Hypertension is the primary risk factor for many forms of cardiovascular diseases, which are the leading cause of death in the developed world. Hypertension and myocardial ischemia are also main contributors to stroke, which results in serious and long-term disability. Early detection, monitoring, and treatment of hypertension and myocardial ischemia are thus important in the delay or prevention of morbidity and mortality from cardiovascular diseases. This thesis investigates new hemodynamic markers that are critical in the diagnosis and assessment of the severity of hypertension and myocardial ischemia. Experimental data was obtained from anesthetized mongrel dogs for control, hypertension, vasodilation, and myocardial ischemia. Simultaneously recorded aortic pressure and aortic flow waveforms were digitized for calculations of hemodynamic parameters. Model-based linear and nonlinear arterial compliances, the compliance- pressure relationship, and different augmentation indices for assessing the effects of wave reflections were computed and evaluated as markers of hypertension. Analysis of the modified three-element nonlinear Windkessel model or the Li- Model revealed a nonlinear blood pressure and arterial compliance relationship and indicated that this model better predicts the blood pressure waveforms during hypertension and vasodilation. The compliance-pressure loops constructed for a single beat demonstrated reduced compliance during hypertension and increased compliance during vasodilation and ischemia. Analysis of the augmentation index revealed that blood pressure is indeed augmented in systole during hypertension and reduced during vasodilation and ischemia. The newly presented methods for augmentation index calculation are also shown to be better indicators of wave reflection effects in hypertension. Thus, these new nonlinear compliance and augmentation indices may be useful markers in the diagnosis and treatment of hypertension.
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Biomedical Engineering
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Rutgers University Electronic Theses and Dissertations
Rutgers University. Graduate School - New Brunswick
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