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Record W4291368113 · doi:10.14740/cr1373

Arrhythmogenic Right Ventricular Cardiomyopathy: The Role of Genetics in Diagnosis, Management, and Screening

2022· review· en· W4291368113 on OpenAlexvenueno aff
Mihir Odak, Steven Douedi, Anton Mararenko, Abbas Alshami, Islam Elkherpitawy, Hani Douedi, Eran S. Zacks, Brett Sealove

Bibliographic record

VenueCardiology Research · 2022
Typereview
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGenetic testingCardiologyInternal medicineSudden cardiac deathCardiomyopathyGenetic counselingSudden deathHeart failureIntensive care medicineGenetics

Abstract

fetched live from OpenAlex

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a predominantly autosomal dominant genetic condition in which fibrous and fatty tissue infiltrate and replace healthy myocardial tissue. This uncommon yet debilitating condition can cause ventricular arrhythmias, cardiac failure, and sudden cardiac death. Management focuses primarily on prevention of syndrome sequelae in order to prevent morbidity and mortality. Genetic testing and screening in affected families, although utilized clinically, has not yet been incorporated in guidelines due to lack of larger studies and data. We aim herein to identify causative gene mutations, present advancements in diagnosis and management, and describe the role of genetic screening and counseling in patients with ARVC. With the advancement of genetic testing and therapy, diseases such as ARVC may become more accurately diagnosed and more effectively managed, ultimately significantly reducing morbidity and mortality.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.069
GPT teacher head0.381
Teacher spread0.312 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations14
Published2022
Admission routes1
Has abstractyes

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