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

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.

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.

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).

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.