Predictors of 90-day outcome in patients stabilized after acute coronary syndromes

Predictors of 90-day outcome in patients stabilized after acute coronary syndromes

Aims We investigated predictors of 90-day risk among patients surviving the early period after an acute coronary syndrome (ACS). Methods and Results The study population included 15 904 stabilized ST-segment elevation or non-ST-segment elevation ACS patients randomized in SYMPHONY and 2nd SYMPHONY....

Full description

Saved in:
Bibliographic Details
Published in:European heart journal Vol. 24; no. 2; pp. 172 - 181
Main Authors: Newby, L.K, Bhapkar, M.V, White, H.D, Topol, E.J, Dougherty, F.C, Harrington, R.A, Smith, M.C, Asarch, L.F, Califf, R.M
Format: Journal Article
Language:English
Published: Oxford Oxford University Press 01-01-2003
Subjects:
Acute coronary syndromes
Aged
Biological and medical sciences
Cardiology. Vascular system
Coronary heart disease
Follow-Up Studies
Heart
Humans
Medical sciences
Models, Biological
Myocardial Infarction - mortality
Myocardial Infarction - therapy
Myocardial Ischemia - mortality
Myocardial Ischemia - therapy
outcomes
Predictive Value of Tests
Prognosis
Recurrence
Risk Factors
risk models
risk stratification
Switzerland - epidemiology
Switzerland
Human
Prognosis
risk stratification
Predictor
Acute
Prediction
Cardiovascular disease
Risk
Coronary heart disease
Phlebology
risk moders
outcomes
Risk factor
Evolution
Circulatory system
Cardiology
Predictive factor
Stratification
Acute coronary syndromes
Day
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Aims We investigated predictors of 90-day risk among patients surviving the early period after an acute coronary syndrome (ACS). Methods and Results The study population included 15 904 stabilized ST-segment elevation or non-ST-segment elevation ACS patients randomized in SYMPHONY and 2nd SYMPHONY. We developed risk models for death, death or myocardial infarction (MI), and death, MI, or severe recurrent ischaemia (SRI) using Cox proportional-hazards techniques. Demographic, history, and pre-randomization clinical and medication variables were tested. Validation techniques included development of individual trial models, backward elimination and bootstrapping. Of 118 variables, 17 independently predicted mortality. The strongest associations included greater age (χ2=31.1), higher randomization heart rate (χ2=27.4), and heart failure (HF) variables (HF between qualifying event and randomization, χ2=21.8; history of HF, χ2=12.2). Higher creatinine clearance (χ2=17.7) and percutaneous coronary intervention between qualifying event and randomization (χ2=11.1) most strongly predicted lower risk. Similar characteristics entered the double and triple composite models, but HF variables and age less strongly predicted these end-points. Conclusions In patients stabilized after ACS, those at highest risk over the next 90 days can be identified. Typical clinical markers are better at identifying risk of death than non-fatal MI or SRI. Novel risk markers are needed for these outcomes.
Bibliography:istex:0ACBF99E6BE10F1A604065D75F3F3703755B9FA6
local:0.2003251.172
ark:/67375/HXZ-640J0QQW-6
Correspondence: L. Kristin Newby, MD, Duke Clinical Research Institute, P.O. Box 17969, Durham, NC, 27715-7969, U.S.A.
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
ObjectType-News-3
content type line 23
ISSN:0195-668X
1522-9645
DOI:10.1016/S0195-668X(02)00325-1