A15-1 Pulse wave analysis independently discriminates between subjects with recurrent vasovagal syncope and healthy controls

EP Europace ◽  
2003 ◽  
Vol 4 (Supplement_2) ◽  
pp. B22-B22
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J. Simek ◽  
D. Wichterle ◽  
V. Melenovsky ◽  
L. Rychly ◽  
J. Malik ◽  
...  
2014 ◽  
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Simon Pecha ◽  
Samer Hakmi ◽  
Iris Wilke ◽  
Yalin Yildirim ◽  
Boris Hoffmann ◽  
...  

EP Europace ◽  
2018 ◽  
Vol 20 (suppl_1) ◽  
pp. i110-i111
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J-H Jang ◽  
J-H Park ◽  
K-Y Ko ◽  
Y S Beak ◽  
S-W Kwan ◽  
...  

2020 ◽  
Vol 43 (7) ◽  
pp. 781-788
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Ji‐Hun Jang ◽  
Jin‐Hee Park ◽  
Kyu‐Yong Ko ◽  
Yong‐Soo Baek ◽  
Sung‐Woo Kwon ◽  
...  

2010 ◽  
Vol 213 (2) ◽  
pp. 469-474 ◽  
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Catherine T. Prince ◽  
Aaron M. Secrest ◽  
Rachel H. Mackey ◽  
Vincent C. Arena ◽  
Lawrence A. Kingsley ◽  
...  

Hypertension ◽  
2021 ◽  
Vol 78 (Suppl_1) ◽  
Author(s):  
Sagar Nagpal ◽  
Debduti Mukhopadhyay ◽  
Peter Osmond ◽  
Joseph E Schwartz ◽  
Joseph L Izzo

BP is highly variable within and between individuals but the impact of variation in underlying hemodynamic components is unknown. We tested the feasibility and clinical associations of quantitated variances in MAP and its hemodynamic components [heart rate (HR), stroke volume (SV) and total vascular resistance (TVR)] obtained by 24-hr ambulatory pulse wave analysis (PWA, Mobil-O-Graph, IEM, Stolzberg, DE). BP and PWA were measured every 20 min for 24 hrs. Indexed to body surface area, MAP = HR*[SV index (SVI)]*[TVR index (TVRI)]; ln(MAP) = ln(HR) + ln(SVI) + ln(TVRI); and total MAP variability = var [ln(MAP)] = covariance (cov)[ln(HR), ln(MAP)] + cov[ln(SVI), ln(MAP)] + cov[ln(TVRI), ln(MAP)]. Relative contributions to var[ln(MAP)] for each hemodynamic component (as %) were calculated and associations with demographic characteristics were analyzed by correlations and t-tests. We studied 152 people (49% women, 23% black); mean(SD): # readings 57(11), age 59(16) yr, BMI 29.9(6.5) kg/m 2 , systolic BP 135(18) and MAP 106(14) mmHg. Mean(SD) 24-hr values were: ln(MAP) 4.64 (0.13), ln(HR) 4.20 (0.15), ln(SVI) -3.32 (0.15), and ln(TVRI) 3.75 (0.18). Relative contributions of hemodynamic components to total 24-hr ln(MAP) variation were: TVRI 54(36)%, HR 33(38)%, and SVI 13(40)%. The large SDs of these relative contributions led to analysis of potential contributing factors: TVRI contribution was correlated with 24-hr mean MAP (r=0.24, p=0.003) and was higher (>54%) in males (p=0.03) and blacks (p=0.04); HR contribution was inversely related to MAP (r=-0.26, p=0.001), age (r=-0.29, p=0.0003) and BMI (r=-0.173 p=0.05) and was lower (<33%) in blacks (p=0.008); SVI contribution was correlated with age (r=0.31, p<0.0001) and BMI (r=0.23, p=0.005) and was higher (>13%) in women (p=0.03). We conclude that 24-hr ambulatory PWA can identify components of MAP variation within individuals and their associations with demographic factors. The relative contributions of hemodynamic components (HR, SV, TVR) to 24-hr variability in ln(MAP) varies systematically with 24-hr mean MAP, age, race, gender, and BMI. Theoretical clinical implications may include therapeutic adjustments for extremes of variation in HR (beta-blockers), TVR (vasodilators) or SV (diuretics).


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