Abstract

Indocyanine green (ICG) is an injectable fluorochrome that has recently gained popularity as a means of assisting intraoperative visualization during laparoscopic and robotic surgery. Many systematic reviews and meta-analyses have been published. We conducted a meta-review to synthesize the findings of these studies. PubMed and Embase were searched to identify systematic reviews and meta-analyses coping with the uses of ICG in abdominal operations, including Metabolic Bariatric Surgery, Cholecystectomy, Colorectal, Esophageal, Gastric, Hepato-Pancreato-Biliary, Obstetrics and Gynecology (OG), Pediatric Surgery, Surgical Oncology, Urology, (abdominal) Vascular Surgery, Adrenal and Splenic Surgery, and Interdisciplinary tasks, until September 2023. We submitted the retrieved meta-analyses to qualitative analysis based on the AMSTAR 2 instrument. We identified 116 studies, 41 systematic reviews (SRs) and 75 meta-analyses (MAs), spanning 2013-2023. The most thoroughly investigated (sub)specialties were Colorectal (6 SRs, 25 MAs), OG (9 SRs, 15 MAs), and HPB (4 SRs, 12 MAs). Interestingly, there was high heterogeneity regarding the administered ICG doses, routes, and timing. The use of ICG offered a clear benefit regarding anastomotic leak prevention, particularly after colorectal and esophageal surgery. There was no clear benefit regarding sentinel node detection after OG. According to the AMSTAR 2 tool, most meta-analyses ranked as "critically low" (34.7%) or "low" (58.7%) quality. There were only five meta-analyses (6.7%) that qualified as "moderate" quality, whereas there were no "high" quality reviews. Regardless of the abundance of pertinent literature and reviews, surgeons should be cautious when interpreting their results on ICG use in abdominal surgery. Future reviews should focus on ensuring methodological vigor; establishing clear protocols of ICG dose, route of administration, and timing; and improving reporting quality. Other sources of data (e.g., registries) and novel methods of data analysis (e.g., machine learning) might also contribute to an enhanced role of ICG as a decision-making tool in surgery.

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