Evidence map›Paper›PMID 17650341›Full record

ArticleBMC public health2007

How many people have had a myocardial infarction? Prevalence estimated using historical hospital data.

Douglas G Manuel, Jenny J Y Lim, Peter Tanuseputro, Therésè A Stukel

Abstract readComparative StudyHistorical Article
In one paragraph

Article in BMC public health, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  11. Health behavior change following chronic illness in middle and later life.The journals of gerontology. Series B, Psychological sciences and social sciences · 2012
    Article
  12. Article
  13. Health care utilization in patients with gout.Seminars in arthritis and rheumatism · 2011
    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

4 authors.

Douglas G ManuelInstitute for Clinical Evaluative Sciences, G106-2075 Bayview Avenue, Toronto, Ontario, M4N 3M5, Canada. doug.manuel@ices.on.ca
Jenny J Y Lim
Peter Tanuseputro
Therésè A Stukel

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth administrative data are increasingly used to examine disease occurrence. However, health administrative data are typically available for a limited number of years - posing challenges for estimating disease prevalence and incidence. The objective of this study is to estimate the prevalence of people previously hospitalized with an acute myocardial infarction (AMI) using 17 years of hospital data and to create a registry of people with myocardial infarction.

methodsMyocardial infarction prevalence in Ontario 2004 was estimated using four methods: 1) observed hospital admissions from 1988 to 2004; 2) observed (1988 to 2004) and extrapolated unobserved events (prior to 1988) using a "back tracing" method using Poisson models; 3) DisMod incidence-prevalence-mortality model; 4) self-reported heart disease from the population-based Canadian Community Health Survey (CCHS) in 2000/2001. Individual respondents of the CCHS were individually linked to hospital discharge records to examine the agreement between self-report and hospital AMI admission.

results170,061 Ontario residents who were alive on March 31, 2004, and over age 20 years survived an AMI hospital admission between 1988 to 2004 (cumulative incidence 1.8%). This estimate increased to 2.03% (95% CI 2.01 to 2.05) after adding extrapolated cases that likely occurred before 1988. The estimated prevalence appeared stable with 5 to 10 years of historic hospital data. All 17 years of data were needed to create a reasonably complete registry (90% of estimated prevalent cases). The estimated prevalence using both DisMod and self-reported "heart attack" was higher (2.5% and 2.7% respectively). There was poor agreement between self-reported "heart attack" and the likelihood of having an observed AMI admission (sensitivity = 63.5%, positive predictive value = 54.3%).

conclusionEstimating myocardial infarction prevalence using a limited number of years of hospital data is feasible, and validity increases when unobserved events are added to observed events. The "back tracing" method is simple, reliable, and produces a myocardial infarction registry with high estimated "completeness" for jurisdictions with linked hospital data.

Indexed as

AdultAgedAged, 80 and overFemaleHistory, 20th CenturyHistory, 21st CenturyHospitalizationHumansLongitudinal StudiesMaleMiddle AgedMyocardial InfarctionOntarioPopulation SurveillancePrevalenceRegistries

Identifiers

PMID17650341
PMCPMC1994682

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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.