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Carotid intima media thickness measurements coupled with stroke severity strongly predict short-term outcome in patients with acute ischemic stroke: a machine learning study
Metabolic Brain Disease ( IF 3.2 ) Pub Date : 2021-08-04 , DOI: 10.1007/s11011-021-00784-7
Ana Lucia Cruz Fürstenberger Lehmann 1 , Daniela Frizon Alfieri 2 , Maria Caroline Martins de Araújo 3 , Emanuelle Roberto Trevisani 2 , Maisa Rocha Nagao 2 , Francisco Spessatto Pesente 4 , Jair Roberto Gelinski 2 , Leonardo Bodner de Freitas 2 , Tamires Flauzino 2 , Márcio Francisco Lehmann 5 , Marcell Alysson Batisti Lozovoy 2, 6 , José Wander Breganó 2, 6 , Andréa Name Colado Simão 2, 6 , Michael Maes 7, 8 , Edna Maria Vissoci Reiche 2, 6
Affiliation  

Acute ischemic stroke (IS) is one of the leading causes of morbidity, functional disability and mortality worldwide. The objective was to evaluate IS risk factors and imaging variables as predictors of short-term disability and mortality in IS. Consecutive 106 IS patients were enrolled. We examined the accuracy of IS severity using the National Institutes of Health Stroke Scale (NIHSS), carotid intima-media thickness (cIMT) and carotid stenosis (both assessed using ultrasonography with doppler) predicting IS outcome assessed with the modified Rankin scale (mRS) three months after hospital admission. Poor prognosis (mRS ≥ 3) at three months was predicted by carotid stenosis (≥ 50%), type 2 diabetes mellitus and NIHSS with an accuracy of 85.2% (sensitivity: 90.2%; specificity: 81.8%). The mRS score at three months was strongly predicted by NIHSS (β = 0.709, p < 0.001). Short-term mortality was strongly predicted using a neural network model with cIMT (≥ 1.0 mm versus < 1.0 mm), NIHSS and age, yielding an area under the receiving operator characteristic curve of 0.977 and an accuracy of 94.7% (sensitivity: 100.0%; specificity: 90.9%). High NIHSS (≥ 15) and cIMT (≥ 1.0 mm) increased the probability of dying with hazard ratios of 7.62 and 3.23, respectively. Baseline NIHSS was significantly predicted by the combined effects of age, large artery atherosclerosis stroke, sex, cIMT, body mass index, and smoking. In conclusion, high values of cIMT and NIHSS at admission strongly predict short-term functional impairment as well as mortality three months after IS, underscoring the importance of those measurements to predict clinical IS outcome.



中文翻译:

颈动脉内膜中层厚度测量与卒中严重程度相结合,强烈预测急性缺血性卒中患者的短期预后:一项机器学习研究

急性缺血性中风 (IS) 是全球发病率、功能性残疾和死亡率的主要原因之一。目的是评估 IS 风险因素和影像学变量作为 IS 短期残疾和死亡率的预测因子。连续招募了 106 名 IS 患者。我们使用美国国立卫生研究院卒中量表 (NIHSS)、颈动脉内膜中层厚度 (cIMT) 和颈动脉狭窄(均使用超声多普勒评估)检查 IS 严重程度的准确性,以预测使用改良 Rankin 量表 (mRS) 评估的 IS 结果入院后三个月。颈动脉狭窄(≥ 50%)、2 型糖尿病和 NIHSS 预测三个月预后不良(mRS ≥ 3)的准确率为 85.2%(敏感性:90.2%;特异性:81.8%)。NIHSS 强烈预测三个月时的 mRS 评分(β = 0.709,p < 0.001)。使用具有 cIMT (≥ 1.0 mm) 的神经网络模型强烈预测短期死亡率 < 1.0 mm)、NIHSS 和年龄相比,接受操作者特征曲线下的面积为 0.977,准确度为 94.7%(敏感性:100.0%;特异性:90.9%)。高 NIHSS (≥ 15) 和 cIMT (≥ 1.0 mm) 增加了死亡概率,风险比分别为 7.62 和 3.23。年龄、大动脉粥样硬化中风、性别、cIMT、体重指数和吸烟的综合影响可显着预测基线 NIHSS。总之,入院时 cIMT 和 NIHSS 的高值强烈预测 IS 后三个月的短期功能障碍和死亡率,强调了这些测量对预测临床 IS 结果的重要性。

更新日期:2021-08-10
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