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Preoperative prediction model for conversion of laparoscopic to open cholecystectomy in patient with acute cholecystitis: based on clinical, laboratory, and CT parameters.

Authors :
Kim MS
Kwon HJ
Park HW
Park JY
Chung EC
Park HJ
Kwag HJ
Hong HP
Source :
Journal of computer assisted tomography [J Comput Assist Tomogr] 2014 Sep-Oct; Vol. 38 (5), pp. 727-32.
Publication Year :
2014

Abstract

Objective: To identify preoperative computed tomography (CT) predictors associated with conversion from laparoscopic to open cholecystectomy and to propose the risk scoring model for prediction of conversion by integrating clinical, laboratory, and CT parameters.<br />Methods: The institutional review board approved this retrospective study, and informed consent was waived. One hundred eighty-three patients who underwent a laparoscopic cholecystectomy for acute cholecystitis were evaluated for clinical, laboratory, and CT parameters. Associations between conversion and these parameters were assessed by using univariate and multivariate logistic regression analysis. The risk scoring model was devised using a regression coefficient-based scoring method.<br />Results: Conversion to open cholecystectomy was performed in 30 patients (17%). Multivariate analysis identified age older than 60 years, male, and pericholecystic fluid as independent predictors of conversion. The preoperative prediction model to calculate the risk score for conversion showed sensitivity of 83% and specificity of 72%, with an area under the receiver operator curve of 0.83.<br />Conclusions: Pericholecystic fluid collection was the only CT parameter with clinical parameters of age older than 60 years and male in prediction for conversion in acute cholecystitis. The preoperative prediction model using these 3 parameters can be adapted easily in clinical practice with a good discrimination.

Details

Language :
English
ISSN :
1532-3145
Volume :
38
Issue :
5
Database :
MEDLINE
Journal :
Journal of computer assisted tomography
Publication Type :
Academic Journal
Accession number :
24887577
Full Text :
https://doi.org/10.1097/RCT.0000000000000116