≥85 min) occurred in 29% of 726 patients.
  • Key predictors identified: cholecystitis type, number of ports, gallbladder adhesion, prior antibiotic use, and gallbladder thickness.
  • The LightGBM model demonstrated strong predictive performance (AUC 0.876, accuracy 0.843).

Conclusions

  • A nomogram based on the LightGBM model can assess the risk of prolonged fluorescence LC time.
  • This tool assists surgeons in identifying patients likely to experience extended operative times.
  • Improved risk stratification can lead to better surgical planning and patient outcomes.

Keywords: