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Predictive Factors for Difficult Laparoscopic Cholecystectomies in Acute Cholecystitis

Authors :
Paul Lorin Stoica
Dragos Serban
Dan Georgian Bratu
Crenguta Sorina Serboiu
Daniel Ovidiu Costea
Laura Carina Tribus
Catalin Alius
Dan Dumitrescu
Ana Maria Dascalu
Corneliu Tudor
Laurentiu Simion
Mihail Silviu Tudosie
Meda Comandasu
Alexandru Cosmin Popa
Bogdan Mihai Cristea
Source :
Diagnostics, Vol 14, Iss 3, p 346 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Laparoscopic cholecystectomy (LC) is the gold standard treatment in acute cholecystitis. However, one in six cases is expected to be difficult due to intense inflammation and suspected adherence to and involvement of adjacent important structures, which may predispose patients to higher risk of vascular and biliary injuries. In this study, we aimed to identify the preoperative parameters with predictive value for surgical difficulties. A retrospective study of 255 patients with acute cholecystitis admitted in emergency was performed between 2019 and 2023. Patients in the difficult laparoscopic cholecystectomy (DLC) group experienced more complications compared to the normal LC group (33.3% vs. 15.3%, p < 0.001). Age (p = 0.009), male sex (p = 0.03), diabetes (p = 0.02), delayed presentation (p = 0.03), fever (p = 0.004), and a positive Murphy sign (p = 0.007) were more frequently encountered in the DLC group. Total leukocytes, neutrophils, and the neutrophil-to-lymphocyte ratio (NLR) were significantly higher in the DLC group (p < 0.001, p = 0.001, p = 0.001 respectively). The Tongyoo score (AUC ROC of 0.856) and a multivariate model based on serum fibrinogen, thickness of the gallbladder wall, and transverse diameter of the gallbladder (AUC ROC of 0.802) showed a superior predictive power when compared to independent parameters. The predictive factors for DLC should be assessed preoperatively to optimize the therapeutic decision.

Details

Language :
English
ISSN :
20754418
Volume :
14
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Diagnostics
Publication Type :
Academic Journal
Accession number :
edsdoj.01af39b01393458f99c1eaabd8fb9564
Document Type :
article
Full Text :
https://doi.org/10.3390/diagnostics14030346