Cui Yuan-Yue, Wang Bin, Jiang Bo, Zhao Shi-Hong
Department of Ophthalmology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
Department of Neurosurgery, Peking University International Hospital, Beijing 102206, China.
Int J Ophthalmol. 2022 Aug 18;15(8):1316-1321. doi: 10.18240/ijo.2022.08.14. eCollection 2022.
To explore the risk factors of oculomotor nerve palsy (ONP) in patients with intracranial aneurysm (IA) and develop a nomogram model for predicting ONP of IA patients.
A total of 329 IA patients were included. Logistic regression analysis was applied to identify independent factors, which were then integrated into the nomogram model. The performance of the nomogram model was evaluated by calibration curve, receiver operating curve (ROC), and decision curve analysis.
Univariate and multivariate logistic regression analysis indicated posterior communicating artery (PCoA) aneurysm [hazard ratio (HR)=17.13, <0.001] and aneurysm diameter (HR=1.31, <0.001) were independent risk factors of ONP in IA patients. Based on the results of logistic regression analysis, a nomogram model for predicting the ONP in IA patients was constructed. The calibration curve indicated the nomogram had a good agreement between the predictions and observations. The nomogram showed a high predictive accuracy and discriminative ability with an area under the curve (AUC) of 0.863. The decision curve analysis showed that the nomogram was powerful in the clinical decision. PCoA aneurysm (HR=3.38, =0.015) was identified to be the only independent risk factor for ONP severity.
PCoA aneurysm and aneurysm diameter are independent risk factors of ONP in IA patients. The nomogram established is performed reliably and accurately for predicting ONP. PCoA aneurysm is the only independent risk factor for ONP severity.
探讨颅内动脉瘤（IA）患者动眼神经麻痹（ONP）的危险因素，并建立预测IA患者ONP的列线图模型。
共纳入329例IA患者。应用Logistic回归分析确定独立因素，然后将其纳入列线图模型。通过校准曲线、受试者工作特征曲线（ROC）和决策曲线分析评估列线图模型的性能。
单因素和多因素Logistic回归分析表明，后交通动脉（PCoA）动脉瘤[风险比（HR）=17.13，<0.001]和动脉瘤直径（HR=1.31，<0.001）是IA患者ONP的独立危险因素。基于Logistic回归分析结果，构建了预测IA患者ONP的列线图模型。校准曲线表明列线图预测值与观察值之间具有良好的一致性。列线图显示出较高的预测准确性和鉴别能力，曲线下面积（AUC）为0.863。决策曲线分析表明列线图在临床决策中具有强大作用。PCoA动脉瘤（HR=3.38，=0.015）被确定为ONP严重程度的唯一独立危险因素。
PCoA动脉瘤和动脉瘤直径是IA患者ONP的独立危险因素。所建立的列线图在预测ONP方面可靠且准确。PCoA动脉瘤是ONP严重程度的唯一独立危险因素。
