Evidence map›Paper›PMID 40078653›Full record

ArticleEuropean heart journal open2025

15-Year trends, predictors, and outcomes of heart failure hospitalization complicating first acute myocardial infarction in the modern percutaneous coronary intervention era.

Muhammad Rashid, Dmitry Abramov, Muhammad Usman Naseer, Harriette G C Van Spall, Fozia Z Ahmed, Claire Lawson, Mohamed Dafaalla, Evangelos Kontopantelis, Mohamed O Mohamed, Mark C Petrie and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European heart journal open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 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.

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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. 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

11 authors.

Muhammad RashidDepartment of Cardiovascular Sciences, University of Leicester and the National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, LE1 7RH Leicester, UK.ORCID https://orcid.org/0000-0001-9725-1583
Dmitry AbramovDivision of Cardiology, Loma Linda University Medical Center, Loma Linda, CA 92354, USA.
Muhammad Usman NaseerDepartment of Cardiology, Glenfield Hospital, University Hospitals of Leicester, LE3 9QP Leicester, UK.
Harriette G C Van SpallDepartment of Medicine, McMaster University, Hamilton, ON, Canada L8S 4L8.
Fozia Z AhmedDepartment of Cardiology, Manchester University Hospitals NHS Foundation Trust, M13 9WL Manchester, UK.
Claire LawsonDepartment of Cardiovascular Sciences, University of Leicester and the National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, LE1 7RH Leicester, UK.ORCID https://orcid.org/0000-0003-0127-5236
Mohamed DafaallaKeele Cardiovascular Research Group, School of Medicine, Keele University, ST5 5BG, UK.ORCID https://orcid.org/0000-0003-4625-2775
Evangelos KontopantelisDivision of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, M13 9NT Manchester, UK.
Mohamed O MohamedInstitute of Health Informatics, University College, NW1 2DA London, UK.
Mark C PetrieBHF Cardiovascular Research Centre, University of Glasgow, G12 8TA Glasgow, UK.ORCID https://orcid.org/0000-0002-6333-9496
Mamas A MamasKeele Cardiovascular Research Group, School of Medicine, Keele University, ST5 5BG, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Heart failure (HF) following acute myocardial infarction (AMI) is a global health concern, but data on risk factors associated with HF hospitalization post-AMI are limited. Methods and results: We analysed data from the Myocardial Ischaemia National Audit Project, including patients admitted with AMI from 1 January 2006 to 31 March 2019. Data linkage with Hospital Episode Statistics Admitted Patient Care and the Office for National Statistics facilitated a longitudinal analysis. High-risk patients were identified using dapagliflozin in patients without diabetes mellitus with acute myocardial infarction (DAPA-MI) and EMPAgliflozin on Hospitalization for Heart Failure and Mortality in Patients With aCuTe Myocardial Infarction (EMPACT-MI) criteria. We assessed clinical outcomes, adherence to European Society of Cardiology quality indicators, and predictors of HF-related hospitalizations. Out of 1 046 480 AMI patients, 9.1% overall, 17.2% in the DAPA-MI cohort, and 16.6% in the EMPACT-MI cohort experienced HF hospitalization within a year post-AMI. High-risk patients, defined by the presence of five risk factors, had nearly one in four hospitalizations with HF at 1-year follow-up. The predicted adjusted incidence rate for heart failure within 1 year almost doubled from 64.5 cases per 1000 person-years [95% confidence interval (CI): 51.1 to 78.0] in 2005, to 118.2 cases per 1000 person-years in 2019 (95% CI: 115.0 to 121.5). Heart failure hospitalization was associated with a three-fold increase in 1-year mortality (hazard ratio 3.01, 95% CI 2.95-3.13). Conclusion: One in 10 AMI patients experienced HF hospitalization within the first-year post-AMI, with rising trends in high-risk subgroups. These findings highlight the need for targeted post-AMI care strategies to improve outcomes and address the increasing burden of HF in the modern percutaneous coronary intervention era.

Indexed as

Acute myocardial infarctionHeart failureMortalityRisk factorsTrends

Identifiers

PMID40078653
PMCPMC11896973

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.