Open AccessWindkessel Measures Derived From Pressure Waveforms Only: The Framingham Heart Study
Author(s) -
Behnam Vira,
Rong Jian,
Larson Martin G.,
Gotal John D.,
Benjamin Emelia J.,
Hamburg Naomi M.,
Vasan Ramachandran S.,
Mitchell Gary F.
Publication year - 2019
Publication title -
journal of the american heart association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.494
H-Index - 85
ISSN - 2047-9980
DOI - 10.1161/jaha.119.012300
Subject(s) - medicine , cardiology , hazard ratio , blood pressure , framingham heart study , framingham risk score , confounding , proportional hazards model , percentile , disease , confidence interval , statistics , mathematics
Background Waveform parameters derived from pressure‐only Windkessel models are related to cardiovascular disease risk and could be useful for understanding arterial system function. However, prior reports varied in their adjustment for potential confounders. Methods and Results Carotid tonometry waveform data from 2539 participants (mean age 63±11 years, 58% women) of the Framingham Heart Study were used to derive Windkessel measures using pressure and assuming a linear model with fixed diastolic time constant (τ dias ) and variable asymptotic pressure (P inf , median 54.5; 25th, 75th percentiles: 38.4, 64.9 mm Hg) or nonlinear model with inverse pressure‐dependent τ dias and fixed P inf (20 mm Hg). During follow‐up (median 15.1 years), 459 (18%) participants had a first cardiovascular disease event. In proportional hazards models adjusted for age, sex, total cholesterol, high‐density lipoprotein cholesterol, smoking, antihypertensive medication use, diabetes mellitus, and physician‐acquired systolic blood pressure, only the systolic time constant (τ sys ) derived from the nonlinear model was related to risk for cardiovascular disease events (hazard ratio=0.91 per 1 SD, 95% CI=0.84–0.99, P =0.04). When heart rate was added to the model, τ sys (hazard ratio=0.92, CI=0.84–1.00, P =0.04) and reservoir pressure amplitude (hazard ratio=1.14, CI=1.01–1.28, P =0.04) were related to events. In contrast, measures derived from the linear model were not related to events in models that adjusted for risk factors including systolic blood pressure ( P >0.31) and heart rate ( P >0.19). Conclusions Our results suggest that pressure‐only Windkessel measures derived by using a nonlinear model may provide incremental risk stratification, although associations were modest and further validation is required.