Predictive factors and a nomogram for hemodynamic instability during operation in patients with pheochromocytomas and...

Intraoperative hemodynamic instability (HDI) remains a significant challenge during surgery for pheochromocytomas and paragangliomas (PPGLs), despite preoperative preparation. Identifying predictive factors is crucial for risk stratification and management optimization.

This retrospective study analyzed 203 PPGLs patients undergoing surgery at Qilu Hospital of Shandong University (July 2019-February 2025). HDI was defined as systolic blood pressure ≥ 160 mmHg or mean arterial pressure < 60 mmHg during surgery. Patient demographics, clinical characteristics, tumor features (including maximum diameter measured on CT), preoperative catecholamine/metabolite levels, and preoperative preparation adequacy (based on BP/HR records) were evaluated. Univariate and multivariate logistic regression identified independent predictors. A predictive nomogram was constructed using significant factors and validated internally.

Among 203 patients, 133 (65.5%) experienced intraoperative HDI. Multivariate analysis identified four independent preoperative predictors: maximum tumor diameter > 49.5 mm (odds ratio (OR) = 3.169, 95% confidence interval (CI): 1.531-6.562, P = 0.002), preoperative hypertension history (OR = 2.636, 95% CI: 1.293-5.375, P = 0.008), elevated plasma adrenaline level (OR = 4.803, 95% CI: 1.977-11.666, P = 0.001), and inadequate preoperative preparation (OR = 0.251 for adequacy, 95% CI: 0.107-0.590, P = 0.002). A nomogram incorporating these factors demonstrated good discrimination (AUC = 0.823, 95% CI: 0.761-0.886), significantly outperforming individual factors, and good calibration (Hosmer-Lemeshow p = 0.218). Decision curve analysis confirmed clinical utility.

Maximum tumor diameter > 49.5 mm, preoperative hypertension history, elevated plasma adrenaline, and inadequate preoperative preparation are key independent predictors of intraoperative HDI in PPGL surgery. The developed nomogram effectively integrates these factors to provide personalized preoperative risk assessment, aiding clinicians in identifying high-risk patients for intensified management strategies.