The pre-operative predictive model for difficult elective laparoscopic cholecystectomy: A modification
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Le résumé fourni par la source
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.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- The pre-operative predictive model for difficult elective laparoscopic cholecystectomy: A modification
- Date Crossref
- 01/04/2021
- Éditeur
- Elsevier BV
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Thammasat University pays non établi dans la noticeUniversité ou école supérieure
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Faculty of Medicine Department of Surgery pays non établi dans la noticeUniversité ou école supérieure
Thammasat University et Department of Surgery — Faculty of Medicine.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.