Evidence map›Paper›PMID 31199839›Full record

ArticlePloS one2019

Defining genotype-phenotype relationships in patients with hypertrophic cardiomyopathy using cardiovascular magnetic resonance imaging.

Robert J H Miller, Shahriar Heidary, Aleksandra Pavlovic, Audrey Schlachter, Rajesh Dash, Dominik Fleischmann, Euan A Ashley, Matthew T Wheeler, Phillip C Yang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 18% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Human Genetics of Cardiomyopathies.Advances in experimental medicine and biology · 2024
    Article
  6. An Update on MYBPC3 Gene Mutation in Hypertrophic Cardiomyopathy.International journal of molecular sciences · 2023
    Review
  7. NATURAL LANGUAGE PROCESSING BASED MACHINE LEARNING MODEL USING CARDIAC MRI REPORTS TO IDENTIFY HYPERTROPHIC CARDIOMYOPATHY PATIENTS.Proceedings of the ... Design of Medical Devices Conference. Design of Medical Devices Conference · 2021
    Article
  8. Review
  9. Article
  10. Article
  11. 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

9 authors at 1 institution in 1 country.

Robert J H MillerDivision of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America.ORCID 0000-0003-4676-2433
Shahriar HeidaryDivision of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America.
Aleksandra PavlovicCenter for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America.
Audrey SchlachterCenter for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America.
Rajesh DashDivision of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America.
Dominik FleischmannDepartment of Radiology, Stanford University School of Medicine, Stanford, California, United States of America.
Euan A AshleyDivision of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America.
Matthew T WheelerDivision of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America.
Phillip C YangDivision of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America.
Stanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeHCM is the most common inherited cardiomyopathy. Historically, there has been poor correlation between genotype and phenotype. However, CMR has the potential to more accurately assess disease phenotype. We characterized phenotype with CMR in a cohort of patients with confirmed HCM and high prevalence of genetic testing.

methodsPatients with a diagnosis of HCM, who had undergone contrast-enhanced CMR were identified. Left ventricular mass index (LVMI) and volumes were measured from steady-state free precession sequences. Late gadolinium enhancement (LGE) was quantified using the full width, half maximum method. All patients were prospectively followed for the development of septal reduction therapy, arrhythmia or death.

resultsWe included 273 patients, mean age 51.2 ± 15.5, 62.9% male. Of those patients 202 (74.0%) underwent genetic testing with 90 pathogenic, likely pathogenic, or rare variants and 13 variants of uncertain significance identified. Median follow-up was 1138 days. Mean LVMI was 82.7 ± 30.6 and 145 patients had late gadolinium enhancement (LGE). Patients with beta-myosin heavy chain (MYH7) mutations had higher LV ejection fraction (68.8 vs 59.1, p<0.001) than those with cardiac myosin binding protein C (MYBPC3) mutations. Patients with MYBPC3 mutations were more likely to have LVEF < 55% (29.7% vs 4.9%, p = 0.005) or receive a defibrillator than those with MYH7 mutations (54.1% vs 26.8%, p = 0.020).

conclusionsWe found that patients with MYBPC3 mutations were more likely to have impaired ventricular function and may be more prone to arrhythmic events. Larger studies using CMR phenotyping may be capable of identifying additional characteristics associated with less frequent genetic causes of HCM.

Indexed as

Cardiomyopathy, HypertrophicCarrier ProteinsContrast MediaFemaleGadolinium DTPAGenetic Association StudiesGenetic TestingGenotypeHumansMagnetic Resonance ImagingMaleMiddle AgedMutationMyocardiumMyosin Binding Protein CMyosin Heavy ChainsCarrier ProteinsContrast MediaGadolinium DTPAMyosin Binding Protein CMyosin Heavy Chains

Identifiers

PMID31199839
PMCPMC6568393
OpenAlexW2949496912

What OpenQuestion 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 OpenQuestion graph.