Evidence map›Paper›PMID 39658197›Full record

ArticleHeart (British Cardiac Society)2025

Age-stratified comparison of heart age and predicted cardiovascular risk in 370 000 primary care patients.

Kathrine Stjernholm, Andrew Kerr, Katrina K Poppe, Anders Elkær Jensen, Suneela Mehta, Jesper Bo Nielsen, Rod Jackson, Susan Wells

Abstract readComparative StudyMulticenter Study
In one paragraph

Article in Heart (British Cardiac Society), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Observational
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

8 authors.

Kathrine StjernholmResearch Unit of General Practice, Department of Public Health, University of Southern Denmark, Odense, Denmark ksnielsen@health.sdu.dk.ORCID 0000-0003-1198-2022
Andrew KerrSection of Epidemiology and Biostatistics, School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID 0000-0001-8310-6289
Katrina K PoppeDepartment of Medicine, School of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID 0000-0002-4418-4476
Anders Elkær JensenResearch Unit of General Practice, Department of Public Health, University of Southern Denmark, Odense, Denmark.ORCID 0000-0002-9056-9326
Suneela MehtaSection of Epidemiology and Biostatistics, School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID 0000-0003-4386-3300
Jesper Bo NielsenResearch Unit of General Practice, Department of Public Health, University of Southern Denmark, Odense, Denmark.ORCID 0000-0002-5764-5462
Rod JacksonSection of Epidemiology and Biostatistics, School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID 0000-0001-5914-6934
Susan WellsDepartment of General Practice and Primary Health Care, School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID 0000-0003-2942-9524

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCardiovascular disease (CVD) preventive medications are recommended for patients at high short-term CVD risk. As most younger people with multiple raised CVD risk factors levels have low short-term risk, they could be falsely reassured to take no action. Heart age-the chronological age of a hypothetical person with the same short-term absolute CVD risk as the patient being assessed, but with an 'ideal' risk profile-is a complementary relative CVD risk metric developed to encourage these younger patients to make long-term lifestyle changes. However, clinicians sometimes use heart age to inform medication decisions. We assessed the appropriateness of this practice by comparing heart age and short-term CVD risk.

methodsNew Zealand primary care patients are recruited to the PREDICT cohort when their CVD risk is assessed. PREDICT is an ongoing prospective study in one-third of New Zealand general practices, designed to derive CVD risk prediction algorithms. Five-year CVD risk was calculated for 35-74-year-old PREDICT participants using published equations. Heart age was calculated using non-smoking, systolic blood pressure of 120 mm Hg and total cholesterol/high-density lipoprotein ratio of 3.5, as the 'ideal' risk profile. CVD risk and heart age gaps (difference between chronological age and heart age) were compared.

resultsAmong 371 676 PREDICT participants, 5-year CVD risk increased with age, approximately doubling every 10 years, whereas heart age gaps decreased with increasing age, approximately halving between 35 and 44-year olds and 65-74-year olds. There were 5-40-year heart age gap differences between groups with similar 5-year CVD risks, but different ages.

conclusionShort-term CVD risk and heart age are not interchangeable risk metrics. Short-term risk increases with increasing age whereas heart age gaps generally decline, with major differences between younger and older people with similar short-term risk. If heart age is used to inform medication decisions rather than encourage long-term lifestyle changes, older people at high short-term risk could be undertreated and younger people at low short-term risk could be unnecessarily medicated.

Indexed as

Cardiovascular DiseasesPrimary Health CareAdultAgedAge FactorsFemaleHeart Disease Risk FactorsHumansMaleMiddle AgedNew ZealandProspective StudiesRisk AssessmentRisk FactorsCoronary Artery DiseaseEpidemiologyHyperlipidemiasHypertensionRisk Factors

Identifiers

PMID39658197
PMCPMC11874366

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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.