Objective: To investigate clinical and imaging parameters to predict blood loss and cranial nerve injury (CNI) following carotid body paraganglioma (CBP) resection. Methods: A retrospective examination of clinical and imaging data was conducted on 63 patients who underwent CBP resection at Xiangya Hospital of Central South University from January 2016 to December 2022, including 23 males and 40 females, aged 26-87 years old. Three imaging parameters including tumor volume, the angle of contact with the internal carotid artery (ICA), and the distance to the base of skull (DTBOS) were gauged using the IMEDPACS software on CTA and MR imaging. The predictive efficacies of age, gender, Shamblin classification, and three imaging parameters for blood loss and CNI following surgery were analysed. Logistic composite parameter models were constructed and their predictive validity was assessed. Results: Multivariate logistic regression analysis underscored that only tumor volume (OR=1.381,95%CI:1.167-1.507,P=0.001) showed significant statistical correlations with blood loss following surgery. Area under curve (AUC) values of 0.910 for receiver operating characteristic (ROC) curves showed a sensitivity of 1.000 and a specificity of 0.694. Tumor volume (OR=1.126,95%CI:1.030-1.231, P=0.002) and DTBOS (OR=0.225,95%CI:0.081-0.630,P=0.005) were significantly associated with postoperative CNI. The analysis of logistic composite model showed AUC values for tumor volume, DTBOS and combination of the two parameters were 0.858, 0.788, and 0.872, respectively. The model for combination of tumor volume and DTBOS also proved superior in predicting postoperative CNI (Z=3.106, P<0.001), with a sensitivity of 0.833 and a specificity of 0.769. Conclusions: Tumor volume and DTBOS emerged as effective predictors for blood loss and/or CNI in patients with CBP resection. Moreover, the logistic composite parameter model outclassed single-parameter models in terms of their predictive clinical value.
目的： 探讨利用术前临床及影像参数预测颈动脉体副神经节瘤（carotid body paraganglioma，CBP）术中出血量及术后颅神经损伤的临床价值。 方法： 回顾性分析2016年1月至2022年12月中南大学湘雅医院进行手术治疗的63例CBP患者的临床资料，其中男23例，女40例，年龄26~87岁。利用IMEDPACS软件对CT血管成像（CTA）与MRI进行测量，包括肿瘤体积、包裹颈内动脉角度及肿瘤上缘到颅底距离（distance to the base of skull，DTBOS）3种影像参数。分析比较年龄、性别、Shamblin分型、影像参数与术中出血量和颅神经损伤并发症的相关性及预测效能，构建联合参数预测模型并评价其效价。 结果： 多因素Logistic回归分析显示，对于术中出血量，仅肿瘤体积（OR=1.381，95%CI：1.167~1.507，P=0.001）有显著影响，绘制肿瘤体积单一参数的受试者工作特征（ROC）曲线，曲线下面积（AUC）为0.910，敏感度和特异度分别为1.000和0.694。对于术后颅神经损伤，肿瘤体积（OR=1.126，95%CI：1.030~1.231，P=0.002）及DTBOS（OR=0.225，95%CI：0.081~0.630，P=0.005）对其有显著影响；分别绘制这2种参数及联合参数模型的ROC曲线，AUC值分别为0.858、0.788和0.872，联合参数模型AUC值最高，其敏感度与特异度分别为0.833和0.769，差异有统计学意义（Z=3.106，P<0.001）。 结论： 肿瘤体积和DTBOS这2种参数，可有效预测CBP患者术中出血量和/或颅神经损伤并发症，联合参数的Logistic回归模型较单一参数具有更好的临床预测价值。.