Evidence map›Paper›PMID 38757491›Full record

ArticleJournal of the American Heart Association2024

Relationship Between Genotype Status and Clinical Outcome in Hypertrophic Cardiomyopathy.

Jiri Bonaventura, Ethan J Rowin, Raymond H Chan, Michael T Chin, Veronika Puchnerova, Eva Polakova, Milan Macek, Pavel Votypka, Rebecca Batorsky, Gayani Perera and 4 more

Abstract readMulticenter Study
In one paragraph

Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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  14. Hypertrophic cardiomyopathy: insights into pathophysiology and novel therapeutic strategies from clinical studies.The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology · 2025
    Review
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

14 authors.

Jiri BonaventuraDepartment of Cardiology, 2nd Faculty of Medicine Charles University and Motol University Hospital Prague Czech Republic.ORCID 0000-0003-0470-9909
Ethan J RowinHypertrophic Cardiomyopathy Center Lahey Hospital and Medical Center Burlington MA USA.ORCID 0000-0002-3953-0143
Raymond H ChanDivision of Cardiology, Peter Munk Cardiac Centre Toronto General Hospital, University Health Network Ontario Canada.ORCID 0000-0002-9907-678X
Michael T ChinMolecular Cardiology Research Institute Tufts Medical Center Boston MA USA.ORCID 0000-0003-3065-8498
Veronika PuchnerovaDepartment of Cardiology, 2nd Faculty of Medicine Charles University and Motol University Hospital Prague Czech Republic.ORCID 0000-0001-9118-7218
Eva PolakovaDepartment of Cardiology, 2nd Faculty of Medicine Charles University and Motol University Hospital Prague Czech Republic.ORCID 0000-0002-9158-3883
Milan MacekDepartment of Biology and Medical Genetics, 2nd Faculty of Medicine Charles University and Motol University Hospital Prague Czech Republic.ORCID 0000-0002-5173-5280
Pavel VotypkaDepartment of Biology and Medical Genetics, 2nd Faculty of Medicine Charles University and Motol University Hospital Prague Czech Republic.ORCID 0000-0002-3540-000X
Rebecca BatorskyMolecular Cardiology Research Institute Tufts Medical Center Boston MA USA.ORCID 0000-0003-4712-6500
Gayani PereraMolecular Cardiology Research Institute Tufts Medical Center Boston MA USA.ORCID 0009-0002-2898-9239
Benjamin KoetheInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center Boston MA USA.ORCID 0000-0001-8019-181X
Josef VeselkaDepartment of Cardiology, 2nd Faculty of Medicine Charles University and Motol University Hospital Prague Czech Republic.
Barry J MaronHypertrophic Cardiomyopathy Center Lahey Hospital and Medical Center Burlington MA USA.ORCID 0000-0002-1710-8670
Martin S MaronHypertrophic Cardiomyopathy Center Lahey Hospital and Medical Center Burlington MA USA.ORCID 0000-0002-9923-3853

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe genetic basis of hypertrophic cardiomyopathy (HCM) is complex, and the relationship between genotype status and clinical outcome is incompletely resolved. METHODS AND

resultsWe assessed a large international HCM cohort to define in contemporary terms natural history and clinical consequences of genotype. Consecutive patients (n=1468) with established HCM diagnosis underwent genetic testing. Patients with pathogenic (or likely pathogenic) variants were considered genotype positive (G+; n=312; 21%); those without definite disease-causing mutations (n=651; 44%) or variants of uncertain significance (n=505; 35%) were considered genotype negative (G-). Patients were followed up for a median of 7.8 years (interquartile range, 3.5-13.4 years); HCM end points were examined by cumulative event incidence. Over follow-up, 135 (9%) patients died, 33 from a variety of HCM-related causes. After adjusting for age, all-cause and HCM-related mortality did not differ between G- versus G+ patients (hazard ratio [HR], 0.78 [95% CI, 0.46-1.31];

conclusionsIn this large consecutive cohort of patients with HCM, genotype (G+ or G-) was not a predictor of clinical course, including all-cause and HCM-related mortality and risk for heart failure progression or sudden death. G+ status should not be used to dictate clinical management or predict outcome in HCM.

Indexed as

Cardiomyopathy, HypertrophicGenotypeAdultAgedDeath, Sudden, CardiacDisease ProgressionFemaleGenetic Predisposition to DiseaseGenetic TestingHeart FailureHeart TransplantationHumansMaleMiddle AgedMutationPhenotypegenotypehypertrophic cardiomyopathymortalityoutcomessudden death

Identifiers

PMID38757491
PMCPMC11179794

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.