Predicting vasovagal syncope from heart rate and blood pressure: A prospective study in 140 subjects.

Background: We developed a vasovagal syncope (VVS) prediction algorithm for use during head-up tilt with simultaneous analysis of heart rate (HR) and systolic blood pressure (SBP). We previously tested this algorithm retrospectively in 1155 subjects, showing sensitivity 95%, specificity 93%, and median prediction time 59 seconds.

Objective: The purpose of this prospective, single-center study of 140 subjects was to evaluate this VVS prediction algorithm and to assess whether retrospective results were reproduced and clinically relevant.

Parametric estimation of pulse arrival time: a robust approach to pulse wave velocity.

Pulse wave velocity (PWV) is a surrogate of arterial stiffness and represents a non-invasive marker of cardiovascular risk. The non-invasive measurement of PWV requires tracking the arrival time of pressure pulses recorded in vivo, commonly referred to as pulse arrival time (PAT). In the state of the art, PAT is estimated by identifying a characteristic point of the pressure pulse waveform.

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

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.