Evidence map›Paper›PMID 17032691›Full record

ArticleBMJ (Clinical research ed.)2006

Prediction of risk of death and myocardial infarction in the six months after presentation with acute coronary syndrome: prospective multinational observational study (GRACE).

Keith A A Fox, Omar H Dabbous, Robert J Goldberg, Karen S Pieper, Kim A Eagle, Frans Van de Werf, Alvaro Avezum, Shaun G Goodman, Marcus D Flather, Frederick A Anderson and 1 more

2 registry-linked trialsAbstract readMulticenter Study
In one paragraph

Article in BMJ (Clinical research ed.), 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 607 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
607citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03646019 unknown statusnot on this mapstarted 2018, after this paper: background citation

Serum Oxidative Status as a Potential Predictor of Coronary Artery Disease.

TypeobservationalSponsorProf. Tony hayek MDRan2018 to 2019Enrolled200ConditionsCoronary Artery Disease, Paraoxanase 1, Thiobarbituric Acid Reactive Substances, Thiol Groups
NCT06993415 recruitingnot on this mapstarted 2025, after this paper: background citation

Optimize Risk Prediction After Myocardial Infarction Through Artificial Intelligence and Multidimensional Evaluation: The ORACLE Study

TypeobservationalSponsorFundación Pública Andaluza para la Investigación de Málaga en Biomedicina y SaludRan2025 to 2028Enrolled750ConditionsMyocardial Infarction (MI)Armsdata collection
3 · Its place in the literature

Who cites it

607 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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547 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Keith A A FoxRoyal Infirmary of Edinburgh, University of Edinburgh, Edinburgh EH16 4SB. k.a.a.fox@ed.ac.uk
Omar H Dabbous
Robert J Goldberg
Karen S Pieper
Kim A Eagle
Frans Van de Werf
Alvaro Avezum
Shaun G Goodman
Marcus D Flather
Frederick A Anderson
Christopher B Granger

Funding

Strengthening Stakeholder Engagement in Human Research Protections.UL1TR002003 · NCATS · UNIVERSITY OF ILLINOIS AT CHICAGO · PI KARNIK, NIRANJAN SUBHASH, MERMELSTEIN, ROBIN J. · 2016 to 2024
$33.7M
NCATS NIH HHS UL1 TR002003
6 · The paper itself

Abstract

objectiveTo develop a clinical risk prediction tool for estimating the cumulative six month risk of death and death or myocardial infarction to facilitate triage and management of patients with acute coronary syndrome.

designProspective multinational observational study in which we used multivariable regression to develop a final predictive model, with prospective and external validation.

settingNinety four hospitals in 14 countries in Europe, North and South America, Australia, and New Zealand. POPULATION: 43,810 patients (21,688 in derivation set; 22,122 in validation set) presenting with acute coronary syndrome with or without ST segment elevation enrolled in the global registry of acute coronary events (GRACE) study between April 1999 and September 2005.

main outcome measuresDeath and myocardial infarction.

results1989 patients died in hospital, 1466 died between discharge and six month follow-up, and 2793 sustained a new non-fatal myocardial infarction. Nine factors independently predicted death and the combined end point of death or myocardial infarction in the period from admission to six months after discharge: age, development (or history) of heart failure, peripheral vascular disease, systolic blood pressure, Killip class, initial serum creatinine concentration, elevated initial cardiac markers, cardiac arrest on admission, and ST segment deviation. The simplified model was robust, with prospectively validated C-statistics of 0.81 for predicting death and 0.73 for death or myocardial infarction from admission to six months after discharge. The external applicability of the model was validated in the dataset from GUSTO IIb (global use of strategies to open occluded coronary arteries).

conclusionsThis risk prediction tool uses readily identifiable variables to provide robust prediction of the cumulative six month risk of death or myocardial infarction. It is a rapid and widely applicable method for assessing cardiovascular risk to complement clinical assessment and can guide patient triage and management across the spectrum of patients with acute coronary syndrome.

Indexed as

Epidemiologic MethodsFemaleHumansMaleMyocardial InfarctionMyocardial IschemiaPrognosisSeverity of Illness IndexSyndromeTriage

Identifiers

PMID17032691
PMCPMC1661748

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.