Evidence map›Paper›PMID 27220369›Full record

ArticleCirculation. Cardiovascular quality and outcomes2016

Predicting Adverse Outcomes After Myocardial Infarction Among Patients With Diabetes Mellitus.

Suzanne V Arnold, John A Spertus, Philip G Jones, Darren K McGuire, Kasia J Lipska, Yaping Xu, Joshua M Stolker, Abhinav Goyal, Mikhail Kosiborod

Abstract readMulticenter StudyValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Circulation. Cardiovascular quality and outcomes, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Low-Dose Colchicine for Secondary Prevention in Patients With Chronic Coronary Syndrome: A Multicenter Real-World Study.Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions · 2026
    Observational
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  13. Clinical Characteristics and Prognosis of Young Patients with Coronary Heart Disease.Medical science monitor : international medical journal of experimental and clinical research · 2020
    Article
  14. Observational
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  16. Observational
  17. Hemoglobin ACardiovascular diabetology · 2017
    Article
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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.

Suzanne V ArnoldFrom the Saint Luke's Mid America Heart Institute, Kansas City, MO (S.V.A., J.A.S., P.G.J., M.K.); University of Missouri-Kansas City (S.V.A., J.A.S., M.K.); University of Texas Southwestern Medical Center, Dallas (D.K.M.); Yale University School of Medicine, New Haven, CT (K.J.L.); Genentech, South San Francisco, CA (Y.X.); Saint Louis University, St. Louis, MO (J.M.S.); and Emory School of Medicine, Atlanta, GA (A.G.). suz.v.arnold@gmail.com.
John A SpertusFrom the Saint Luke's Mid America Heart Institute, Kansas City, MO (S.V.A., J.A.S., P.G.J., M.K.); University of Missouri-Kansas City (S.V.A., J.A.S., M.K.); University of Texas Southwestern Medical Center, Dallas (D.K.M.); Yale University School of Medicine, New Haven, CT (K.J.L.); Genentech, South San Francisco, CA (Y.X.); Saint Louis University, St. Louis, MO (J.M.S.); and Emory School of Medicine, Atlanta, GA (A.G.).
Philip G JonesFrom the Saint Luke's Mid America Heart Institute, Kansas City, MO (S.V.A., J.A.S., P.G.J., M.K.); University of Missouri-Kansas City (S.V.A., J.A.S., M.K.); University of Texas Southwestern Medical Center, Dallas (D.K.M.); Yale University School of Medicine, New Haven, CT (K.J.L.); Genentech, South San Francisco, CA (Y.X.); Saint Louis University, St. Louis, MO (J.M.S.); and Emory School of Medicine, Atlanta, GA (A.G.).
Darren K McGuireFrom the Saint Luke's Mid America Heart Institute, Kansas City, MO (S.V.A., J.A.S., P.G.J., M.K.); University of Missouri-Kansas City (S.V.A., J.A.S., M.K.); University of Texas Southwestern Medical Center, Dallas (D.K.M.); Yale University School of Medicine, New Haven, CT (K.J.L.); Genentech, South San Francisco, CA (Y.X.); Saint Louis University, St. Louis, MO (J.M.S.); and Emory School of Medicine, Atlanta, GA (A.G.).
Kasia J LipskaFrom the Saint Luke's Mid America Heart Institute, Kansas City, MO (S.V.A., J.A.S., P.G.J., M.K.); University of Missouri-Kansas City (S.V.A., J.A.S., M.K.); University of Texas Southwestern Medical Center, Dallas (D.K.M.); Yale University School of Medicine, New Haven, CT (K.J.L.); Genentech, South San Francisco, CA (Y.X.); Saint Louis University, St. Louis, MO (J.M.S.); and Emory School of Medicine, Atlanta, GA (A.G.).
Yaping XuFrom the Saint Luke's Mid America Heart Institute, Kansas City, MO (S.V.A., J.A.S., P.G.J., M.K.); University of Missouri-Kansas City (S.V.A., J.A.S., M.K.); University of Texas Southwestern Medical Center, Dallas (D.K.M.); Yale University School of Medicine, New Haven, CT (K.J.L.); Genentech, South San Francisco, CA (Y.X.); Saint Louis University, St. Louis, MO (J.M.S.); and Emory School of Medicine, Atlanta, GA (A.G.).
Joshua M StolkerFrom the Saint Luke's Mid America Heart Institute, Kansas City, MO (S.V.A., J.A.S., P.G.J., M.K.); University of Missouri-Kansas City (S.V.A., J.A.S., M.K.); University of Texas Southwestern Medical Center, Dallas (D.K.M.); Yale University School of Medicine, New Haven, CT (K.J.L.); Genentech, South San Francisco, CA (Y.X.); Saint Louis University, St. Louis, MO (J.M.S.); and Emory School of Medicine, Atlanta, GA (A.G.).
Abhinav GoyalFrom the Saint Luke's Mid America Heart Institute, Kansas City, MO (S.V.A., J.A.S., P.G.J., M.K.); University of Missouri-Kansas City (S.V.A., J.A.S., M.K.); University of Texas Southwestern Medical Center, Dallas (D.K.M.); Yale University School of Medicine, New Haven, CT (K.J.L.); Genentech, South San Francisco, CA (Y.X.); Saint Louis University, St. Louis, MO (J.M.S.); and Emory School of Medicine, Atlanta, GA (A.G.).
Mikhail KosiborodFrom the Saint Luke's Mid America Heart Institute, Kansas City, MO (S.V.A., J.A.S., P.G.J., M.K.); University of Missouri-Kansas City (S.V.A., J.A.S., M.K.); University of Texas Southwestern Medical Center, Dallas (D.K.M.); Yale University School of Medicine, New Haven, CT (K.J.L.); Genentech, South San Francisco, CA (Y.X.); Saint Louis University, St. Louis, MO (J.M.S.); and Emory School of Medicine, Atlanta, GA (A.G.).

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Yale Study Support Suite (YES3): Dashboard and Web Portal Software Supporting Research Workflow through integrated, customizable REDCap External ModulesP30AG021342 · NIA · YALE UNIVERSITY · PI Albert C Shaw · 2002 to 2026
$37.9M
SCCOR in Cardiac Dysfunction and DiseaseP50HL077113 · NHLBI · WASHINGTON UNIVERSITY · PI KELLY, DANIEL PATRICK · 2005 to 2009
$13.4M
Predicting Severe Hypoglycemia among Older Adults with DiabetesK23AG048359 · NIA · YALE UNIVERSITY · PI LIPSKA, KASIA JOANNA · 2014 to 2018
$778k
NCATS NIH HHS UL1 TR001863NHLBI NIH HHS P50 HL077113NIA NIH HHS K23 AG048359NIA NIH HHS P30 AG021342
6 · The paper itself

Abstract

backgroundAlthough patients with diabetes mellitus experience high rates of adverse events after acute myocardial infarction (AMI), including death and recurrent ischemia, some diabetic patients are likely at low risk, whereas others are at high risk. We sought to develop prediction models to stratify risk after AMI in patients with diabetes mellitus. METHODS AND

resultsWe developed prediction models for long-term mortality and angina among 1613 patients with diabetes mellitus discharged alive after AMI from 24 US hospitals and then validated the models in a separate, multicenter registry of 786 patients with diabetes mellitus. Event rates in the derivation cohort were 27% for 5-year mortality and 27% for 1-year angina. Parsimonious prediction models demonstrated good discrimination (c-indices=0.78 and 0.69, respectively) and excellent calibration. Within the context of the predictors we estimated, the strongest predictors for mortality were higher creatinine, not working at the time of the AMI, older age, lower hemoglobin, left ventricular dysfunction, and chronic heart failure. The strongest predictors for angina were angina burden in the 4 weeks before the AMI, younger age, history of prior coronary bypass graft surgery, and non-white race. The lowest and highest deciles of predicted risk ranged from 4% to 80% for mortality and 12% to 59% for angina. The models also performed well in external validation (c-indices=0.78 and 0.73, respectively).

conclusionsWe found a wide range of risk for adverse outcomes after AMI in diabetic patients. Predictive models can identify patients with diabetes mellitus for whom closer follow-up and aggressive secondary prevention strategies should be considered.

Indexed as

AgedAngina PectorisDecision Support TechniquesDiabetes MellitusFemaleHumansKaplan-Meier EstimateMaleMiddle AgedMyocardial InfarctionPredictive Value of TestsPrognosisProportional Hazards ModelsRegistriesReproducibility of ResultsRisk Assessmentangina pectorisdiabetes mellitusmyocardial infarction

Identifiers

PMID27220369
PMCPMC5341790

What OpenQuestion holds

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Registered trials

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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.