Evidence map›Paper›PMID 28329300›Full record

ArticleEuropean heart journal2017

Personalising the decision for prolonged dual antiplatelet therapy: development, validation and potential impact of prognostic models for cardiovascular events and bleeding in myocardial infarction survivors.

Laura Pasea, Sheng-Chia Chung, Mar Pujades-Rodriguez, Alireza Moayyeri, Spiros Denaxas, Keith A A Fox, Lars Wallentin, Stuart J Pocock, Adam Timmis, Amitava Banerjee and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in European heart journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.5field-weighted citation impact, top 3% 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

21 citing papers in PubMed, 44 citations in OpenAlex.

  1. Prognostic Impact ofJournal of the American Heart Association · 2024
    Article
  2. Article
  3. Review
  4. Review
  5. Review
  6. Drug-Drug-Gene Interactions in Cardiovascular Medicine.Pharmacogenomics and personalized medicine · 2022
    Review
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 6 institutions in 2 countries.

Laura PaseaThe Farr Institute of Health Informatics Research, University College London, London, UK.
Sheng-Chia ChungThe Farr Institute of Health Informatics Research, University College London, London, UK.
Mar Pujades-RodriguezThe Farr Institute of Health Informatics Research, University College London, London, UK.
Alireza MoayyeriThe Farr Institute of Health Informatics Research, University College London, London, UK.
Spiros DenaxasThe Farr Institute of Health Informatics Research, University College London, London, UK.
Keith A A FoxCentre for Cardiovascular Science, University of Edinburgh and Royal Infirmary of Edinburgh, Edinburgh, UK.
Lars WallentinDepartment of Medical Sciences Cardiology, Uppsala Clinical Research Centre, Uppsala University, Uppsala, Sweden.
Stuart J PocockDepartment of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK.
Adam TimmisBart's Heart Centre, Barts and the London National Institute for Health Research Cardiovascular Biomedical Research Unit, London, UK.
Amitava BanerjeeThe Farr Institute of Health Informatics Research, University College London, London, UK.
Riyaz PatelThe Farr Institute of Health Informatics Research, University College London, London, UK.
Harry HemingwayThe Farr Institute of Health Informatics Research, University College London, London, UK.
Farr Institute · GBUniversity College London · GBEdinburgh Royal Infirmary · GBLondon School of Hygiene & Tropical Medicine · GBNational Institute for Health Research · GBUppsala University · SE

Funding

British Heart Foundation FS/14/76/30933Department of Health 05/40/04Department of Health RP-PG-0407-10314Medical Research Council G0902393Medical Research Council MC_PC_13041Medical Research Council MR/K006584/1Medical Research Council MR/M015084/1Wellcome Trust
6 · The paper itself

Abstract

Aims: The aim of this study is to develop models to aid the decision to prolong dual antiplatelet therapy (DAPT) that requires balancing an individual patient's potential benefits and harms. Methods and results: Using population-based electronic health records (EHRs) (CALIBER, England, 2000-10), of patients evaluated 1 year after acute myocardial infarction (MI), we developed (n = 12 694 patients) and validated (n = 5613) prognostic models for cardiovascular (cardiovascular death, MI or stroke) events and three different bleeding endpoints. We applied trial effect estimates to determine potential benefits and harms of DAPT and the net clinical benefit of individuals. Prognostic models for cardiovascular events (c-index: 0.75 (95% CI: 0.74, 0.77)) and bleeding (c index 0.72 (95% CI: 0.67, 0.77)) were well calibrated: 3-year risk of cardiovascular events was 16.5% overall (5.2% in the lowest- and 46.7% in the highest-risk individuals), while for major bleeding, it was 1.7% (0.3% in the lowest- and 5.4% in the highest-risk patients). For every 10 000 patients treated per year, we estimated 249 (95% CI: 228, 269) cardiovascular events prevented and 134 (95% CI: 87, 181) major bleeding events caused in the highest-risk patients, and 28 (95% CI: 19, 37) cardiovascular events prevented and 9 (95% CI: 0, 20) major bleeding events caused in the lowest-risk patients. There was a net clinical benefit of prolonged DAPT in 63-99% patients depending on how benefits and harms were weighted. Conclusion: Prognostic models for cardiovascular events and bleeding using population-based EHRs may help to personalise decisions for prolonged DAPT 1-year following acute MI.

Indexed as

AgedClinical Decision-MakingDeath, Sudden, CardiacDrug Therapy, CombinationFemaleHemorrhageHumansMaleModels, BiologicalMyocardial InfarctionPlatelet Aggregation InhibitorsPrecision MedicineStrokeSurvivorsTreatment OutcomePlatelet Aggregation InhibitorsBleedingMyocardial infarctionPrognosis

Identifiers

PMID28329300
PMCPMC5400049
OpenAlexW2593728002

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.