 Postural Orthostatic Tachycardia Syndrome (POTS) is associated with the onset of tachycardia upon postural change. The current diagnosis involves the measurement of heart rate (HR) and blood pressure (BP) during head-up tilt (HUT) or active standing test. A positive diagnosis is made if HR changes with more than 30 bpm (40 bpm in patients aged 12-19 years), ignoring all of the BP and most of the HR signals. This study examines 0.1 Hz oscillations in systolic arterial blood pressure (SBP) and HR signals providing additional metrics characterizing the efficacy of the baroreflex.  We analyze data from 28 control subjects and 28 POTS patients who underwent HUT. We extract beat-to-beat HR and SBP during a 10 min interval including 5 minutes of baseline and 5 minutes of HUT. We employ Uniform Phase Empirical Mode Decomposition (UPEMD) to extract 0.1 Hz stationary modes from both signals and use random forest machine learning and k-means clustering to analyze the outcomes. Results show that the amplitude of the 0.1 Hz oscillations is higher in POTS patients and that the phase response between the two signals is shorter (p < 0.005).  POTS is associated with an increase in the amplitude of SBP and HR 0.1 Hz oscillation and a shortening of the phase between the two signals.  The 0.1 Hz phase response and oscillation amplitude metrics provide new markers that can improve POTS diagnostic augmenting the existing diagnosis protocol only analyzing the change in heart rate.
Objective: Postural Orthostatic Tachycardia Syndrome (POTS) is associated with the onset of tachycardia upon postural change. The current diagnosis involves the measurement of heart rate (HR) and blood pressure (BP) during head-up tilt (HUT) or active standing test. A positive diagnosis is made if HR changes with more than 30 bpm (40 bpm in patients aged 12-19 years), ignoring all of the BP and most of the HR signals. This study examines 0.1 Hz oscillations in systolic arterial blood pressure (SBP) and HR signals providing additional metrics characterizing the dynamics of the baroreflex. Methods: We analyze data from 28 control subjects and 28 POTS patients who underwent HUT. We extract beat-to-beat HR and SBP during a 10 min interval including 5 minutes of baseline and 5 minutes of HUT. We employ Uniform Phase Empirical Mode Decomposition (UPEMD) to extract 0.1 Hz stationary modes from both signals and use random forest machine learning and k-means clustering to analyze the outcomes. Results show that the amplitude of the 0.1 Hz oscillations is higher in POTS patients and that the phase response between the two signals is shorter (p < 0.005). Conclusion: POTS is associated with an increase in the amplitude of SBP and HR 0.1 Hz oscillation and a shortening of the phase between the two signals. Significance: The 0.1 Hz phase response and oscillation amplitude metrics provide new markers that can improve POTS diagnostic augmenting the existing diagnosis protocol only analyzing the change in heart rate.
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