T he initiation of lifelong primary prevention therapy for cardiovascular disease in a high-risk patient should be based on a shared decision-making process between patient and doctor following the clear presentation of appropriate information, including the quantification of the risks and benefits expected from treatment and the cost and inconvenience (disutility) to the patient. This ideal scenario is almost never achieved. Editorial see p 2500 Clinical Perspective on p 2546Currently, primary prevention practice focuses on risk stratification by using population-based statistical estimates to determine which individuals would have most to gain from preventative therapy.1 Doctors are documented to view risks differently from patients, and both have difficulty in evaluating, perceiving, and conveying risks and benefits in an easily understood manner.2-5 The benefits of primary prevention are thus often presented to the patient without formal quantification of the cost, harms, or inconvenience they might incur. However, patients do understand risks and trade-offs 3 and trust doctors more when presented with numeric information than when given vague interpretations of risk. 6Previous interventions, aimed at improving adherence, have used new methods to convey cardiovascular risk rather than tackling the underlying reasons why people stop medication. The focus has been on individual counseling, and on quantitative and graphical displays, or the use of imaging techniques such as coronary CT scans to improve risk perception. [7][8][9] These are based on the principle that better risk perception will lead to higher adherence and persistence with primary prevention therapy. 10-12Patient inconvenience, or medication disutility, has rarely been taken into consideration when initiating therapy. Knowing one's risk to be high does not necessarily mean that one will, must, or even should take a preventive step. Taking action depends on many factors, and a large part of a patient's resistance to treatment involves the reluctance to embark on a Background-Primary prevention guidelines focus on risk, often assuming negligible aversion to medication, yet most patients discontinue primary prevention statins within 3 years. We quantify real-world distribution of medication disutility and separately calculate the average utilities for a range of risk strata. Method and Results-We randomly sampled 360 members of the general public in London. Medication aversion was quantified as the gain in lifespan required by each individual to offset the inconvenience (disutility) of taking an idealized daily preventative tablet. In parallel, we constructed tables of expected gain in lifespan (utility) from initiating statin therapy for each age group, sex, and cardiovascular risk profile in the population. This allowed comparison of the widths of the distributions of medication disutility and of group-average expectation of longevity gain. Observed medication disutility ranged from 1 day to >10 years of life being required by subjects (median, 6...

Impact of variability in the measured parameter is rarely considered in designing clinical protocols for optimization of atrioventricular (AV) or interventricular (VV) delay of cardiac resynchronization therapy (CRT). In this article, we approach this question quantitatively using mathematical simulation in which the true optimum is known and examine practical implications using some real measurements. We calculated the performance of any optimization process that selects the pacing setting which maximizes an underlying signal, such as flow or pressure, in the presence of overlying random variability (noise). If signal and noise are of equal size, for a 5-choice optimization (60, 100, 140, 180, 220 ms), replicate AV delay optima are rarely identical but rather scattered with a standard deviation of 45 ms. This scatter was overwhelmingly determined (ρ = −0.975, P < 0.001) by Information Content, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\frac{\text{Signal}}{{{\text{Signal}} + {\text{Noise}}}}} $$\end{document}, an expression of signal-to-noise ratio. Averaging multiple replicates improves information content. In real clinical data, at resting, heart rate information content is often only 0.2–0.3; elevated pacing rates can raise information content above 0.5. Low information content (e.g. <0.5) causes gross overestimation of optimization-induced increment in VTI, high false-positive appearance of change in optimum between visits and very wide confidence intervals of individual patient optimum. AV and VV optimization by selecting the setting showing maximum cardiac function can only be accurate if information content is high. Simple steps to reduce noise such as averaging multiple replicates, or to increase signal such as increasing heart rate, can improve information content, and therefore viability, of any optimization process.

C entral (aortic) blood pressure (BP) waveform indices independently predict cardiovascular events and all-cause mortality, 1 but the physiological mechanisms to explain the waveform morphology remain disputed. The well-established wave reflection theory ascribes transmission of discrete forward and backward (incident and reflected) waves as the principal contributory factor underlying the shape of the central BP waveform.2 However, while providing a plausible description of central BP morphology, recent studies have concluded that the influence of discrete reflected waves on central BP may be less than originally conceived, and this is probably because of wave dispersion along the aorta and entrapment of reflected waves in the periphery. 3,4 Indeed, augmentation of central BP may be largely attributable to forward wave propagation (as a result of left ventricular [LV] ejection) and proximal aortic reservoir function. [5][6][7][8][9] Importantly, wave separation theory obscures the pressure buffering role of the highly elastic proximal aorta (ie, the aortic reservoir), and a failure to consider this function may lead to incorrect interpretations of the physiology underlying central BP waveform morphology.The reservoir-excess pressure concept is an alternate method proposed to explain the underlying physiology of the aortic BP waveform. This method has been used invasively to study changes in aortic BP associated with both aging and exercise. 6,8 Moreover, indices derived from this model were recently shown to predict cardiovascular events (fatal and nonfatal) and procedures independent from brachial BP and other conventional cardiovascular risk parameters (eg, age, sex, cholesterol, smoking, diabetes mellitus), including Framingham risk score, in an analysis of the Conduit Artery Function Evaluation study. 10 In accounting for the reservoir function of the aorta, 7,11 the reservoir-excess pressure model is founded on the basis that aortic BP can be separated into © 2014 American Heart Association, Inc.