Redefining hemodynamic instability in pheochromocytoma surgery through latent class analysis

Area of Science:

• Anesthesiology and Critical Care Medicine
• Surgical Oncology
• Cardiovascular Physiology

Background:

• Hemodynamic instability (HDI) during pheochromocytoma resection presents a significant anesthesiologic challenge.
• Current definitions of HDI are often arbitrary, hindering effective risk stratification and comparability.
• An objective, data-driven classification is needed to standardize assessment and management.

Purpose of the Study:

• To develop and validate an objective, data-driven classification system for intraoperative hemodynamic instability (HDI).
• To identify distinct patient risk groups undergoing pheochromocytoma surgical resection.
• To improve anesthesiologic management and risk stratification for this complex surgery.

Main Methods:

• Collected hemodynamic variables (SBP, DBP, HR, MAP) at five intraoperative time points from 92 patients.
• Employed Latent Class Analysis (LCA) to classify patients into low-risk (l-HDI) and high-risk (h-HDI) groups.
• Evaluated four LCA models using different hemodynamic variable combinations, selecting the optimal model via AIC and BIC.

Main Results:

• The LCA model using only intraoperative mean arterial pressure (MAP) provided the best classification (AIC: 3783; BIC: 3824).
• Identified two distinct classes: high-risk HDI (34.8%) and low-risk HDI (65.2%).
• Significant MAP differences observed between groups during key surgical phases; patient age and symptomatic presentation were strong predictors of HDI.

Conclusions:

• Proposes a reproducible and objective classification of intraoperative HDI in pheochromocytoma surgery.
• The classification is based on mean arterial pressure (MAP) derived from Latent Class Analysis (LCA).
• This objective classification facilitates better risk stratification and management of hemodynamic instability.