Evidence map›Paper›PMID 37527539›Full record

ArticleEuropean journal of preventive cardiology2024

Echocardiographic heart ageing patterns predict cardiovascular and non-cardiovascular events and reflect biological age: the SardiNIA study.

Antonello Ganau, Marco Orrù, Matteo Floris, Pier Sergio Saba, Federica Loi, Giuseppe D Sanna, Michele Marongiu, Lenuta Balaci, Niccolò Curreli, Liana A P Ferreli and 8 more

Open access · greenAbstract read
In one paragraph

Article in European journal of preventive cardiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
4.0field-weighted citation impact, top 5% 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

10 citing papers in PubMed, 18 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors at 6 institutions in 2 countries.

Antonello GanauDepartment of Medicine, Surgery, and Pharmacy, University of Sassari, Via Istria12, 07100 Sassari, Italy, Italy.ORCID 0000-0002-7053-293X
Marco OrrùArmando Businco Hospital, Azienda Ospedaliera Brotzu, Cagliari 09047, Italy.
Matteo FlorisDepartment of Biomedical Sciences, University of Sassari, Sassari 07100, Italy.
Pier Sergio SabaCardiac Thoracic Vascular Department, Azienda Ospedaliero Universitaria, Sassari 07100, Italy.
Federica LoiDepartment of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, Padova 35128, Italy.
Giuseppe D SannaCardiac Thoracic Vascular Department, Azienda Ospedaliero Universitaria, Sassari 07100, Italy.
Michele MarongiuInstitute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy.ORCID 0000-0002-7289-9815
Lenuta BalaciInstitute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy.
Niccolò CurreliInstitute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy.
Liana A P FerreliInstitute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy.
Francesco LoiInstitute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy.
Marco MasalaInstitute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy.
Guido ParodiDepartment of Medicine, Surgery, and Pharmacy, University of Sassari, Via Istria12, 07100 Sassari, Italy, Italy.
Alessandro P DelitalaDepartment of Medicine, Surgery, and Pharmacy, University of Sassari, Via Istria12, 07100 Sassari, Italy, Italy.
David SchlessingerLaboratory of Genetics & Genomics, NIH/National Institute of Ageing, Bethesda, MD, USA.
Edward LakattaLaboratory of Cardiovascular Science, NIH/National Institute of Ageing, Bethesda, MD, USA.
Edoardo FiorilloInstitute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy.
Francesco CuccaDepartment of Biomedical Sciences, University of Sassari, Sassari 07100, Italy.
Institute of Genetic and Biomedical Research · ITUniversity of Sassari · ITAzienda Ospedaliero Universitaria di Sassari · ITUniversity of Padua · ITAzienda Ospedaliera G. Brotzu · ITNational Institute on Aging · US

Funding

Age Associated Changes In Structural And Functional Cardio-Vascular PropertiesZIAAG000856 · NIA · NATIONAL INSTITUTE ON AGING · PI LAKATTA, EDWARD · 2009 to 2025
$3.4M
NIA NIH HHSNIDA NIH HHS HHSN271201100005CNIH HHS N01-AG-1-2109
6 · The paper itself

Abstract

aimsAge is a crucial risk factor for cardiovascular (CV) and non-CV diseases. As people age at different rates, the concept of biological age has been introduced as a personalized measure of functional deterioration. Associations of age with echocardiographic quantitative traits were analysed to assess different heart ageing rates and their ability to predict outcomes and reflect biological age. METHODS AND

resultsAssociations of age with left ventricular mass, geometry, diastolic function, left atrial volume, and aortic root size were measured in 2614 healthy subjects. Based on the 95% two-sided tolerance intervals of each correlation, three discrete ageing trajectories were identified and categorized as 'slow', 'normal', and 'accelerated' heart ageing patterns. The primary endpoint included fatal and non-fatal CV events, and the secondary endpoint was a composite of CV and non-CV events and all-cause death. The phenotypic age of the heart (HeartPhAge) was estimated as a proxy of biological age. The slow ageing pattern was found in 8.7% of healthy participants, the normal pattern in 76.9%, and the accelerated pattern in 14.4%. Kaplan-Meier curves of the heart ageing patterns diverged significantly (P = 0.0001) for both primary and secondary endpoints, with the event rate being lowest in the slow, intermediate in the normal, and highest in the accelerated pattern. In the Cox proportional hazards model, heart ageing patterns predicted both primary (P = 0.01) and secondary (P = 0.03 to <0.0001) endpoints, independent of chronological age and risk factors. Compared with chronological age, HeartPhAge was 9 years younger in slow, 4 years older in accelerated (both P < 0.0001), and overlapping in normal ageing patterns.

conclusionStandard Doppler echocardiography detects slow, normal, and accelerated heart ageing patterns. They predict CV and non-CV events, reflect biological age, and provide a new tool to calibrate prevention timing and intensity.

Indexed as

EchocardiographyVentricular Function, LeftAgingChildEchocardiography, DopplerHumansRisk FactorsAge-dependent diseasesAgeing heartBiological ageCardiovascular diseaseCardiovascular preventionEchocardiography

Identifiers

PMID37527539
PMCPMC11025036
OpenAlexW4385443353

What OpenQuestion holds

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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.