目的 开发并验证一种线性模型，用于预测影响嗜铬细胞瘤和副神经节瘤（pheochromocytomas and paragangliomas，PPGLs）术后出现低血压的因素及概率。 方法 本研究收集了2011年1月1日至2023年12月31日在重庆医科大学附属第一医院泌尿外科接受腹膜后肿瘤切除并经过病理学诊断为PPGLs的315例患者，记录每位患者的人口学特征，基础疾病、疾病特征、α肾上腺受体拮抗剂使用情况、24 h尿香草扁杏仁酸（vanillylmandelic acid，VMA）、术中资料及术后资料，将血压低于术前30％或者术后需要升压药维持的患者纳入低血压组。而后采用LASSO回归对数据进行特征缩减和筛选，然后利用多元逻辑回归分析建立预测模型。通过ROC曲线、校准曲线和临床有用性来评估该预测模型的表现。 结果 预测模型中包含的预测因子包括24 h尿香草扁杏仁酸、α肾上腺受体拮抗剂使用情况、肿瘤大小以及手术失血量。该模型显示出良好的区分能力，C指数为0.882（95%CI=0.872~0.886），并且具有良好的校准性，ROC值为0.88。决策曲线分析显示具有临床价值。 结论 本研究提供了一个可靠的预测模型，该预测模型对PPGLs患者术后出现低血压的情况进行术前个体化预测，为患者围手术期治疗和术后恢复方案提供依据。

Objective To develop and validate a linear model to predict the factors and likelihood of postoperative hypotension in pheochromocytomas and paragangliomas（PPGLs）. Methods This study included 315 patients who underwent retroperitoneal tumor resection and were pathologically diagnosed with PPGLs from January 1，2011 to December 31，2023 at The First Affiliated Hospital of Chongqing Medical University. Demographic characteristics，comorbidities，disease features，use of α-adrenergic receptor antagonists，24-hour urinary vanillylmandelic acid levels，intraoperative data，and postoperative data were recorded for each patient. Patients with blood pressure lower than 30% preoperatively or requiring vasopressors postoperatively were assigned to the hypotension group. LASSO regression was utilized for feature reduction and selection，followed by multinomial logistic regression analysis to establish a predictive model. The performance of the predictive model was evaluated using receiver operating characteristic curves，calibration curves，and clinical utility assessments. Results Predictive factors included in the model were 24-hour urinary vanillylmandelic acid levels，use of α-adrenergic receptor antagonists，tumor size，and intraoperative blood loss. The model demonstrated good discriminative ability with a C-index of 0.882（95% confidence interval： 0.872-0.886） and excellent calibration performance with a receiver operating characteristic value of 0.88. Decision curve analysis indicated clinical utility. Conclusion This study presents a reliable predictive model for individualized preoperative prediction of postoperative hypotension in PPGLs patients，offering a basis for perioperative management and postoperative recovery strategies.