PubMed Health⌕ Search

PubMed · 10596763

Treating multiple-risk hypertensive populations.

Abstract

The majority of patients with hypertension have one or more additional risk factors for cardiovascular disease. In planning an appropriate treatment program, it is useful to identify and stratify hypertensive patients according to their risk of developing cardiovascular, cerebrovascular, or renal disease. At particular risk are the elderly, patients with diabetes, and those with target-organ damage manifested by impaired renal function. Evidence supports increased risk in these patients, and clinical trial results demonstrate the considerable benefits realized through aggressive blood pressure (BP) control. The number of elderly individuals continues to increase in the United States and other industrialized countries. The prevalence of isolated systolic hypertension (ISH) is higher in the elderly than in younger individuals. ISH is associated with significant morbidity and mortality and should not be considered a physiologic manifestation of the normal aging process. Type 2 diabetes is also increasing in prevalence. Patients with diabetes are at increased risk for coronary heart disease, stroke, renal failure, and other cardiovascular complications. Aggressive treatment of elevated BP can produce dramatic decreases in the cardiovascular complications of diabetes. The incidence of end-stage renal disease has increased 2.5-fold in the past two decades, and poorly controlled BP is a major contributor to the increase. Lowering BP to levels well below the traditional goal of 140/90 mm Hg is needed to slow the progression of renal dysfunction and prevent renal failure in hypertensive patients with renal disease, whether related to diabetes or to another etiology. Aggressive treatment of hypertension in multiple-risk populations (to the goals of JNC VI and the recent WHO-ISH Guidelines for the Management of Hypertension) can be expected to produce significant reductions in the incidence and prevalence of stroke, heart failure, coronary heart disease, chronic renal failure, and total cardiovascular mortality.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

S Oparil. 1999. Treating multiple-risk hypertensive populations.. https://doi.org/10.1016/s0895-7061(99)00206-x

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Tree-structured gatekeeping tests in clinical trials with hierarchically ordered multiple objectives.

This paper discusses a new class of multiple testing procedures, tree-structured gatekeeping procedures, with clinical trial applications. These procedures arise in clinical trials with hierarchically ordered multiple objectives, for example, in the context of multiple dose-control tests with logical restrictions or analysis of multiple endpoints. The proposed approach is based on the principle of closed testing and generalizes the serial and parallel gatekeeping approaches developed by Westfall and Krishen (J. Statist. Planning Infer. 2001; 99:25-41) and Dmitrienko et al. (Statist. Med. 2003; 22:2387-2400). The proposed testing methodology is illustrated using a clinical trial with multiple endpoints (primary, secondary and tertiary) and multiple objectives (superiority and non-inferiority testing) as well as a dose-finding trial with multiple endpoints.

Antihypertensive Agents↗

Bayesian analysis of latent variable models with non-ignorable missing outcomes from exponential family.

To provide a comprehensive framework for analysing complex non-normal medical and biological data, we propose a Bayesian approach for a non-linear latent variable model with covariates, and non-ignorable missing data, under the exponential family of distributions. The non-ignorable missing mechanism is defined via a logistic regression model. Based on conjugate prior distributions, full conditional distributions for the implementation of Markov chain Monte Carlo methods in simulating observations from the joint posterior distribution are derived. These observations are used in computing the Bayesian estimates, as well as in implementing a path sampling procedure to evaluate the Bayes factor for model comparison. The proposed methods are illustrated using real data from a study on the non-adherence of hypertension patients.

Antihypertensive Agents↗

Revisiting the relation between change and initial value: a review and evaluation.

The relation between initial disease status and subsequent change following treatment has attracted great interest in clinical research. However, statisticians have repeatedly warned against correlating/regressing change with baseline due to two methodological concerns known as mathematical coupling and regression to the mean. Oldham's method and Blomqvist's formula are the two most often adopted methods to rectify these problems. The aims of this article are to review briefly the proposed solutions in the statistical and psychological literature, and to clarify the popular misconception that Blomqvist's formula is superior to Oldham's method. We argue that this misconception is due to a failure to recognize that the heterogeneity of individual responses to treatment is a source of regression to the mean in the analysis of the relation between change and initial value. Furthermore, we demonstrate how each method actually answers different research questions, and how confusion arises when this is not always understood.

Antihypertensive Agents↗