This study aimed to develop a method to distinguish between the cardiovascular reactivity in chronic fatigue syndrome (CFS) and other patient populations. Patients with CFS (n = 23), familial Mediterranean fever (n = 15), psoriatic arthritis (n = 10), generalized anxiety disorder (n = 12), neurally mediated syncope (n = 20), and healthy subjects (n = 20) were evaluated with a shortened head-up tilt test (HUTT). A 10-minute supine phase of the HUTT was followed by recording 600 cardiac cycles on tilt, i. e., 5 to 10 minutes. Beat-to-beat heart rate (HR) and pulse transit time (PTT) were acquisitioned. Data were processed by recurrence plot and fractal analysis. Fifty-two variables were calculated in each subject. On multivariate analysis, the best predictors of CFS were HR-tilt-R/L, PTT-tilt-R/L, HR-supine-DET, PTT-tilt-WAVE, and HR-tilt-SD. Based on these predictors, the ‘Fractal & Recurrence Analysis-based Score’ (FRAS) was calculated: FRAS = 76.2 + 0.04*HR-supine-DET – 12.9*HR-tilt-R/L – 0.31*HR-tilt-SD – 19.27*PTT-tilt-R/L – 9.42* PTT-tilt-WAVE. The best cut-off differentiating CFS from the control population was FRAS = + 0.22. FRAS > + 0.22 was associated with CFS (sensitivity 70 % and specificity 88 %). The cardiovascular reactivity received mathematical expression with the aid of the FRAS. The shortened HUTT was well tolerated. The FRAS provides objective criteria which could become valuable in the assessment of CFS.

OBJECTIVES:To evaluate the cardiovascular response to postural challenge in patients with chronic fatigue syndrome (CFS) and to determine whether the degree of instability of the cardiovascular response may aid in diagnosing CFS.METHODS:Patients with CFS (n = 25) and their age- and gender-matched healthy controls (n = 37), patients with fibromyalgia (n = 30), generalized anxiety disorder (n = 15), and essential hypertension (n = 20) were evaluated with the aid of a standardized tilt test. The blood pressure (BP) and heart rate (HR) were recorded during 10 minutes of recumbence and 30 minutes of head-up tilt. We designated BP changes as the differences between successive BP values and the last recumbent BP. The average and standard deviation (SD) were calculated. Time curves of BP differences were loaded into a computerized image analyzer, and their outline ratios and fractal dimensions were measured. HR changes were determined similarly. The average and SD of the parameters were calculated, and intergroup comparisons were performed.RESULTS:On multivariate analysis, the independent predictors of CFS patients versus healthy controls were the fractal dimension of absolute values of the systolic BP changes (SYST-FD.abs), the standard deviation of the current values of the systolic BP changes (SYST-SD.cur), and the standard deviation of the current values of the heart rate changes (HR-SD.cur). The following equation was deduced to calculate the hemodynamic instability score (HIS) in the individual patient: HIS = 64.3303 + (SYST-FD.abs x -68.0135) + (SYST-SD.cur x 111.3726) + (HR-SD.cur x 60.4164). The best cutoff differentiating CFS from the healthy controls was -0.98. HIS values >-0.98 were associated with CFS (sensitivity 97%, specificity 97%). The HIS differed significantly between CFS and other groups (P <.0001) except for generalized anxiety disorder. Group averages (SD) of HIS were CFS = +3.72 (5.02), healthy = -4.62 (2.26), fibromyalgia = -3.27 (2.63), hypertension = -5.53 (2.24), and generalized anxiety disorder = +1.08 (5.2).CONCLUSION:The HIS adds objective criteria confirming the diagnosis of CFS.