Evidence map›Paper›PMID 37583586›Full record

ReviewFrontiers in cardiovascular medicine2023

Advanced searching for hypertrophic cardiomyopathy heritability in real practice tomorrow.

Olga S Chumakova, Natalia M Baulina

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 2023. 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
2.6field-weighted citation impact, top 9% 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, 12 citations in OpenAlex.

  1. Review
  2. Review
  3. 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. 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

2 authors at 1 institution in 1 country.

Olga S ChumakovaLaboratory of Functional Genomics of Cardiovascular Diseases, National Medical Research Centre of Cardiology Named After E.I. Chazov, Moscow, Russia.
Natalia M BaulinaLaboratory of Functional Genomics of Cardiovascular Diseases, National Medical Research Centre of Cardiology Named After E.I. Chazov, Moscow, Russia.
National Medical Research Center of Cardiology · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease associated with morbidity and mortality at any age. As studies in recent decades have shown, the genetic architecture of HCM is quite complex both in the entire population and in each patient. In the rapidly advancing era of gene therapy, we have to provide a detailed molecular diagnosis to our patients to give them the chance for better and more personalized treatment. In addition to emphasizing the importance of genetic testing in routine practice, this review aims to discuss the possibility to go a step further and create an expanded genetic panel that contains not only variants in core genes but also new candidate genes, including those located in deep intron regions, as well as structural variations. It also highlights the benefits of calculating polygenic risk scores based on a combination of rare and common genetic variants for each patient and of using non-genetic HCM markers, such as microRNAs that can enhance stratification of risk for HCM in unselected populations alongside rare genetic variants and clinical factors. While this review is focusing on HCM, the discussed issues are relevant to other cardiomyopathies.

Indexed as

diagnosisgeneticsHCM-associated variantshypertrophic cardiomyopathymiRNAmissing heritabilityNGSpolygenic risk score

Identifiers

PMID37583586
PMCPMC10425241
OpenAlexW4385410727

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.