Redefining Hemodynamic Instability in Pheochromocytoma Surgery through Latent Class Analysis

Objective Hemodynamic instability (HDI) during pheochromocytoma surgical resection remains a major anesthesiologic challenge. The definition of HDI is often arbitrary, limiting comparability and risk stratification. We aimed to develop an objective, data-driven classification of intraoperative HDI. Methods Hemodynamic variables, including systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR), and mean arterial pressure (MAP), were collected at five intraoperative time points. Latent class analysis (LCA) was used to classify patients into two groups: low-risk (l-HDI) and high-risk (h-HDI) HDI classes. We compared four LCA models based on different combinations of variables (SBP+DBP, SBP+DBP+HR, MAP, MAP+HR) to identify the optimal classification of HDI, using AIC and BIC for model selection. Results Among 92 patients, the LCA model based solely on intraoperative MAP yielded the best classification of HDI (AIC: 3783; BIC: 3824). Two latent classes were identified: high-risk HDI (n = 32, 34.8%) and low-risk HDI (n = 60, 65.2%). MAP values were significantly different between the two groups during anesthesia induction (89 vs. 102 mmHg, p < 0.001), pneumoperitoneum induction (83 vs. 94 mmHg, p = 0.002), gland manipulation (95 vs. 131 mmHg, p < 0.001), and immediately post-adrenal vein ligation (79 vs. 83 mmHg, p = 0.039). Multivariable logistic regression showed that patients’ age (OR 1.04 per year; 95% CI 1.01–1.02; p=0.047) and symptomatic presentation (OR 15.35; 95% CI 4.19–56.2; p<0.001) were strongly associated with HDI. Conclusion This study proposes a reproducible and objective classification of intraoperative HDI in pheochromocytoma surgery based on MAP-derived latent class analysis.