Measurement of Indocyanine Green as a Predictor of Liver Failure After Hepatic Resection, Contributing to Risk Stratification in Personalized Medicine
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Most of the advances in liver surgery have been achieved in the last few decades. The development of new diagnostic and therapeutic techniques has aided diagnosis and has facilitated more efficient and personalized resections for liver disorders. The estimation of the hepatic reserve has gained great importance because it marks the limit for more aggressive liver resections. It was hypothesized that determination of hepatic reserve by measuring plasma clearance of indocyanine green—following hepatic parenchymal liver resection—could provide earlier and more accurate knowledge of hepatic reserve and thus allow for more personalized therapy. Methods: A prospective observational post-authorization study was performed. Results: Applying ROC curves and the area under the curve (AUC) for the evaluation of the different tests as predictors of liver failure, favorable data were obtained in relation to bilirubin (AUC = 0.922) and prothrombin time (AUC = 1), and for postoperative PDR (AUC = 0.879) and GOT (AUC = 0.857), but not for preoperative PDR (AUC = 0.667) or GPT (AUC = 0.6). Conclusions: The gold standard for predicting early liver failure (the 50:50 criterion at on postoperative day 5) has a very good relationship with the plasma clearance rate of indocyanine green on postoperative day 1 and therefore has the potential to support earlier and more personalized therapeutic interventions, pending further validation.
Source: Journal of Personalized Medicine
DOI: 10.3390/jpm15100488
Authors: Víctor Baladrón González, David Padilla Valverde, María del Carmen Gasco García, Pedro Juan Villarejo Campos, María Jesús Pardo Mora, Natalia Bejarano Ramírez, Omar Montenegro Herrera, Patricia Faba Martín, Rubén Villazala González, Francisco Javier Redondo Calvo
Language: English
Subfield: Hepatology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W4415241107
