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Abstract 16468: Results of Research Genetic Testing in Pediatric Cardiomyopathy Patients Justify Broader Clinical Genetic Testing

2015· article· en· W2885344095 on OpenAlexaff
Stephanie M. Ware, Steven E. Lipshultz, Steven D. Colan, Ling Shi, Charles E. Canter, Daphne T. Hsu, Debra A. Dodd, Melanie D. Everitt, Paul F. Kantor, Linda J. Addonizio, John L. Jefferies, Joseph W. Rossano, Elfriede Pahl, Paolo Rusconi, Jeffrey Schubert, Teresa Lee, Erin Miller, Muhammad Tariq, James D. Wilkinson, Jeffrey A. Towbin

Bibliographic record

VenueCirculation · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsStollery Children's Hospital
Fundersnot available
KeywordsMedicineGenetic testingCardiomyopathyProbandExome sequencingExomeFamily historyDiseaseRestrictive cardiomyopathyInternal medicineMutationBioinformaticsGeneticsHeart failureGeneBiology

Abstract

fetched live from OpenAlex

Introduction: Pediatric cardiomyopathies are genetically heterogeneous diseases with high risk of death or cardiac transplant. Despite progress in identifying causes, the majority of cases remain idiopathic. Currrently, genetic testing is not performed in all children with cardiomyopathy. Gene identification leads to better individual risk stratification and has the potential to stimulate the development of therapies based on the underlying mutation. The aim of this study is to identify genetic mutations in pediatric cardiomyopathy patients using whole exome sequencing. Hypothesis: Sarcomeric mutations are under-diagnosed causes of all forms of cardiomyopathy in children. Methods: Probands with cardiomyopathy were recruited from 11 institutions. Results of clinical genetic testing prior to enrollment were collected. Whole exome sequencing was performed and mutations were identified in 35 genes currently available on clinical genetic testing panels. Results: The initial 154 probands subjected to exome included 78 patients with DCM, 43 with HCM, 14 with RCM, and 19 with LVNC, mixed, or unknown types. Familial disease was present in 38% and the remainder were idiopathic. Twenty-seven percent had positive clinical genetic testing prior to enrollment. Exome testing identified mutations in 38 subjects who had not had clinical testing, increasing the cohort positive testing rate to 55% (DCM, 34.6%; HCM, 74.4%; RCM, 71.4%). Forty-five percent of subjects with no family history of disease had an identifiable mutation. Conclusions: Pediatric cardiomyopathy patients have a high incidence of mutations that can be identified by clinically available genetic testing. Lack of a family history of cardiomyopathy was not predictive of normal genetic testing. These results support the broader use of genetic testing in pediatric patients with all functional phenotypes of cardiomyopathy to identify disease causation allowing better family risk stratification.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.257
GPT teacher head0.412
Teacher spread0.156 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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