Evidence map›Paper›PMID 35165703›Full record

ArticleEuropean heart journal2022

Estimation of recurrent atherosclerotic cardiovascular event risk in patients with established cardiovascular disease: the updated SMART2 algorithm.

Steven H J Hageman, Ailsa J McKay, Peter Ueda, Laura H Gunn, Tomas Jernberg, Emil Hagström, Deepak L Bhatt, Ph Gabriel Steg, Kristi Läll, Reedik Mägi and 17 more

Open access · bronzeAbstract read
In one paragraph

Article in European heart journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 1 pooled it
22.2field-weighted citation impact, top 1% of its field
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

59 citing papers in PubMed, 1 synthesis or guideline pooled it, 108 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

27 authors at 17 institutions in 11 countries.

Steven H J HagemanDepartment of Vascular Medicine, University Medical Center Utrecht, PO Box 85500, 3508 GA Utrecht, The Netherlands.ORCID 0000-0003-2299-6745
Ailsa J McKayDepartment of Primary Care and Public Health, Imperial College London, London, UK.ORCID 0000-0003-4138-4963
Peter UedaClinical Epidemiology Division, Department of Medicine, Karolinska Institutet, Solna, Stockholm, Sweden.ORCID 0000-0002-3275-8743
Laura H GunnDepartment of Primary Care and Public Health, Imperial College London, London, UK.ORCID 0000-0003-3962-4526
Tomas JernbergDepartment of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden.
Emil HagströmDepartment of Medical Sciences, Uppsala University, Uppsala Clinical Research Center, Uppsala, Sweden.ORCID 0000-0003-3221-0144
Deepak L BhattBrigham and Women's Hospital Heart and Vascular Center, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-1278-6245
Ph Gabriel StegFrench Alliance for Cardiovascular Trials, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, Université de Paris, INSERM Unité, 1148 Paris, France.
Kristi LällEstonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.ORCID 0000-0002-9161-4694
Reedik MägiEstonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
Mari Nordbø GynnildDepartment of Neuromedicine and Movement Science, Faculty of Medicine and Health Science, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0001-8623-7911
Hanne EllekjærDepartment of Neuromedicine and Movement Science, Faculty of Medicine and Health Science, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.
Ingvild SaltvedtDepartment of Neuromedicine and Movement Science, Faculty of Medicine and Health Science, NTNU-Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0002-7897-9808
José TuñónDepartment of Cardiology, Fundación Jiménez Díaz, Madrid, Autónoma University, Madrid, Spain.ORCID 0000-0002-1373-0999
Ignacio MahílloDepartment of Epidemiology, Fundación Jiménez Díaz, Madrid, Spain.
Álvaro AceñaDepartment of Cardiology, Fundación Jiménez Díaz, Madrid, Autónoma University, Madrid, Spain.
Karol KaminskiDepartment of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Białystok, Poland.ORCID 0000-0002-9465-2581
Malgorzata ChlabiczDepartment of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Białystok, Poland.ORCID 0000-0002-5113-5672
Emilia SawickaDepartment of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Białystok, Poland.ORCID 0000-0002-8306-1882
Taavi TillmanCentre for Non-Communicable Disease, Institute for Global Health, University College London, London, UK.ORCID 0000-0002-8428-3719
John W McEvoyNational Institute for Prevention and Cardiovascular Health, Galway, Ireland.ORCID 0000-0001-6530-5479
Emanuele Di AngelantonioCardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID 0000-0001-8776-6719
Ian GrahamSchool of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland.ORCID 0000-0002-0979-4674
Dirk De BacquerDepartment of Public Health and Primary Care, Ghent University, Ghent, Belgium.ORCID 0000-0002-3202-7238
Kausik K RayDepartment of Primary Care and Public Health, Imperial College London, London, UK.ORCID 0000-0003-0508-0954
Jannick A N DorresteijnDepartment of Vascular Medicine, University Medical Center Utrecht, PO Box 85500, 3508 GA Utrecht, The Netherlands.ORCID 0000-0002-0190-8526
Frank L J VisserenDepartment of Vascular Medicine, University Medical Center Utrecht, PO Box 85500, 3508 GA Utrecht, The Netherlands.ORCID 0000-0003-3951-5223
Medical University of Białystok · PLNorwegian University of Science and Technology · NOUniversity Medical Center Utrecht · NLHospital Universitario Fundación Jiménez Díaz · ESImperial College London · GBKarolinska Institutet · SEUniversity of Tartu · EEBrigham and Women's Hospital · USCentro de Investigación en Red en Enfermedades Cardiovasculares · ESGhent University · BEInserm · FROllscoil na Gaillimhe – University of Galway · IETrinity College Dublin · IEUniversity College London · GBUniversity of Cambridge · GBUniversity of North Carolina at Charlotte · USUppsala University · SE

Funding

British Heart Foundation CH/12/2/29428British Heart Foundation RG/13/13/30194British Heart Foundation RG/18/13/33946
6 · The paper itself

Abstract

aimsThe 10-year risk of recurrent atherosclerotic cardiovascular disease (ASCVD) events in patients with established ASCVD can be estimated with the Secondary Manifestations of ARTerial disease (SMART) risk score, and may help refine clinical management. To broaden generalizability across regions, we updated the existing tool (SMART2 risk score) and recalibrated it with regional incidence rates and assessed its performance in external populations. METHODS AND

resultsIndividuals with coronary artery disease, cerebrovascular disease, peripheral artery disease, or abdominal aortic aneurysms were included from the Utrecht Cardiovascular Cohort-SMART cohort [n = 8355; 1706 ASCVD events during a median follow-up of 8.2 years (interquartile range 4.2-12.5)] to derive a 10-year risk prediction model for recurrent ASCVD events (non-fatal myocardial infarction, non-fatal stroke, or cardiovascular mortality) using a Fine and Gray competing risk-adjusted model. The model was recalibrated to four regions across Europe, and to Asia (excluding Japan), Japan, Australia, North America, and Latin America using contemporary cohort data from each target region. External validation used data from seven cohorts [Clinical Practice Research Datalink, SWEDEHEART, the international REduction of Atherothrombosis for Continued Health (REACH) Registry, Estonian Biobank, Spanish Biomarkers in Acute Coronary Syndrome and Biomarkers in Acute Myocardial Infarction (BACS/BAMI), the Norwegian COgnitive Impairment After STroke, and Bialystok PLUS/Polaspire] and included 369 044 individuals with established ASCVD of whom 62 807 experienced an ASCVD event. C-statistics ranged from 0.605 [95% confidence interval (CI) 0.547-0.664] in BACS/BAMI to 0.772 (95% CI 0.659-0.886) in REACH Europe high-risk region. The clinical utility of the model was demonstrated across a range of clinically relevant treatment thresholds for intensified treatment options.

conclusionThe SMART2 risk score provides an updated, validated tool for the prediction of recurrent ASCVD events in patients with established ASCVD across European and non-European populations. The use of this tool could allow for a more personalized approach to secondary prevention based upon quantitative rather than qualitative estimates of residual risk.

Indexed as

AtherosclerosisCardiovascular DiseasesMyocardial InfarctionStrokeAlgorithmsBiomarkersHumansRisk AssessmentRisk FactorsBiomarkersEstablished ASCVDPersonalized treatmentRecurrent riskResidual riskRisk predictionSecondary prevention

Identifiers

PMID35165703
PMCPMC9312860
OpenAlexW4210443892

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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.