Guo Qinyu, Chen Hongyi, Lin Shirong, Gong Zheng, Song Zhiwei, Chen Feng
Department of Emergency, Fujian Provincial Hospital, Fujian, Fuzhou, China.
Shengli Clinical Medical College, Fujian Medical University, Fujian, Fuzhou, China.
Front Neurol. 2024 Aug 19;15:1410735. doi: 10.3389/fneur.2024.1410735. eCollection 2024.
Spontaneous aneurysmal subarachnoid hemorrhage (aSAH) is a common acute cerebrovascular disease characterized by severe illness, high mortality, and potential cognitive and motor impairments. We carried out a retrospective study at Fujian Provincial Hospital to establish and validate a model for forecasting functional outcomes at 6 months in aSAH patients who underwent interventional embolization.
386 aSAH patients who underwent interventional embolization between May 2012 and April 2022 were included in the study. We established a logistic regression model based on independent risk factors associated with 6-month adverse outcomes (modified Rankin Scale Score ≥ 3, mRS). We evaluated the model's performance based on its discrimination, calibration, clinical applicability, and generalization ability. Finally, the study-derived prediction model was also compared with other aSAH prognostic scales and the model's itself constituent variables to assess their respective predictive efficacy.
The predictors considered in our study were age, the World Federation of Neurosurgical Societies (WFNS) grade of IV-V, mFisher score of 3-4, secondary cerebral infarction, and first leukocyte counts on admission. Our model demonstrated excellent discrimination in both the modeling and validation cohorts, with an area under the curve of 0.914 ( < 0.001, 95%CI = 0.873-0.956) and 0.947 ( < 0.001, 95%CI = 0.907-0.987), respectively. Additionally, the model also exhibited good calibration (Hosmer-Lemeshow goodness-of-fit test: X = 9.176, = 0.328). The clinical decision curve analysis and clinical impact curve showed favorable clinical applicability. In comparison to other prediction models and variables, our model displayed superior predictive performance.
The new prediction nomogram has the capability to forecast the unfavorable outcomes at 6 months after intervention in patients with aSAH.
自发性动脉瘤性蛛网膜下腔出血（aSAH）是一种常见的急性脑血管疾病，其特点是病情严重、死亡率高，且存在潜在的认知和运动功能障碍。我们在福建省立医院开展了一项回顾性研究，以建立并验证一个预测接受介入栓塞治疗的aSAH患者6个月时功能结局的模型。
本研究纳入了2012年5月至2022年4月期间接受介入栓塞治疗的386例aSAH患者。我们基于与6个月不良结局（改良Rankin量表评分≥3，mRS）相关的独立危险因素建立了一个逻辑回归模型。我们根据模型的区分度、校准度、临床适用性和泛化能力评估了模型的性能。最后，还将本研究得出的预测模型与其他aSAH预后量表及其自身的构成变量进行比较，以评估它们各自的预测效能。
我们研究中考虑的预测因素包括年龄、世界神经外科联合会（WFNS）IV - V级、mFisher评分为3 - 4分、继发性脑梗死以及入院时的首次白细胞计数。我们的模型在建模队列和验证队列中均表现出出色的区分度，曲线下面积分别为0.914（P < 0.001，95%CI = 0.873 - 0.956）和0.947（P < 0.001，95%CI = 0.907 - 0.987）。此外，该模型还表现出良好的校准度（Hosmer - Lemeshow拟合优度检验：X = 9.176，P = 0.328）。临床决策曲线分析和临床影响曲线显示出良好的临床适用性。与其他预测模型和变量相比，我们的模型表现出卓越的预测性能。
新的预测列线图能够预测aSAH患者介入治疗后6个月时的不良结局。
