English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Objective: Postural Orthostatic Tachycardia Syndrome (POTS) is associatedwith the onset of tachycardia upon postural change. The current diagnosisinvolves the measurement of heart rate (HR) and blood pressure (BP) duringhead-up tilt (HUT) or active standing test. A positive diagnosis is made if HRchanges with more than 30 bpm (40 bpm in patients aged 12-19 years), ignoringall of the BP and most of the HR signals. This study examines 0.1 Hzoscillations in systolic arterial blood pressure (SBP) and HR signals providingadditional metrics characterizing the dynamics of the baroreflex. Methods: Weanalyze 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 minutesof baseline and 5 minutes of HUT. We employ Uniform Phase Empirical ModeDecomposition (UPEMD) to extract 0.1 Hz stationary modes from both signals anduse random forest machine learning and k-means clustering to analyze theoutcomes. Results show that the amplitude of the 0.1 Hz oscillations is higherin 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 amplitudeof SBP and HR 0.1 Hz oscillation and a shortening of the phase between the twosignals. Significance: The 0.1 Hz phase response and oscillation amplitudemetrics provide new markers that can improve POTS diagnostic augmenting theexisting diagnosis protocol only analyzing the change in heart rate.

Characterization of blood pressure and heart rate oscillations of POTS patients via uniform phase empirical mode decomposition