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基于心率和血压趋势及变异性预测血管迷走性晕厥:1155例患者的经验

Prediction of vasovagal syncope from heart rate and blood pressure trend and variability: experience in 1,155 patients.

作者信息

Virag Nathalie, Sutton Richard, Vetter Rolf, Markowitz Toby, Erickson Mark

机构信息

Medtronic Europe, Tolochenaz, Switzerland.

出版信息

Heart Rhythm. 2007 Nov;4(11):1375-82. doi: 10.1016/j.hrthm.2007.07.018. Epub 2007 Jul 18.

Abstract

BACKGROUND

Vasovagal syncope (VVS) is a complex fainting disorder commonly triggered by orthostatic stress.

OBJECTIVE

We developed an algorithm for VVS prediction based on the joint assessment of RR interval (RR) and systolic blood pressure (SBP).

METHODS

Simultaneous analysis of RR and SBP trends during head-up tilt as well as their variability represented by low-frequency power (LFRR and LFSBP) generated a cumulative risk that was compared with a predetermined VVS risk threshold. When cumulative risk exceeded the threshold, an alert was generated. Prediction time was the duration between the first alert and syncope. In the first 180 sec of head-up tilt, baseline values were established, following which VVS prediction was possible. An analysis was performed using 1,155 patients who had undergone head-up tilt for syncope: 759 tilt-positive and 396 tilt-negative patients. In the tilt-test protocol, at syncope or after 35 min, the patient was returned to supine.

RESULTS

In tilt-positive patients, VVS was predicted in 719 of 759 patients (sensitivity 95%), whereas 29 false alarms were generated in 396 tilt-negative patients (specificity 93%). Prediction times varied from 0 to 30 min but were longer than 1 min in 49% of patients.

CONCLUSION

Predicting impending syncope requires use of simultaneous blood pressure and heart rate, which may shorten diagnostic testing time, free patients from experiencing syncope during a diagnostic tilt-test, and have application in risk-guided tilt training and in an implanted device-to-trigger pacing intervention. The prospects for relieving patient discomfort are encouraging.

摘要

背景

血管迷走性晕厥(VVS)是一种常见的复杂晕厥障碍,通常由体位性应激引发。

目的

我们基于RR间期(RR)和收缩压(SBP)的联合评估开发了一种VVS预测算法。

方法

在头高位倾斜期间同时分析RR和SBP趋势以及由低频功率(LFRR和LFSBP)表示的它们的变异性,产生累积风险,并与预先确定的VVS风险阈值进行比较。当累积风险超过阈值时,发出警报。预测时间是首次警报与晕厥之间的持续时间。在头高位倾斜的前180秒内,建立基线值,此后即可进行VVS预测。对1155例因晕厥接受过头高位倾斜检查的患者进行了分析:759例倾斜试验阳性患者和396例倾斜试验阴性患者。在倾斜试验方案中,在晕厥时或35分钟后,患者恢复仰卧位。

结果

在倾斜试验阳性患者中,759例患者中有719例被预测为VVS(敏感性95%),而396例倾斜试验阴性患者中有29例假阳性(特异性93%)。预测时间从0到30分钟不等,但49%的患者超过1分钟。

结论

预测即将发生的晕厥需要同时使用血压和心率,这可能会缩短诊断测试时间,使患者在诊断性倾斜试验期间免于经历晕厥,并可应用于风险导向的倾斜训练以及植入式设备触发起搏干预。缓解患者不适的前景令人鼓舞。

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