On the feasibility of tilt test outcome early prediction using ECG and pressure parameters

Abstract

The tilt test is a valuable clinical tool for vasovagal syncope (VVS) diagnostic, and its early prediction from simple ECG and blood pressure-based parameters has widely been studied in the literature. However, no practical system is currently used in the clinical setting for the early prediction of the tilt test outcome. The objectives of this study were (1) to benchmark the early prediction performance of all the previously proposed parameters, when nonlinearly combined; (2) to try to improve this performance with the inclusion of additional information and processing techniques. We analyzed a database of 727 consecutive cases of tilt test. Previously proposed features were measured from heart rate and systolic/diastolic pressure tachograms, in several representative signal segments. We aimed to improve the prediction performance: first, using new nonlinear features (detrended fluctuation analysis and sample entropy); second, using a multivariable nonlinear classifier (support vector machine); and finally, including additional physiological signals (stroke volume). The predictive performance of the nonlinearly combined previously proposed features was limited [area under receiver operating characteristic curve (ROC) 0.57 ± 0.12], especially at the beginning of the test, which is the most clinically relevant period. The improvement with additional available physiological information was limited too. We conclude that the use of a system for tilt test outcome prediction with current knowledge and processing should be considered with caution, and that further effort has to be devoted to understand the mechanisms of VVS.

Entropy Measures in Analysis of Head up Tilt Test Outcome for Diagnosing Vasovagal Syncope

“…The idea of looking for such a predictor was also considered by other researchers [ 46 , 47 , 48 , 49 , 50 , 51 ]. The criterion for a negative HUTT outcome based on heart rate (HR) analysis during 6 min following an upright tilt was proposed by Mallat et al [ 50 ].…”

Kernel based support vector machine for the early detection of syncope during head-up tilt test

“…Previous studies have suggested an early prediction of the tilt test outcomes (Mallat et al 1997, Bellard et al 2001, Schang et al 2007, Gimeno-Blanes et al 2011. The original aspects of our study are (1) the population included in this work, containing only asymptomatic subjects, (2) the use of non-linear parameters that have shown interesting results in previous studies and (3) the applied signal processing and classification methods, with varying time support that enabled the identification of the information content of the Early15 phase.…”

“…Several methods have been proposed for this purpose such as the time-and frequency-domain analyses of RR series extracted from ECG (Madrid et al 1994, Lippman et al 1995, the early response of HR to HUTT (Mallat et al 1997, Sumiyoshi et al 2000, Movahed and Hassapoyannes 2001, the analysis of BP changes (Pitzalis et al 2002), the joint assessment of HR and BP changes (Bellard et al 2001, Virag et al 2007 and processing transthoracic impedance waveforms (TI) (Schang et al 2007). Few studies have evaluated the non-linear characteristics of HRV during HUTT (Gimeno-Blanes et al 2011). This is due to the fact that most of the non-linear analysis techniques require long-duration time series, greater than those typically recorded in HUTT.…”