Comparison of Three Methods of Gallbladder Drainage for Patients with Acute Cholecystitis Who Are at High Surgical Risk: A Network Meta-Analysis and Systematic Review

J Laparoendosc Adv Surg Tech A. 2021 Nov;31(11):1295-1302. doi: 10.1089/lap.2020.0897. Epub 2021 Jan 8.

Abstract

Background: Percutaneous gallbladder drainage (PTGBD), endoscopic ultrasound-guided gallbladder drainage (EUSGBD), and endoscopic transpapillary gallbladder drainage (ETGBD) are used for the treatment of patients with acute cholecystitis who are at high surgical risk. However, it is unclear which procedure is associated with the best outcomes. Methods: We systematically searched records in PubMed, Embase, Web of Science, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov up to March 1, 2020. Studies that compared at least two of PTGBD, ETGBD, and EUSGBD were included. Results: A total of 13 studies were included in the present analyses. PTGBD, EUSGBD, and ETGBD were associated with similar clinical success, adverse event, recurrent cholecystitis, reintervention, and mortality rates. PTGBD was associated with a higher technical success rate than EUSGBD (odds ratio [OR] = 0.75, 95% confidence interval [CI] = 0.40-1.41) or ETGBD (OR = 0.73, 95% CI = 0.35-1.53). EUSGBD was associated with the highest probability of clinical success (67.5%), and the lowest prevalences of adverse events (57.0%) and recurrent cholecystitis (60.9%). ETGBD was associated with the best reintervention outcomes (81.8%). Conclusions: Compared with PTGBD and ETGBD, EUSGBD appears to be preferable with respect to both safety and efficacy for the treatment of patients with acute cholecystitis who are at high surgical risk.

Keywords: endoscopic ultrasonography; gallbladder drainage; meta-analysis; percutaneous; transpapillary endoscopy.

Publication types

  • Meta-Analysis
  • Systematic Review

MeSH terms

  • Cholecystitis, Acute* / surgery
  • Drainage
  • Endosonography
  • Gallbladder* / diagnostic imaging
  • Gallbladder* / surgery
  • Humans
  • Network Meta-Analysis