Predicting the difficult laparoscopic cholecystectomy based on a preoperative scale

Camilo Ramírez-Giraldo, Kelly Alvarado-Valenzuela, Andrés Isaza-Restrepo, Jorge Navarro-Alean

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

It is important to establish the difficulty of a cholecystectomy preoperatively to improve the outcomes. There are multiple risk factors for a difficult cholecystectomy that may depend on the patient, the disease, or extrinsic factors. The aim of this study is to evaluate the predictive capacity of a difficult cholecystectomy with a preoperative scale. A diagnostic trial study was designed to evaluate the performance of a scale to predict the difficulty of laparoscopic cholecystectomy, considering as a reference standard the intraoperative findings evaluated according to an intraoperative difficulty scale. A ROC curve was performed and used to estimate predictive value of the preoperative score to predict the difficulty of a cholecystectomy preoperatively. The ROC curve shows an area of 0.88 under the curve. The calculated ideal cutoff was 8, with a sensitivity, specificity, positive predictive value and negative predictive value of 75.15%, 88.31%, 87.32 and 76.83%, respectively. It was demonstrated that, as the difficulty predicted by the preoperative scale increases, the rate of conversion to open procedure, the rate of subtotal cholecystectomies, the rate of complication and the rate of a critical view of safety failed increase. We suggest implementing the preoperative scale in all patients who are planning laparoscopic cholecystectomy, considering it a simple and easy tool to perform. This to inform the patient, organize the surgery schedule, select personnel, request support and have adequate pre-operative planning.

Translated title of the contributionPredicción de la colecistectomía laparoscópica difícil basada en una escala preoperatoria
Original languageEnglish (US)
Article number489
JournalUpdates in Surgery
Volume2022
Early online dateFeb 4 2022
DOIs
StatePublished - Feb 4 2022

All Science Journal Classification (ASJC) codes

  • General Medicine

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