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Record W4212806567 · doi:10.1161/jaha.121.024220

Pediatric Hypertrophic Cardiomyopathy: Exploring the Genotype‐Phenotype Association

2022· article· en· W4212806567 on OpenAlexaff

Bibliographic record

VenueJournal of the American Heart Association · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsToronto General HospitalSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsHypertrophic cardiomyopathySudden cardiac deathRisk stratificationSudden deathCardiomyopathyAssociation (psychology)Clinical phenotypeDiseaseMEDLINE

Abstract

fetched live from OpenAlex

Pediatric hypertrophic cardiomyopathy (HCM) is the most common form of cardiomyopathy in children and a leading cause of sudden cardiac death. Yet, the association between genotype variation, phenotype expression, and adverse events in pediatric HCM has not been fully elucidated. Although the literature on this topic is evolving in adult HCM, the evidence in children is lacking. Solidifying our understanding of this relationship could improve risk stratification as well as improve our comprehension of the underlying pathophysiological characteristics of pediatric HCM. In this state-of-the-art review, we examine the current literature on genetic variations in HCM and their association with outcomes in children, discuss the current approaches to identifying cardiovascular phenotypes in pediatric HCM, and explore possible avenues that could improve sudden cardiac death risk assessment.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.253
Teacher spread0.231 · 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

Citations22
Published2022
Admission routes1
Has abstractyes

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