Evidence map›Paper›PMID 27266420›Full record

ArticleThe Annals of thoracic surgery2016

Predicting Likelihood for Coronary Artery Bypass Grafting After Non-ST-Elevation Myocardial Infarction: Finding the Best Prediction Model.

Ali Shafiq, Jae-Sik Jang, Faraz Kureshi, Timothy J Fendler, Kensey Gosch, Phil G Jones, David J Cohen, Richard Bach, John A Spertus

Abstract readMulticenter Study
In one paragraph

Article in The Annals of thoracic surgery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Medical Fuzzy-Expert System for Assessment of the Degree of Anatomical Lesion of Coronary Arteries.International journal of environmental research and public health · 2023
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Ali ShafiqCardiovascular Outcomes Research, Saint Luke's Mid America Heart Institute, Kansas City, Missouri; Division of Cardiology, University of Missouri, Kansas City, Missouri. Electronic address: shafiqa@umkc.edu.
Jae-Sik JangDivision of Cardiology, Inje University Busan Paik Hospital, Busan, Korea.
Faraz KureshiCardiovascular Outcomes Research, Saint Luke's Mid America Heart Institute, Kansas City, Missouri; Division of Cardiology, University of Missouri, Kansas City, Missouri.
Timothy J FendlerCardiovascular Outcomes Research, Saint Luke's Mid America Heart Institute, Kansas City, Missouri; Division of Cardiology, University of Missouri, Kansas City, Missouri.
Kensey GoschCardiovascular Outcomes Research, Saint Luke's Mid America Heart Institute, Kansas City, Missouri.
Phil G JonesCardiovascular Outcomes Research, Saint Luke's Mid America Heart Institute, Kansas City, Missouri; Division of Cardiology, University of Missouri, Kansas City, Missouri.
David J CohenCardiovascular Outcomes Research, Saint Luke's Mid America Heart Institute, Kansas City, Missouri; Division of Cardiology, University of Missouri, Kansas City, Missouri.
Richard BachDivision of Cardiology, Washington University School of Medicine, St. Louis, Missouri.
John A SpertusCardiovascular Outcomes Research, Saint Luke's Mid America Heart Institute, Kansas City, Missouri; Division of Cardiology, University of Missouri, Kansas City, Missouri.

Funding

SCCOR in Cardiac Dysfunction and DiseaseP50HL077113 · NHLBI · WASHINGTON UNIVERSITY · PI KELLY, DANIEL PATRICK · 2005 to 2009
$13.4M
CARDIOVASCULAR OUTCOMES RESEARCH TRAINING PROGRAMT32HL110837 · NHLBI · UNIVERSITY OF MISSOURI KANSAS CITY · PI JOHN A SPERTUS · 2012 to 2026
$5.0M
NHLBI NIH HHS P50 HL077113NHLBI NIH HHS T32 HL110837
6 · The paper itself

Abstract

backgroundUp to half of patients with non-ST-elevation myocardial infarction (NSTEMI) do not receive dual antiplatelet therapy before angiography "pretreatment" because of the risk of increased bleeding if coronary artery bypass grafting (CABG) operation is needed. Several models have been published that predict the likelihood of CABG after NSTEMI, but they have not been independently validated. The purpose of this study was to validate these models and improve the best one.

methodsWe studied patients with NSTEMI who were enrolled in the 24-center Translational Research Investigating Underlying Disparities in Acute Myocardial Infarction Patients' Health Status (TRIUMPH) registry between 2005 and 2008. Previous CABG prediction models were assessed using c-statistics and calibration assessments to determine the best model. Variables from TRIUMPH likely to be associated with CABG were tested to see whether they could improve the best model's performance.

resultsAmong 2,473 patients with NSTEMI, 11.8% underwent in-hospital CABG. C-statistics for the Modified Thrombolysis in Myocardial Infarction, Treat Angina With Aggrastat and Determine the Cost of Therapy With an Invasive or Conservative Strategy-Thrombolysis in Myocardial Infarction 18, Poppe, and Global Risk of Acute Coronary Events (GRACE) models were 0.54, 0.61, 0.61, and 0.62, respectively. The GRACE model showed the best discrimination and calibration. From the TRIUMPH registry, preselected variables were added to the GRACE model but did not significantly improve model discrimination. A GRACE model risk score of less than 9 had high sensitivity (96%), thus making it useful for predicting patients with NSTEMI who were at low risk for requiring CABG, which included approximately 21% of patients with NSTEMI.

conclusionsThis study could not improve on the GRACE model, which had the best predictive value for identifying a need for CABG after NSTEMI with a broader range of predicted risk levels and high sensitivity, especially in patients with scores lower than 9.

Indexed as

AgedCoronary AngiographyCoronary Artery BypassCoronary Artery DiseaseDatabases, FactualElectrocardiographyFemaleFollow-Up StudiesHumansLikelihood FunctionsMaleMiddle AgedModels, CardiovascularNon-ST Elevated Myocardial InfarctionPredictive Value of TestsQualitative Research

Identifiers

PMID27266420
PMCPMC5145468

What OpenQuestion holds

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Registered trials

None linked

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.