腹腔镜胆囊切除术困难的超声预测指标。

IF 1.3 Q3 MEDICINE, GENERAL & INTERNAL
Cureus Pub Date : 2025-10-05 eCollection Date: 2025-10-01 DOI:10.7759/cureus.93870
Ibrahim Asim, Ahmed Taymour Algahiny, Omar HeshamEldin Abouelella, Malak Mohamed Refaat Shehab El Din, Omar Samir Mohamed Megahed Saleh Elmitwalli, Mohamed Bakr Elnagar, Haya Khaled Ali Abdulla AlKhalifa, Ahmed Mostafa Abdalla Mohamed, Hosam Alazazzi
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引用次数: 0

摘要

腹腔镜胆囊切除术(LC)是胆结石疾病的金标准治疗方法,但一些手术在技术上具有挑战性,导致手术时间更长,转换率更高,并发症增加。准确的术前预测对于安全的手术计划至关重要。本文综述了目前超声预测困难LC (DLC)的证据,并评估了经验证的基于超声的术前风险分层评分系统。超声仍然是胆囊评估的一线方式,并提供了手术难度的几个关键预测因素:胆囊壁厚度(GBWT)始终显示与DLC最强的独立关联,与转换和术后并发症相关。胆囊周围积液,虽然不常见,但对严重炎症和复杂病例具有高度特异性。颈部或哈特曼囊胆结石嵌塞是比结石多样性更强的预测因素。异常的胆囊大小,无论是收缩还是膨胀,都会使夹层复杂化,而胆总管扩张是第二个预测因素。一些评分系统将这些超声特征与临床变量(如年龄、性别、肥胖和既往炎症)结合起来,帮助实现更强的预测准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ultrasonographic Predictors of Difficult Laparoscopic Cholecystectomy.

Laparoscopic cholecystectomy (LC) is the gold-standard treatment for gallstone disease, but some procedures become technically challenging, resulting in longer operative times, higher conversion rates, and increased complications. Accurate preoperative prediction is essential for safe surgical planning. This review summarizes current evidence on ultrasonographic predictors of difficult LC (DLC) and evaluates validated ultrasound-based scoring systems for preoperative risk stratification. Ultrasound remains the first-line modality for gallbladder assessment and provides several key predictors of surgical difficulty: gallbladder wall thickness (GBWT) consistently demonstrates the strongest independent association with DLC, correlating with conversion and postoperative complications. Pericholecystic fluid, though less frequent, is highly specific for severe inflammation and complex cases. Gallstone impaction at the neck or Hartmann's pouch is a stronger predictor than stone multiplicity. Abnormal gallbladder size, whether contracted or distended, complicates dissection, while common bile duct dilatation serves as a secondary predictor. Several scoring systems combine these sonographic features with clinical variables such as age, sex, obesity, and prior inflammation, helping achieve stronger predictive accuracy.

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