Evidence map›Paper›PMID 35231928›Full record

ArticleAmerican journal of epidemiology2022

From Atherosclerosis to Myocardial Infarction: A Process-Oriented Model Investigating the Role of Risk Factors.

Cristoforo Simonetto, Margit Heier, Annette Peters, Jan Christian Kaiser, Susanne Rospleszcz

Open access · hybridAbstract read
In one paragraph

Article in American journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
4.1field-weighted citation impact, top 6% 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

4 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Reduced circulating CD63Cardiovascular diabetology · 2024
    Article
  3. Review
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Cristoforo Simonetto
Margit Heier
Annette Peters
Jan Christian Kaiser
Susanne Rospleszcz
Helmholtz Zentrum München · DEGerman Centre for Cardiovascular Research · DEUniversity Hospital Augsburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mathematical models are able to reflect biological processes and to capture epidemiologic data. Thus, they may help elucidate roles of risk factors in disease progression. We propose to account for smoking, hypertension, and dyslipidemia in a previously published process-oriented model that describes the development of atherosclerotic lesions resulting in myocardial infarction (MI). The model is sex-specific and incorporates individual heterogeneity. It was applied to population-based individual risk factors and MI rates (Cooperative Health Research in the Region of Augsburg (KORA) study) together with subclinical atherosclerotic lesion data (Pathobiological Determinants of Atherosclerosis in Youth (PDAY) study). Different model variants were evaluated, testing the association of risk factors with different disease processes. Best fits were obtained for smoking affecting a late-stage disease process, suggesting a thrombogenic role. Hypertension was mainly related to complicated, vulnerable lesions. Dyslipidemia was consistent with increasing the number of initial lesions. By accounting for heterogeneity, individual hazard ratios differ from the population average. The mean individual hazard ratio for smoking was twice the population-based hazard ratio for men and even more for women. Atherosclerotic lesion progression and MI incidence data can be related in a mathematical model to illuminate how risk factors affect different phases of this pathological process.

Indexed as

AtherosclerosisDyslipidemiasHypertensionMyocardial InfarctionAdolescentFemaleHumansMaleRisk Factorsatherosclerosisbiological modelscardiovascular risk factorscomputer simulationmyocardial infarctionsurvival analysis

Identifiers

PMID35231928
PMCPMC9535448
OpenAlexW4214547176

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.