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Early detection of vasovagal syncope in tilt-up test with hemodynamic and autonomic study

机译:通过血液动力学和自主性研究在倾斜试验中早期发现血管迷走性晕厥

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摘要

The diagnosis of vasovagal syncope (VVS) is according to history, tilt table test and blood pressure change with postural stress. We collected 30 patients below 55 years-old, received tilt table test without pharmacological challenge from 2005 to 2010. Due to this disorder is the heterogeneity, multiple factor. The pathophysological pathway was not fully understood. We used logistic regression and neural network to evaluate variables during baseline and first 3 minutes tilt table test to early detect vasovagal syncope with tilt table test. We found using parameters of baseline heart rate, body mass index and mean blood pressure, cardiac index, left ventricular work index during 3 minutes of tilt up test for neural network model, the model revealed good train and test performance (accuracy:95.5%) with good sensitivity and specificity.
机译:血管迷走性晕厥(VVS)的诊断根据病史,倾斜试验和血压随体位压力的变化而变化。我们从2005年至2010年收集了30名55岁以下的患者,接受了倾斜台试验,没有受到药理学挑战。由于这种疾病是异质性,多因素的。病理途径尚未完全了解。我们使用逻辑回归和神经网络在基线和前3分钟倾斜台测试期间评估变量,以通过倾斜台测试及早发现血管迷走性晕厥。对于神经网络模型,使用基线心率,体重指数和平均血压,心脏指数,左心室工作指数在3分钟向上倾斜测试期间的参数,该模型显示出良好的训练和测试性能(准确性:95.5%)具有良好的敏感性和特异性。

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