Evidence map›Paper›PMID 37681527›Full record

ArticleJournal of the American Heart Association2023

A Multicenter Analysis of Abnormal Chromosomal Microarray Findings in Congenital Heart Disease.

Benjamin J Landis, Lindsey R Helvaty, Gabrielle C Geddes, Jiuann-Huey Ivy Lin, Svetlana A Yatsenko, Cecilia W Lo, William L Border, Stephanie Burns Wechsler, Chaya N Murali, Mahshid S Azamian and 6 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Journal of the American Heart Association, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

12 citing papers in PubMed, 14 citations in OpenAlex.

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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

16 authors at 6 institutions in 2 countries.

Benjamin J LandisIndiana University School of Medicine Indianapolis IN.ORCID 0000-0001-5837-8581
Lindsey R HelvatyIndiana University School of Medicine Indianapolis IN.
Gabrielle C GeddesIndiana University School of Medicine Indianapolis IN.
Jiuann-Huey Ivy LinUniversity of Pittsburgh Pittsburgh PA.ORCID 0000-0003-3029-6079
Svetlana A YatsenkoUniversity of Pittsburgh Pittsburgh PA.ORCID 0000-0003-4809-8601
Cecilia W LoUniversity of Pittsburgh Pittsburgh PA.ORCID 0000-0003-4314-3434
William L BorderEmory University School of Medicine Atlanta GA.
Stephanie Burns WechslerEmory University School of Medicine Atlanta GA.
Chaya N MuraliBaylor College of Medicine Houston TX.
Mahshid S AzamianBaylor College of Medicine Houston TX.ORCID 0000-0002-8543-8284
Seema R LalaniBaylor College of Medicine Houston TX.
Robert B HintonCincinnati Children's Hospital Medical Center Cincinnati OH.
Vidu GargNationwide Children's Hospital The Ohio State University Columbus OH.ORCID 0000-0002-3778-5927
Kim L McBrideNationwide Children's Hospital The Ohio State University Columbus OH.ORCID 0000-0002-8407-8942
Jennelle C HodgeIndiana University School of Medicine Indianapolis IN.
Stephanie M WareIndiana University School of Medicine Indianapolis IN.ORCID 0000-0003-4714-0142
Indiana University School of MedicineBaylor College of Medicine · USUniversity of Pittsburgh · USEmory University · USNationwide Children's Hospital · USCincinnati Children's Hospital Medical Center · US

Funding

Investigating the role of mitochondria in thoracic aortic aneurysm pathogenesisK23HL141667 · NHLBI · INDIANA UNIVERSITY INDIANAPOLIS · PI LANDIS, BENJAMIN JOHN · 2019 to 2023
$810k
NHLBI NIH HHS K23 HL141667
6 · The paper itself

Abstract

Background Chromosomal microarray analysis (CMA) provides an opportunity to understand genetic causes of congenital heart disease (CHD). The methods for describing cardiac phenotypes in patients with CMA abnormalities have been inconsistent, which may complicate clinical interpretation of abnormal testing results and hinder a more complete understanding of genotype-phenotype relationships. Methods and Results Patients with CHD and abnormal clinical CMA were accrued from 9 pediatric cardiac centers. Highly detailed cardiac phenotypes were systematically classified and analyzed for their association with CMA abnormality. Hierarchical classification of each patient into 1 CHD category facilitated broad analyses. Inclusive classification allowing multiple CHD types per patient provided sensitive descriptions. In 1363 registry patients, 28% had genomic disorders with well-recognized CHD association, 67% had clinically reported copy number variants (CNVs) with rare or no prior CHD association, and 5% had regions of homozygosity without CNV. Hierarchical classification identified expected CHD categories in genomic disorders, as well as uncharacteristic CHDs. Inclusive phenotyping provided sensitive descriptions of patients with multiple CHD types, which occurred commonly. Among CNVs with rare or no prior CHD association, submicroscopic CNVs were enriched for more complex types of CHD compared with large CNVs. The submicroscopic CNVs that contained a curated CHD gene were enriched for left ventricular obstruction or septal defects, whereas CNVs containing a single gene were enriched for conotruncal defects. Neuronal-related pathways were over-represented in single-gene CNVs, including top candidate causative genes

Indexed as

Heart Defects, CongenitalChildGenomicsHeartHeart VentriclesHumansMicroarray Analysischromosomal microarraycongenital heart diseaseconotruncal defectsgenomicsneurodevelopment

Identifiers

PMID37681527
PMCPMC10547279
OpenAlexW4386529895

What OpenQuestion holds

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LicenceCC BY-NC
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.