METHODS: 590 AIS patients with LVO assessed for regional leptomeningeal collateral (rLMC) were retrospectively enrolled, and randomly divided into a training set (n = 414) and a testing set (n = 176). Unfavorable functional outcome was defined as a modified Rankin scale (mRS) score of 3 to 6 at 3 months. We assessed the accuracy and clinical utility of the nomogram using calibration plots, area under the curve (AUC), decision curve analysis (DCA), net reclassification index (NRI), and integrated discrimination improvement (IDI).
RESULTS: Both NAR and rLMC were independently associated with unfavorable outcome at 3 months (OR=8.96, p=0.0341; OR=0.89, p=0.0002, respectively). The developed nomogram (akaike information criterion (AIC)=398.77), which included NAR, rLMC and other factors, showed good performance (the AUC for the development and validation cohorts was 0.848 and 0.840 respectively) and improved the predictive value compared to a model without NAR and rLMC, according to an overall NRI of 3.27% (p=0.2401), overall IDI of 3.27% (p=0.2414), and a higher AUC (0.848 vs 0.831).
CONCLUSIONS: NAR can serve as an independent predictor in AIS patients with anterior LVO, and the nomogram incorporating NAR and rLMC is reliable in predicting unfavorable outcome. Further studies with larger sample sizes are needed to validate and extend these findings.
方法:对590例AIS患者进行局部软脑膜侧支(rLMC)评估,并随机分为训练集(n=414)和测试集(n=176)。不良功能结局定义为3个月时3至6分的改良Rankin量表(mRS)评分。我们使用校准图评估了列线图的准确性和临床实用性,曲线下面积(AUC),决策曲线分析(DCA),净重新分类指数(NRI),和综合歧视改进(IDI)。
结果:NAR和rLMC均与3个月时的不良结局独立相关(OR=8.96,p=0.0341;OR=0.89,p=0.0002)。开发的列线图(阿凯信息准则(AIC)=398.77),其中包括NAR,rLMC和其他因素,与没有NAR和rLMC的模型相比,显示出良好的性能(开发和验证队列的AUC分别为0.848和0.840)并提高了预测值,根据总NRI为3.27%(p=0.2401),总IDI为3.27%(p=0.2414),和更高的AUC(0.848vs0.831)。
结论:NAR可以作为AIS患者前LVO的独立预测因子,包含NAR和rLMC的列线图在预测不利结果方面是可靠的。需要更大样本量的进一步研究来验证和扩展这些发现。