Evidence map›Paper›PMID 41299444›Full record

ArticleBMC medicine2025

Long-term accrual of conditions following myocardial infarction: a study of disease trajectories in the Wales Multimorbidity e-Cohort.

Jonathan A Batty, Christopher J Hayward, Ronan A Lyons, Chris P Gale, Niels Peek, Marlous Hall

Abstract read
In one paragraph

Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Jonathan A BattyLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Worsley Building, Level 11, Clarendon Way, Leeds, UK. Jonny.Batty@hyms.ac.uk.
Christopher J HaywardLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Worsley Building, Level 11, Clarendon Way, Leeds, UK.
Ronan A LyonsPopulation Data Science, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea University, Swansea, UK.
Chris P GaleLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Worsley Building, Level 11, Clarendon Way, Leeds, UK.
Niels PeekThe Healthcare Improvement Studies Institute, University of Cambridge, Cambridge, UK.
Marlous HallLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Worsley Building, Level 11, Clarendon Way, Leeds, UK. m.s.hall@leeds.ac.uk.

Funding

Alan Turing Institute TU/ASG/R-SPEH-114British Heart Foundation BHF-Turing-19/02/1022Wellcome TrustWellcome Trust 206470/Z/17/ZWellcome Trust 227498/Z/23/Z; R127002
6 · The paper itself

Abstract

backgroundImproved survivorship following myocardial infarction (MI) has resulted in transferred morbidity to other long-term conditions (LTCs). Understanding of disease accrual over time following MI has been limited by a lack of methodologies that consider real-world complexity. We characterised post-MI multimorbidity trajectories in a real-world population of individuals following MI.

methodsThis population-wide retrospective study comprised all individuals with MI in the Wales Multimorbidity e-Cohort (which included linked primary and secondary care data for 2,902,101 GP-registered residents of Wales; 2005-2019). Single-year post-MI disease clusters and multi-year latent multimorbidity trajectories were constructed from 227 chronic conditions and 62 acute conditions, using non-negative matrix factorisation (NMF). Multinomial logistic regression identified sociodemographic factors associated with single-year post-MI disease clusters. Time-updating flexible parametric survival models quantified the association between multi-year multimorbidity trajectories and long-term all-cause mortality, adjusting for age, sex, year of MI, socioeconomic deprivation and rurality.

resultsIn total, 70,529 individuals had an incident MI during the study period (median [interquartile range] age 72 [62-82] years; 40.6% female), with restricted mean post-MI survival of 8.1 years. At MI diagnosis, 67,023 (95.0%) had ≥ 2 LTCs (median 8 [interquartile range; IQR 5-12]), which increased to 99.8% at 1 year (50,633/50,737 surviving patients, median [IQR] 12 [7-17]). NMF classified individuals into one of 10 post-MI disease clusters, based on all observed acute and chronic diagnoses (n = 3,954,622) accrued over time. Individuals that followed the most adverse latent multimorbidity trajectory (n = 26,035, 36.9%) were characterised by recurrent MI, acute infections and renal disease and had an increased risk of all-cause mortality (adjusted hazard ratio 6.62; 95% CI: 6.09-7.20) compared with individuals in the least adverse trajectory.

conclusionsPatients with MI have a high pre-existing multimorbidity burden that increases post-MI. Using NMF, we were able to reduce the real-world complexity of all individual diseases accrued over time into 10 latent post-MI multimorbidity trajectories. These trajectories were characterised by specific patterns of acute and chronic conditions, with differential impact on outcomes. These trajectories may enable the implementation of targeted strategies for individuals that are at greatest risk of adverse outcomes.

Indexed as

MultimorbidityMyocardial InfarctionAgedAged, 80 and overChronic DiseaseCohort StudiesFemaleHumansMaleMiddle AgedRetrospective StudiesWalesClusteringDisease trajectoriesMultimorbidityMyocardial infarctionNon-negative matrix factorisation

Identifiers

PMID41299444
PMCPMC12751190

What Socratic 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 Socratic graph.