Zhou Zhaopeng, Liu Zhuanghua, Yang Hongqiao, Zhang Chunlei, Zhang Chenxu, Chen Junhui, Wang Yuhai
Department of Neurosurgery, The 904th Hospital of Joint Logistic Support Force of PLA, Wuxi Clinical College of Anhui Medical University, Wuxi, Jiangsu, China.
Front Neurol. 2023 Mar 22;14:1146106. doi: 10.3389/fneur.2023.1146106. eCollection 2023.
Aneurysmal subarachnoid hemorrhage (aSAH) is a common and potentially fatal cerebrovascular disease. Poor-grade aSAH (Hunt-Hess grades IV and V) accounts for 20-30% of patients with aSAH, with most patients having a poor prognosis. This study aimed to develop a stable nomogram model for predicting adverse outcomes at 6 months in patients with aSAH, and thus, aid in improving the prognosis.
The clinical data and imaging findings of 150 patients with poor-grade aSAH treated with microsurgical clipping of intracranial aneurysms on admission from December 2015 to October 2021 were retrospectively analyzed. Least absolute shrinkage and selection operator (LASSO), logistic regression analyses, and a nomogram were used to develop the prognostic models. Receiver operating characteristic (ROC) curves and Hosmer-Lemeshow tests were used to assess discrimination and calibration. The bootstrap method (1,000 repetitions) was used for internal validation. Decision curve analysis (DCA) was performed to evaluate the clinical validity of the nomogram model.
LASSO regression analysis showed that age, Hunt-Hess grade, Glasgow Coma Scale (GCS), aneurysm size, and refractory hyperpyrexia were potential predictors for poor-grade aSAH. Logistic regression analyses revealed that age (: 1.107, 95% : 1.056-1.116, < 0.001), Hunt-Hess grade (: 8.832, 95% : 2.312-33.736, = 0.001), aneurysm size (: 6.871, 95% : 1.907-24.754, = 0.003) and refractory fever (: 3.610, 95% : 1.301-10.018, < 0.001) were independent predictors of poor outcome. The area under the ROC curve (AUC) was 0.909. The calibration curve and Hosmer-Lemeshow tests showed that the nomogram had good calibration ability. Furthermore, the DCA curve showed better clinical utilization of the nomogram.
This study provides a reliable and valuable nomogram that can accurately predict the risk of poor prognosis in patients with poor-grade aSAH after microsurgical clipping. This tool is easy to use and can help physicians make appropriate clinical decisions to significantly improve patient prognosis.
动脉瘤性蛛网膜下腔出血（aSAH）是一种常见且可能致命的脑血管疾病。低级别aSAH（Hunt-Hess分级IV级和V级）占aSAH患者的20%-30%，大多数患者预后较差。本研究旨在建立一个稳定的列线图模型，用于预测aSAH患者6个月时的不良结局，从而有助于改善预后。
回顾性分析2015年12月至2021年10月收治的150例接受颅内动脉瘤显微夹闭术治疗的低级别aSAH患者的临床资料和影像学表现。采用最小绝对收缩和选择算子（LASSO）、逻辑回归分析和列线图构建预后模型。采用受试者操作特征（ROC）曲线和Hosmer-Lemeshow检验评估模型的区分度和校准度。采用自助法（1000次重复）进行内部验证。进行决策曲线分析（DCA）以评估列线图模型的临床有效性。
LASSO回归分析显示，年龄、Hunt-Hess分级、格拉斯哥昏迷量表（GCS）、动脉瘤大小和难治性高热是低级别aSAH的潜在预测因素。逻辑回归分析显示，年龄（β：1.107，95%CI：1.056-1.116，P<0.001）、Hunt-Hess分级（β：8.832，95%CI：2.312-33.736，P=0.001）、动脉瘤大小（β：6.871，95%CI：1.907-24.754，P=0.003）和难治性发热（β：3.610，95%CI：1.301-10.018，P<0.001）是不良结局的独立预测因素。ROC曲线下面积（AUC）为0.909。校准曲线和Hosmer-Lemeshow检验显示列线图具有良好的校准能力。此外，DCA曲线显示列线图具有更好的临床实用性。
本研究提供了一个可靠且有价值的列线图，可准确预测低级别aSAH患者显微夹闭术后预后不良的风险。该工具易于使用，可帮助医生做出适当的临床决策，显著改善患者预后。
