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The normal response to postural challenge is characterised by maintenance of relatively stable blood pressure (BP) and heart rate (HR) after 30 sec to 30 min of head-up tilt. The objective of the present study was to determine the degree of instability of cardiovascular responses to postural challenge in normotensive and hypertensive subjects. In the initial phase of the study, two groups of age and sex-matched subjects were assessed: essential hypertension (n = 20) and healthy (n = 37). The BP and HR were recorded at 5-min intervals during the course of the 10-min supine-30-min head-up tilt test (HUTT). We categorised 'BP-change' as the difference between individual BP measurements during HUTT and the last recumbent BP value, divided by latter value. The average and standard deviation (SD) of the recorded BP changes were calculated, and BP changes were plotted along a time curve. A computerised image analyser then calculated the outline ratio (OR) and fractal dimension (FD) values for each of the curves. An identical process evaluated measurements for HR-changes. BP- and HR-changes were then converted into absolute numbers, and the average, SD, OR, and FD were calculated. A multivariate analysis was conducted, evaluating independent predictors of hypertension. Finally, an equation for the calculation of 'haemodynamic instability score' (HIS) was deduced and a cut-off between HIS of hypertensive and normotensive subjects was established. Independent predictors of the cardiovascular response to postural challenge of hypertensives (Group I) vs healthy (Group II) were: a.DIAST-FD, a.HR-AVG, a.HR-SD, a.HR-FD, DIAS-SD and HR-SD and HR-SD. Based on these five predictors, a linear discriminant score was computed and called the Haemodynamic Instability Score (HIS): HIS = 59.4 + (-16.6*a.DIAST-FD) + (-29.0*a.HR-AVG) + (-82.4*a.HR-SD) + (-30.1*a.HR-FD) + (-57.9*DIAS-SD) + (73.4*HR-SD) The HIS values in Group I (hypertensives) were: avg = 3.348, SD = 2.863, and 95% CI for... [ABSTRACT FROM AUTHOR]

Methods used for the assessment of cardiovascular reactivity are flawed by nonlinear dynamics of the cardiovascular responses to stimuli. In an attempt to address this issue, we utilized a short postural challenge, recorded beat-to-beat heart rate (HR) and pulse transit time (PTT), assessed the data by fractal and recurrence quantification analysis, and processed the obtained variables by multivariate statistics. A 10-min supine phase of the head-up tilt test was followed by recording 600 cardiac cycles on tilt, that is, 5-10 min. Three groups of patients were studied, each including 20 subjects matched for age and gender — healthy subjects, patients with essential hypertension (HT), and patients with chronic fatigue syndrome (CFS). The latter group was studied on account of the well-known dysautonomia of CFS patients, which served as contrast against the cardiovascular reactivity of the healthy population. A total of 52 variables of the HR and PTT were determined in each subject. The multivariate model identified the best predictors for the assessment of reactivity of healthy subjects vs CFS. Based on these predictors, the 'Fractal & Recurrence Analysis-based Score' (FRAS) was calculated: FRAS = 76.2+0.04*HRsupine-DET -12.9*HR-tilt-RIL -0.31*HR-tilt-s.d. -19.27*PTT-tilt-RIL -9.42*PTT-tilt-WAVE. The median values and IQR of FRAS in the groups were: healthy = -1.85 (IQR 1.89), hypertensives = +0.52 (IQR 5.78), and CFS = -24.2 (5.34) (HT vs healthy subjects: P = -0.0036; HT vs CFS: P < 0.0001). Since the FRAS differed significantly between the three groups, it appears likely that the FRAS may recognize phenotypes of cardiovascular reactivity. [ABSTRACT FROM AUTHOR]