Literature DB >> 14660993

Anginal symptoms consistently predict total mortality among outpatients with coronary artery disease.

Dariush Mozaffarian1, Chris L Bryson, John A Spertus, Mary B McDonell, Stephan D Fihn.   

Abstract

BACKGROUND: Age, race, education, and diabetes have been associated with differences in anginal symptoms, treatments, and outcomes among outpatients with coronary artery disease (CAD), but there is little data on whether such characteristics affect relationships between anginal symptoms and mortality.
METHODS: Using a prospective cohort design, we examined associations of anginal symptoms, as assessed by the Seattle Angina Questionnaire, with total mortality among 8908 outpatients with CAD to investigate whether this relationship is influenced by patient demographic or clinical characteristics. Potential effect modification was primarily assessed for age, race, education, and diabetes, and secondarily assessed for smoking, prevalent congestive heart failure (CHF), myocardial infarction, and coronary revascularization.
RESULTS: Over 2 years mean follow-up, there were 896 deaths. After adjustment for potential confounders, persons reporting greater physical limitation due to angina had higher mortality: 27% higher with mild limitation (hazard ratio [HR] 1.27, 95% CI 0.98-1.64), 61% higher with moderate limitation (HR 1.61, 95% CI 1.27-2.05), and 2.5-fold higher with the greatest limitation (HR 2.55, 95% CI 1.97-3.30), compared with little or no limitation (P for trend <.001). Anginal instability was also independently predictive of mortality. There was little evidence that these relationships varied by age, race, education, diabetes, smoking, or presence of CHF, prior myocardial infarction, or prior coronary revascularization (P for each interaction >.28). Anginal symptoms predicted higher mortality risk comparable to a decade of age difference, presence of diabetes, or presence of CHF.
CONCLUSIONS: Among outpatients with CAD, self-reported anginal symptoms consistently predict mortality irrespective of differences in age, race, education, or clinical comorbidities.

Entities:  

Mesh:

Year:  2003        PMID: 14660993     DOI: 10.1016/S0002-8703(03)00436-8

Source DB:  PubMed          Journal:  Am Heart J        ISSN: 0002-8703            Impact factor:   4.749


  34 in total

1.  Low education as a risk factor for undiagnosed angina.

Authors:  Michael M McKee; Paul C Winters; Kevin Fiscella
Journal:  J Am Board Fam Med       Date:  2012 Jul-Aug       Impact factor: 2.657

2.  The association of angina pectoris with heart disease mortality among men and women by diabetes status: the Rancho Bernardo Study.

Authors:  Kimbach T Carpiuc; Deborah L Wingard; Donna Kritz-Silverstein; Elizabeth Barrett-Connor
Journal:  J Womens Health (Larchmt)       Date:  2010-08       Impact factor: 2.681

3.  Small Dense Low-Density Lipoprotein Cholesterol Predicts Cardiovascular Events in Liver Transplant Recipients.

Authors:  Mohammad Bilal Siddiqui; Tamoore Arshad; Samarth Patel; Emily Lee; Somaya Albhaisi; Arun J Sanyal; R Todd Stravitz; Carolyn Driscoll; Richard K Sterling; Trevor Reichman; Chandra Bhati; Mohammad Shadab Siddiqui
Journal:  Hepatology       Date:  2019-03-29       Impact factor: 17.425

4.  Physical function and independence 1 year after myocardial infarction: observations from the Translational Research Investigating Underlying disparities in recovery from acute Myocardial infarction: Patients' Health status registry.

Authors:  John A Dodson; Suzanne V Arnold; Kimberly J Reid; Thomas M Gill; Michael W Rich; Frederick A Masoudi; John A Spertus; Harlan M Krumholz; Karen P Alexander
Journal:  Am Heart J       Date:  2012-05       Impact factor: 4.749

5.  Frequency of angina pectoris and secondary events in patients with stable coronary heart disease (from the Heart and Soul Study).

Authors:  Alexis L Beatty; John A Spertus; Mary A Whooley
Journal:  Am J Cardiol       Date:  2014-07-16       Impact factor: 2.778

6.  Development and validation of a short version of the Seattle angina questionnaire.

Authors:  Paul S Chan; Philip G Jones; Suzanne A Arnold; John A Spertus
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2014-09-02

7.  Frequency, predictors, and consequences of crossing over to revascularization within 12 months of randomization to optimal medical therapy in the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) trial.

Authors:  John A Spertus; David J Maron; David J Cohen; Paul Kolm; Pam Hartigan; William S Weintraub; Daniel S Berman; Koon K Teo; Leslee J Shaw; Steven P Sedlis; Merril Knudtson; Mihaela Aslan; Marcin Dada; William E Boden; G B John Mancini
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2013-07-09

8.  Association of smoking status with health-related outcomes after percutaneous coronary intervention.

Authors:  Jae-Sik Jang; Donna M Buchanan; Kensey L Gosch; Philip G Jones; Praneet K Sharma; Ali Shafiq; Anna Grodzinsky; Timothy J Fendler; Garth Graham; John A Spertus
Journal:  Circ Cardiovasc Interv       Date:  2015-05       Impact factor: 6.546

9.  Inducible ischemia and the risk of recurrent cardiovascular events in outpatients with stable coronary heart disease: the heart and soul study.

Authors:  Anil K Gehi; Sadia Ali; Beeya Na; Nelson B Schiller; Mary A Whooley
Journal:  Arch Intern Med       Date:  2008-07-14

10.  Clinical and Economic Implications of Inconclusive Noninvasive Test Results in Stable Patients With Suspected Coronary Artery Disease: Insights From the PROMISE Trial.

Authors:  Akash Goyal; Neha Pagidipati; C Larry Hill; Brooke Alhanti; James E Udelson; Michael H Picard; Patricia A Pellikka; Udo Hoffmann; Daniel B Mark; Pamela S Douglas
Journal:  Circ Cardiovasc Imaging       Date:  2020-04-09       Impact factor: 7.792

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.