A PATIENT SPECIFIC ALGORITHM AND APPLICATION FOR OPTIMAL BLOOD PRESSURE MANAGEMENT IN PATIENTS WITH CORONARY ARTERY DISEASE

Abstract

Management of patients with HTN and coronary artery disease (CAD) confronts the problem of lowering BP to reduce the severity of atherosclerosis and avoiding excessive DBP reduction which compromises coronary blood flow (CBF). Clinicians must also take into account the severity of CAD, and LV mass which reflects myocardial oxygen demand. The purpose of this study was two-fold; to produce a patient specific algorithm that utilizes clinic DBP, LV mass and coronary stenosis to estimate CBF and to create an easily accessible application to help guide clinicians in patient management. Our previous work developed non-parametric models that incorporated fractional flow reserve (FFR) measured at the time of coronary angiography and left ventricular mass measured by echocardiography. This study sought to validate these equations on a series of 81 patients who had CAD, clinic DBP measured by an automated device and LV mass assessed by an echocardiogram. Data on the severity of CAD were obtained from either coronary angiogram or coronary computerized tomography angiogram (CCTA). FFR was calculated from the degree of coronary stenosis based on published estimates of its relationships to the severity of coronary stenosis. This web application was constructed using HTML, CSS, Javascript, and open source bootstrap template. There was a highly significant correlation (r=0.565; p < 0.01) between DBP and estimated CBF (ml/g LV mass/body surface area). More severe coronary stenosis and greater LV mass significantly correlated (r=0.734, p < 0.01) with reduced CBF. An algorithm to estimate CBF was developed based on the regression data analysis with clinic DBP, LV mass and degree of coronary stenosis. The algorithm provided guidance at multiple levels. For example, for the same degree of coronary stenosis, the absolute level of DBP became increasingly a more important consideration for CBF at lower DBP while LVMI had greater contribution to reductions in CBF at higher DBP. The application integrated our data in an easily accessible user interface that estimates CBF. We validated an estimate of CBF in patient with CAD using measurement of the severity of CAD by CCTA or coronary angiography, LV mass and DBP. We then developed a software to permit clinicians to manage HTN in patients with CAD. With this new approach, clinicians can utilize clinic DBP, echocardiographic assessment of LV mass and coronary stenosis determined either from coronary angiography or CCTA to guide target DBP and avoid excessive reduction in CBF and optimize blood pressure control.