Recent advances in algorithms predicting hemodynamic instability undergoing surgery for phaeochromocytoma and paraganglioma.

Abstract

Abdominal pheochromocytomas and paragangliomas (PPGLs) are characterized by the overproduction of catecholamines, which are associated with hemodynamic instability (HDI) during surgery. Therefore, perioperative management to prevent intraoperative HDI is imperative for the surgical treatment of PPGLs. Owing to the rarity and heterogeneous nature of these tumors, pre-surgical prediction of HDI is a clinical dilemma. The reported risk factors for HDI include perioperative preparation, genetic background, tumor conditions, body composition, catecholamine levels, and surgical approach. Additionally, several personalized algorithms or models including these factors have been developed. The first part of this review outlines the prediction models that include clinical features such as tumor size and location, body mass index (BMI), blood glucose level, catecholamine levels, and preoperative management with α-adrenoceptor blockade and crystal/colloid fluid. We then summarize recently reported models that consider additional factors such as genetic background, radiomics, robotic-assisted surgical approach, three-dimensional visualization, and machine-learning models. These findings suggest that a comprehensive model including risk factors is the most likely approach for achieving effective perioperative management.