Literature DB >> 14975466

The prognostic importance of comorbidity for mortality in patients with stable coronary artery disease.

Molly Sachdev1, Jie Lena Sun, Anastasios A Tsiatis, Charlotte L Nelson, Daniel B Mark, James G Jollis.   

Abstract

OBJECTIVES: To identify the prevalent and prognostically important coexisting illnesses among single coronary artery disease (CAD) patients.
BACKGROUND: As the population ages, physicians are increasingly required to make decisions concerning patients with multiple co-existing illnesses (comorbidity). Many trials of CAD therapy have excluded patients with significant comorbidity, such that there are limited data to guide the management of those patients.
METHODS: To consider the long-term prognostic importance of comorbid illness, we examined a cohort of 1471 patients with CAD who underwent cardiac catheterization between 1985 and 1989 and were followed up through 2000 in the Duke Databank for Cardiovascular Diseases. Weights were assigned to individual diseases according to their prognostic significance in Cox proportional hazards models, thus creating a new CAD-specific index. The new index was compared with the widely used Charlson index, according to prevalence of conditions, individual and overall associations with survival, and agreement.
RESULTS: The Charlson index and the CAD-specific index were highly associated with long-term survival and almost equivalent to left ventricular ejection fraction. When considering the components of the Charlson index, diabetes, renal insufficiency, chronic obstructive pulmonary disease, and peripheral vascular disease had greater prognostic significance among CAD patients, whereas peptic ulcer disease, connective tissue disease, and lymphoma were less significant. Hemiplegia, leukemia, lymphoma, severe liver disease, and acquired immunodeficiency syndrome were rarely identified among patients undergoing coronary angiography.
CONCLUSIONS: Comorbid disease is strongly associated with long-term survival in patients with CAD. These data suggest co-existing illnesses should be measured and considered in clinical trials, disease registries, quality comparisons, and counseling of individual patients.

Entities:  

Mesh:

Year:  2004        PMID: 14975466     DOI: 10.1016/j.jacc.2003.10.031

Source DB:  PubMed          Journal:  J Am Coll Cardiol        ISSN: 0735-1097            Impact factor:   24.094


  42 in total

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2.  Hematopoietic cell transplantation specific comorbidity index as an outcome predictor for patients with acute myeloid leukemia in first remission: combined FHCRC and MDACC experiences.

Authors:  Mohamed L Sorror; Sergio Giralt; Brenda M Sandmaier; Marcos De Lima; Munir Shahjahan; David G Maloney; H Joachim Deeg; Frederick R Appelbaum; Barry Storer; Rainer Storb
Journal:  Blood       Date:  2007-09-14       Impact factor: 22.113

3.  Predicting prognosis in stable angina--results from the Euro heart survey of stable angina: prospective observational study.

Authors:  Caroline A Daly; Bianca De Stavola; Jose L Lopez Sendon; Luigi Tavazzi; Eric Boersma; Felicity Clemens; Nicholas Danchin; Francois Delahaye; Anselm Gitt; Desmond Julian; David Mulcahy; Witold Ruzyllo; Kristian Thygesen; Freek Verheugt; Kim M Fox
Journal:  BMJ       Date:  2006-01-13

4.  Temporal trends in permanent pacemaker implantation: a population-based study.

Authors:  Daniel Z Uslan; Imad M Tleyjeh; Larry M Baddour; Paul A Friedman; Sarah M Jenkins; Jennifer L St Sauver; David L Hayes
Journal:  Am Heart J       Date:  2008-02-19       Impact factor: 4.749

5.  A disease-specific comorbidity index for predicting mortality in patients admitted to hospital with a cardiac condition.

Authors:  Lorenzo Azzalini; Malorie Chabot-Blanchet; Danielle A Southern; Anna Nozza; Stephen B Wilton; Michelle M Graham; Guillaume Marquis Gravel; Jean-Pierre Bluteau; Jean-Lucien Rouleau; Marie-Claude Guertin; E Marc Jolicoeur
Journal:  CMAJ       Date:  2019-03-18       Impact factor: 8.262

6.  Comparison of frail patients versus nonfrail patients ≥65 years of age undergoing percutaneous coronary intervention.

Authors:  S Michael Gharacholou; Veronique L Roger; Ryan J Lennon; Charanjit S Rihal; Jeff A Sloan; John A Spertus; Mandeep Singh
Journal:  Am J Cardiol       Date:  2012-03-20       Impact factor: 2.778

7.  Influence of explanatory and confounding variables on HRQoL after controlling for measurement bias and response shift in measurement.

Authors:  Pranav K Gandhi; L Douglas Ried; Carole L Kimberlin; Teresa L Kauf; I-Chan Huang
Journal:  Expert Rev Pharmacoecon Outcomes Res       Date:  2013-12       Impact factor: 2.217

Review 8.  Frailty and its potential relevance to cardiovascular care.

Authors:  Mandeep Singh; Karen Alexander; Veronique L Roger; Charanjit S Rihal; Heather E Whitson; Amir Lerman; Arschad Jahangir; K Sreekumaran Nair
Journal:  Mayo Clin Proc       Date:  2008-10       Impact factor: 7.616

9.  Role of comorbidities in optimizing decision-making for allogeneic hematopoietic cell transplantation.

Authors:  Mohamed L Sorror; Rainer F Storb
Journal:  Mediterr J Hematol Infect Dis       Date:  2010-06-09       Impact factor: 2.576

Review 10.  A brief review of chronic exercise intervention to prevent autonomic nervous system changes during the aging process.

Authors:  Rogério Brandão Wichi; Kátia De Angelis; Lia Jones; Maria Claudia Irigoyen
Journal:  Clinics (Sao Paulo)       Date:  2009       Impact factor: 2.365

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