Evidence map›Paper›PMID 35850144›Full record

ArticleThe Lancet. Public health2022

Contributions of event rates, pre-hospital deaths, and deaths following hospitalisation to variations in myocardial infarction mortality in 326 districts in England: a spatial analysis of linked hospitalisation and mortality data.

Perviz Asaria, James E Bennett, Paul Elliott, Theo Rashid, Hima Iyathooray Daby, Margaret Douglass, Darrel P Francis, Daniela Fecht, Majid Ezzati

Open access · goldAbstract read
In one paragraph

Article in The Lancet. Public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
5.3field-weighted citation impact, top 4% 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

15 citing papers in PubMed, 21 citations in OpenAlex.

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  10. Sex-based analysis of NSTEMI processes of care and outcomes by hospital: a nationwide cohort study.European heart journal. Quality of care & clinical outcomes · 2024
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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 at 3 institutions in 2 countries.

Perviz AsariaDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; Department of Cardiology, Imperial College NHS Trust, London, UK.
James E BennettDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.
Paul ElliottDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; UK Small Area Health Statistics Unit, School of Public Health, Imperial College London, London, UK.
Theo RashidDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.
Hima Iyathooray DabyDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; UK Small Area Health Statistics Unit, School of Public Health, Imperial College London, London, UK.
Margaret DouglassDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; UK Small Area Health Statistics Unit, School of Public Health, Imperial College London, London, UK.
Darrel P FrancisDepartment of Cardiology, Imperial College NHS Trust, London, UK; National Heart and Lung Institute, Imperial College London, London, UK.
Daniela FechtDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; UK Small Area Health Statistics Unit, School of Public Health, Imperial College London, London, UK.
Majid EzzatiDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; Regional Institute for Population Studies, University of Ghana, Accra, Ghana. Electronic address: majid.ezzati@imperial.ac.uk.
MRC Centre for Environment and HealthImperial College London · GBImperial College Healthcare NHS Trust · GB

Funding

British Heart Foundation RE/18/4/34215Medical Research Council MR/S019669/1Medical Research Council MR/V034057/1Wellcome Trust 092853Wellcome Trust 092853/Z/10/ZWellcome Trust 209376Wellcome Trust 209376/Z/17/Z
6 · The paper itself

Abstract

backgroundMyocardial infarction mortality varies substantially within high-income countries. There is limited guidance on what interventions-including primary and secondary prevention, or improvement of care pathways and quality-can reduce myocardial infarction mortality. Our aim was to understand the contributions of incidence (event rate), pre-hospital deaths, and hospital case fatality to the variations in myocardial infarction mortality within England.

methodsWe used linked data from national databases on hospitalisations and deaths with acute myocardial infarction (ICD-10 codes I21 and I22) as a primary hospital diagnosis or underlying cause of death, from Jan 1, 2015, to Dec 31, 2018. We used geographical identifiers to estimate myocardial infarction event rate (number of events per 100 000 population), death rate (number of deaths per 100 000 population), total case fatality (proportion of events that resulted in death), pre-hospital fatality (proportion of events that resulted in pre-hospital death), and hospital case fatality (proportion of admissions due to myocardial infarction that resulted in death within 28 days of admission) for men and women aged 45 years and older across 326 districts in England. Data were analysed in a Bayesian spatial model that accounted for similarities and differences in spatial patterns of fatal and non-fatal myocardial infarction. Age-standardised rates were calculated by weighting age-specific rates by the corresponding national share of the appropriate denominator for each measure.

findingsFrom 2015 to 2018, national age-standardised death rates were 63 per 100 000 population in women and 126 per 100 000 in men, and event rates were 233 per 100 000 in women and 512 per 100 000 in men. After age-standardisation, 15·0% of events in women and 16·9% in men resulted in death before hospitalisation, and hospital case fatality was 10·8% in women and 10·6% in men. Across districts, the 99th-to-1st percentile ratio of age-standardised myocardial infarction death rates was 2·63 (95% credible interval 2·45-2·83) in women and 2·56 (2·37-2·76) in men, with death rates highest in parts of northern England. The main contributor to this variation was myocardial infarction event rate, with a 99th-to-1st percentile ratio of 2·55 (2·39-2·72) in women and 2·17 (2·08-2·27) in men across districts. Pre-hospital fatality was greater than hospital case fatality in every district. Pre-hospital fatality had a 99th-to-1st percentile ratio of 1·60 (1·50-1·70) in women and 1·75 (1·66-1·86) in men across districts, and made a greater contribution to variation in total case fatality than did hospital case fatality (99th-to-1st percentile ratio 1·39 [1·29-1·49] and 1·49 [1·39-1·60]). The contribution of case fatality to variation in deaths across districts was largest in women aged 55-64 and 65-74 years and in men aged 55-64, 65-74, and 75-84 years. Pre-hospital fatality was slightly higher in men than in women in most districts and age groups, whereas hospital case fatality was higher in women in virtually all districts at ages up to and including 65-74 years.

interpretationMost of the variation in myocardial infarction mortality in England is due to variation in myocardial infarction event rate, with a smaller role for case fatality. Most variation in case fatality occurs before rather than after hospital admission. Reducing subnational variations in myocardial infarction mortality requires interventions that reduce event rate and pre-hospital deaths.

fundingWellcome Trust, British Heart Foundation, Medical Research Council (UK Research and Innovation), and National Institute for Health Research (UK).

Indexed as

Myocardial InfarctionBayes TheoremFemaleHospitalizationHospitalsHumansMaleSpatial Analysis

Identifiers

PMID35850144
PMCPMC10506182
OpenAlexW4285601032

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.