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DOI 10.1016/j.asjsur.2020.11.018

Медицинская библиотека · Asian journal of surgery · 2021

The pre-operative predictive model for difficult elective laparoscopic cholecystectomy: A modification.

Tongyoo Assanee, Chotiyasilp Parm, Sriussadaporn Ekkapak, Limpavitayaporn Palin, Mingmalairak Chatchai

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Аннотация

BACKGROUND

Although LC is a common operation, difficult cases are still challenging. Several studies have identified factors for the difficulty and conversion. Many scoring systems have been established for pre-operative prediction. This study aimed to investigate significant factors and validity of Randhawa's model in our setting.

METHODS

This prospective study enrolled LC patients in Hepato-Pancreato-Biliary Surgery unit between March 2018 and October 2019. The difficulty of operation was categorized into 3 groups by intra-operative grading scale. Multivariate analysis was performed to define significant factors of very-difficult and converted cases. The difficulty predicted by Randhawa's model were compared with actual outcome. Area under ROC curve was calculated.

RESULTS

Among 152 patients, difficult and very-difficult groups were 59.2% and 15.1%, respectively. Sixteen cases needed conversion. Four factors (cholecystitis, ERCP, thickened wall, contracted gallbladder) for very-difficult group and 3 factors (obesity, biliary inflammation or procedure, contracted gallbladder) for conversion were significant. After some modification of Randhawa's model, the modified scoring system provided better prediction in terms of higher correlation coefficient (0.41 vs 0.35) and higher AUROC curve (0.82 vs 0.75) than original model.

DISCUSSION: Randhawa's model was feasible for pre-operative preparation. The modification of this model provided better prediction on difficult cases.

Для цитирования: Tongyoo Assanee, Chotiyasilp Parm, Sriussadaporn Ekkapak, Limpavitayaporn Palin, Mingmalairak Chatchai. The pre-operative predictive model for difficult elective laparoscopic cholecystectomy: A modification.. Asian journal of surgery. 2021. DOI: 10.1016/j.asjsur.2020.11.018.

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