Literature DB >> 17721747

Serum uric acid shows a J-shaped trend with coronary mortality in non-insulin-dependent diabetic elderly people. The CArdiovascular STudy in the ELderly (CASTEL).

A Mazza1, S Zamboni, E Rizzato, A C Pessina, V Tikhonoff, L Schiavon, E Casiglia.   

Abstract

The relationship between serum uric acid (SUA) and risk of coronary heart disease (CHD) mortality remains controversial, particularly in diabetic subjects. The aim of the present study is to evaluate whether SUA independently predicts CHD mortality in non-insulin-dependent elderly people from the general population and to investigate the interactions between SUA and other risk factors. Five hundred and eighty-one subjects aged >/=65 years with non-insulin-dependent diabetes mellitus were prospectively studied in the frame of the CArdiovascular STudy in the ELderly (CASTEL). Historical and clinical data, blood tests and 12-year fatal events were recorded. SUA as a continuous item was divided into tertiles and, for each tertile, adjusted relative risk (RR) with 95% confidence intervals (CI) was derived from multivariate Cox analysis. CHD mortality was predicted by SUA in a J-shaped manner. Mortality rate was 7.9% (RR 1.28, CI 1.05-1.72), 6.0% (reference tertile) and 12.1% (RR 1.76, CI 1.18-2.27) in the increasing tertiles of SUA, respectively, without any difference between genders. In diabetic elderly subjects, SUA independently predicts the risk of CHD mortality in a J-shaped manner.

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Year:  2007        PMID: 17721747     DOI: 10.1007/s00592-007-0249-3

Source DB:  PubMed          Journal:  Acta Diabetol        ISSN: 0940-5429            Impact factor:   4.280


  28 in total

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2.  Serum uric acid does not predict cardiovascular or all-cause mortality in type 2 diabetes: the Fremantle Diabetes Study.

Authors:  G Ong; W A Davis; T M E Davis
Journal:  Diabetologia       Date:  2010-03-30       Impact factor: 10.122

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Journal:  Mech Ageing Dev       Date:  2011-01-22       Impact factor: 5.432

5.  How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Biodemographic Models and Methods in Genetic Analyses of Longitudinal Data.

Authors:  Anatoliy I Yashin; Konstantin G Arbeev; Deqing Wu; Liubov Arbeeva; Alexander Kulminski; Irina Kulminskaya; Igor Akushevich; Svetlana V Ukraintseva
Journal:  N Am Actuar J       Date:  2016-06-22

6.  The quadratic hazard model for analyzing longitudinal data on aging, health, and the life span.

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Journal:  Phys Life Rev       Date:  2012-05-17       Impact factor: 11.025

7.  Uric Acid Is Associated With Inflammation, Coronary Microvascular Dysfunction, and Adverse Outcomes in Postmenopausal Women.

Authors:  Megha Prasad; Eric L Matteson; Joerg Herrmann; Rajiv Gulati; Charanjit S Rihal; Lilach O Lerman; Amir Lerman
Journal:  Hypertension       Date:  2016-12-19       Impact factor: 10.190

Review 8.  How the effects of aging and stresses of life are integrated in mortality rates: insights for genetic studies of human health and longevity.

Authors:  Anatoliy I Yashin; Konstantin G Arbeev; Liubov S Arbeeva; Deqing Wu; Igor Akushevich; Mikhail Kovtun; Arseniy Yashkin; Alexander Kulminski; Irina Culminskaya; Eric Stallard; Miaozhu Li; Svetlana V Ukraintseva
Journal:  Biogerontology       Date:  2015-08-18       Impact factor: 4.277

9.  Genetic model for longitudinal studies of aging, health, and longevity and its potential application to incomplete data.

Authors:  Konstantin G Arbeev; Igor Akushevich; Alexander M Kulminski; Liubov S Arbeeva; Lucy Akushevich; Svetlana V Ukraintseva; Irina V Culminskaya; Anatoli I Yashin
Journal:  J Theor Biol       Date:  2009-02-04       Impact factor: 2.691

10.  Elevated serum uric acid concentrations independently predict cardiovascular mortality in type 2 diabetic patients.

Authors:  Giacomo Zoppini; Giovanni Targher; Carlo Negri; Vincenzo Stoico; Fabrizia Perrone; Michele Muggeo; Enzo Bonora
Journal:  Diabetes Care       Date:  2009-06-19       Impact factor: 19.112

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