Evidence map›Paper›PMID 26472190›Full record

ReviewCurrent heart failure reports2015

Evolving Approaches to Genetic Evaluation of Specific Cardiomyopathies.

Loon Yee Louis Teo, Rocio T Moran, W H Wilson Tang

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current heart failure reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

5 citing papers in PubMed, 15 citations in OpenAlex.

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  4. Review
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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

3 authors at 2 institutions in 1 country.

Loon Yee Louis TeoKaufman Center for Heart Failure, Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH, USA.
Rocio T MoranDivision of Genetics and Genomics, MetroHealth Medical Center, Cleveland, OH, 44109, USA.
W H Wilson TangKaufman Center for Heart Failure, Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH, USA. tangw@ccf.org.
Cleveland Clinic · USMetroHealth Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The understanding of the genetic basis of cardiomyopathy has expanded significantly over the past 2 decades. The increasing availability, shortening diagnostic time, and lowering costs of genetic testing have provided researchers and physicians with the opportunity to identify the underlying genetic determinants for thousands of genetic disorders, including inherited cardiomyopathies, in effort to improve patient morbidities and mortality. As such, genetic testing has advanced from basic scientific research to clinical application and has been incorporated as part of patient evaluations for suspected inherited cardiomyopathies. Genetic evaluation framework of inherited cardiomyopathies typically encompasses careful evaluation of family history, genetic counseling, clinical screening of family members, and if appropriate, molecular genetic testing. This review summarizes the genetics, current guideline recommendations, and evidence supporting the genetic evaluation framework of five hereditary forms of cardiomyopathy: dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), arrhythmogenic right ventricular cardiomyopathy (ARVC), restrictive cardiomyopathy (RCM), and left ventricular noncompaction (LVNC).

Indexed as

CardiomyopathiesGenetic CounselingGenetic TestingHeart FailureHumansCardiomyopathyEvolving approachesGenetic evaluationGenetic testingHereditary

Identifiers

PMID26472190
OpenAlexW1932990615

What OpenQuestion holds

Textmetadata
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.