PubMed Health⌕ Search

PubMed · 12621978

[Salt sensitivity and hypertension].

Abstract

For many years there has been ongoing controversy concerning the presumed relationship between salt intake and population blood pressure. In addition, in light of the availability of many efficient antihypertensive drugs and the frequent difficulty to motivate patients to maintain prolonged salt restriction, clinicians often doubt the importance of salt restriction in the individual treatment of hypertension. Accumulating data now underline the importance of a restriction of salt intake on a population level. This is expressed in a recent advice of the Dutch Health Council (Gezondheidsraad) and governmental intervention in some other countries. However, it is not the level of salt intake but salt sensitivity of blood pressure which predicts the effect of salt restriction in the individual treatment of essential hypertension. It should be noted that salt restriction or depletion will increase the sensitivity to other antihypertensive drugs in each form of hypertension. Recent data suggest that salt sensitivity per se should be viewed as an independent risk factor for cardiovascular morbidity and mortality. Therefore, identification and aggressive treatment of salt-sensitive hypertension, including salt restriction, is indicated. Demographic and racial characteristics as well as additional laboratory investigation may help identifying potential 'salt-sensitive' subjects, who form part of a high-risk population.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

E F H van Bommel. 2003-02-08. [Salt sensitivity and hypertension].. https://pubmed.ncbi.nlm.nih.gov/12621978/

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↗