Windkessel Measures Derived From Pressure Waveforms Only: The Framingham Heart Study

Area of Science:

• Cardiovascular Physiology
• Biomedical Engineering
• Epidemiology

Background:

• Windkessel models analyze arterial system function using pressure waveforms.
• Previous studies showed varied results due to confounder adjustments.
• Accurate Windkessel parameter derivation is crucial for cardiovascular risk assessment.

Purpose of the Study:

• To evaluate the utility of pressure-only Windkessel model parameters in predicting cardiovascular disease (CVD) risk.
• To compare linear versus nonlinear Windkessel models for risk stratification.
• To assess the incremental predictive value of Windkessel measures beyond established CVD risk factors.

Main Methods:

• Utilized carotid tonometry waveform data from 2539 Framingham Heart Study participants.
• Derived Windkessel measures using both linear (fixed diastolic time constant) and nonlinear (pressure-dependent diastolic time constant) models.
• Employed proportional hazards models, adjusting for multiple CVD risk factors, to assess event prediction.

Main Results:

• The systolic time constant (τ_sys) from the nonlinear model significantly predicted CVD events (HR=0.91, P=0.04) after adjustment for confounders.
• When heart rate was included, τ_sys (HR=0.92, P=0.04) and reservoir pressure amplitude (HR=1.14, P=0.04) remained significant predictors.
• Measures derived from the linear Windkessel model did not show significant associations with CVD events (P>0.19).

Conclusions:

• Nonlinear pressure-only Windkessel model parameters, particularly τ_sys, may offer incremental cardiovascular disease risk stratification.
• These findings suggest a potential role for advanced Windkessel analysis in understanding arterial hemodynamics and risk.
• Further validation is necessary to confirm the clinical utility and robustness of these associations.