Selective Cholecystectomy: using an evidence-based prediction model to plan for cholecystectomy

Gunnarsson, Ronny, and de Costa, Alan (2019) Selective Cholecystectomy: using an evidence-based prediction model to plan for cholecystectomy. ANZ Journal of Surgery, 89 (5). pp. 488-491.

[img] PDF (Published Version) - Published Version
Restricted to Repository staff only

View at Publisher Website:


Background: Symptomatic gall stones are treated safely and efficiently with laparoscopic cholecystectomy. Conversion to open cholecystectomy may be associated with adverse outcomes. Accurate prediction of conversion should decrease the incidence of conversion and improve patient care.

Methods: The recent literature on conversion at laparoscopic cholecystectomy is reviewed to identify robust prediction models that are both internally and externally validated. Results: Two prediction models are identified which meet these criteria.

Conclusions: The Cairns Prediction Model using nomograms, is an easily applied tool predicting conversion, which is presently in use. Routine use of this tool should decrease conversion, and improve the process of patient consent.

Item ID: 55836
Item Type: Article (Research - C1)
ISSN: 1445-2197
Keywords: conversion, laparoscopic cholecystectomy, nomogram, prediction, risk factor
Copyright Information: © 2018 Royal Australasian College of Surgeons
Date Deposited: 12 Oct 2018 02:59
FoR Codes: 32 BIOMEDICAL AND CLINICAL SCIENCES > 3202 Clinical sciences > 320226 Surgery @ 100%
SEO Codes: 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920105 Digestive System Disorders @ 50%
92 HEALTH > 9202 Health and Support Services > 920204 Evaluation of Health Outcomes @ 50%
Downloads: Total: 5
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page