Pulse wave analysis of the aortic pressure waveform in patients with vasovagal syncope

An analysis of vascular properties using pulse wave analysis in patients with vasovagal syncope

BACKGROUND

Vasovagal syncope (VVS) is a common cause of recurrent syncope. Nevertheless, the exact hemodynamic mechanism has not been elucidated. Pulse wave analysis (PWA) is widely used to evaluate vascular properties, as it reflects the condition of the entire arterial system.

HYPOTHESIS

Cardiovascular autonomic modulation may influence the hemodynamic mechanism and result in different vascular properties between VVS patients and healthy individuals.

METHODS

We enrolled consecutive patients diagnosed with VVS on head-up tilt testing from January 2014 to August 2019. Healthy subjects were enrolled as the control group. We performed PWA on all participants. Using propensity score matching, we assembled a study population with similar baseline characteristics and compared hemodynamic parameters.

RESULTS

A total of 111 VVS patients (43 ± 18 years, 72 females) and 475 healthy control subjects (48 ± 13 years, 192 females) were enrolled. Compared to the healthy control subjects, the VVS patients had a higher augmentation index (AIx) adjusted to a heart rate of 75 beats per minute (AIx@HR75, 20.5 ± 13.1% vs 16.7 ± 11.9%, P = .003). After 1:1 matched comparison (111 matched control), VVS patients consistently showed higher AIx@HR75 (20.5 ± 13.1% vs 16.7 ± 12.9%, P = .02) than the matched control group. According to age distribution, VVS patients showed significantly higher AIx@HR75 (10.6 ± 11.7% vs 2.5 ± 11.1%, P = .01) in a young age (15-33 years) group.

CONCLUSIONS

VVS patients had greater arterial stiffness than healthy subjects. This is one of the plausible mechanisms of the pathophysiology of VVS.

Prediction of the Time to Syncope Occurrence in Patients Diagnosed with Vasovagal Syncope

OBJECTIVE

In this study we aimed to predict the time to syncope occurrence (TSO) in patients with vasovagal syncope (VVS), solely based on measurements recorded during the supine position of the head-up tilt (HUT) testing protocol.

METHODS

We extracted various time and frequency domain features related to morphological aspects of arterial blood pressure (ABP) and the electrocardiogram (ECG) raw signals as well as to dynamic interactions between beat-to-beat ABP, heart rate, and cerebral blood flow velocity. From these we identified the most predictive features related to TSO.

RESULTS

Specifically, when no orthostatic stress is involved, TSO in VVS patients can be predicted with high accuracy from a set of only five ECG features.