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利用心率变异性和压力反射敏感性参数预测血管迷走性晕厥患者直立倾斜试验的结果。

Predicting the outcome of head-up tilt test using heart rate variability and baroreflex sensitivity parameters in patients with vasovagal syncope.

作者信息

Klemenc Matjaž, Štrumbelj Erik

机构信息

Department of Cardiology, General Hospital of Nova Gorica, Padlih borcev 13a, 5290, Šempeter Pri Gorici, Slovenia.

Faculty of Computer Science, University of Ljubljana, Večna pot 113, 1000, Ljubljana, Slovenia.

出版信息

Clin Auton Res. 2015 Dec;25(6):391-8. doi: 10.1007/s10286-015-0318-6. Epub 2015 Nov 7.

DOI:10.1007/s10286-015-0318-6
PMID:26546357
Abstract

PURPOSE

The aim of the study was to investigate whether a statistical model could be used for an early prediction of the head-up tilt test (HUTT) outcome from heart rate variability (HRV) and baroreflex sensitivity (BRS) data obtained during early stages of the HUTT.

METHODS

A modified Italian protocol was used for HUTT in 105 patients with a previous history of vasovagal syncope. Beat-to-beat heart rate and blood pressure were continuously recorded. Fast Fourier transformation was used for spectral analysis of HRV and a sequence technique for measuring the BRS.

RESULTS

Linear statistical models based on HRV and BRS data from the first 15 min of HUTT were no more accurate than always naively predicted majority class that a syncope will occur (average model out-of-sample accuracy 56.2 ± 5.1 % vs. majority class relative frequency 54.2 %). Even when HRV and BRS data from the first 30 min were used in the model, we did not obtain any predictions of meaningful practical value (75.0 ± 5.1 % accuracy vs. 72.2 % majority class).

CONCLUSIONS

While there are discernible and meaningful differences between HUTT-P and HUTT-N subjects, they are not sufficient to discriminate between the two groups and predict a syncope early in the HUTT. The results might improve with a larger set of subjects; however, we can conclude that it is not likely that syncope predictions of practical value can be obtained from aggregate HRV spectral analysis and BRS values.

摘要

目的

本研究旨在探讨是否可以使用统计模型,根据头高位倾斜试验(HUTT)早期阶段获得的心率变异性(HRV)和压力反射敏感性(BRS)数据,对头高位倾斜试验结果进行早期预测。

方法

采用改良的意大利方案对105例有血管迷走性晕厥病史的患者进行头高位倾斜试验。连续记录逐搏心率和血压。采用快速傅里叶变换对心率变异性进行频谱分析,并采用序列技术测量压力反射敏感性。

结果

基于头高位倾斜试验前15分钟的心率变异性和压力反射敏感性数据建立的线性统计模型,并不比总是天真地预测晕厥会发生的多数类更准确(平均模型样本外准确率为56.2±5.1%,而多数类相对频率为54.2%)。即使在模型中使用头高位倾斜试验前30分钟的心率变异性和压力反射敏感性数据,我们也没有得到任何具有实际意义的预测结果(准确率为75.0±5.1%,而多数类为72.2%)。

结论

虽然头高位倾斜试验阳性(HUTT-P)和头高位倾斜试验阴性(HUTT-N)的受试者之间存在明显且有意义的差异,但这些差异不足以区分两组,并在头高位倾斜试验早期预测晕厥。更大样本量的研究结果可能会有所改善;然而,我们可以得出结论,从综合心率变异性频谱分析和压力反射敏感性值中获得具有实际价值的晕厥预测不太可能。

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本文引用的文献

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Can the result of a tilt test be predicted in the first five minutes?倾斜试验的结果能否在最初的 5 分钟内预测?
Cardiol J. 2011;18(5):521-6. doi: 10.5603/cj.2011.0007.
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Europace. 2010 Aug;12(8):1149-55. doi: 10.1093/europace/euq149. Epub 2010 May 20.
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Blood pressure oscillations during tilt testing as a predictive marker of vasovagal syncope.
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Quantitative Complexity Theory Used in the Prediction of Head-Up Tilt Testing Outcome.用于预测头高位倾斜试验结果的定量复杂性理论。
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