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Record W2883202428 · doi:10.1093/eurheartj/ehy412

SCN5A mutations in 442 neonates and children: genotype–phenotype correlation and identification of higher-risk subgroups

2018· article· en· W2883202428 on OpenAlexaff
Alban‐Elouen Baruteau, Florence Kyndt, Elijah R. Behr, Arja S. Vink, Matthias Lachaud, Anna Joong, Jean‐Jacques Schott, Minoru Horie, Isabelle Denjoy, Lia Crotti, Wataru Shimizu, J. Martijn Bos, Elizabeth A. Stephenson, Leonie C.H. Wong, Dominic J. Abrams, Andrew M. Davis, Annika Winbo, Anne M. Dubin, Shubhayan Sanatani, Leonardo Liberman, Juan Pablo Kaski, Boris Rudic, Sit Yee Kwok, Claudine Rieubland, Jacob Tfelt‐Hansen, George F. Van Hare, Béatrice Guyomarc’h-Delasalle, Nico A. Blom, Yanushi D. Wijeyeratne, Jean‐Baptiste Gourraud, Hervé Le Marec, Junichi Ozawa, Véronique Fressart, Jean‐Marc Lupoglazoff, Federica Dagradi, Carla Spazzolini, Takeshi Aiba, David J. Tester, Laura Zahavich, Virginie Beauséjour-Ladouceur, Mangesh P. Jadhav, Jonathan R. Skinner, Sonia Franciosi, Andrew D. Krahn, Mena Abdelsayed, Peter C. Ruben, Tak‐Cheung Yung, Michael J. Ackerman, Arthur A.M. Wilde, Peter J. Schwartz, Vincent Probst

Bibliographic record

VenueEuropean Heart Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsSimon Fraser UniversityHospital for Sick ChildrenUniversity of British ColumbiaSickKids FoundationBC Children's HospitalUniversity of Toronto
FundersNederlandse Federatie van Universitair Medische CentraSociété Française de CardiologieUniversity College LondonGreat Ormond Street Hospital for ChildrenZonMwNational Institute for Health and Care ResearchNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
KeywordsMedicineGenotypePhenotypeCorrelationIdentification (biology)GeneticsGenotype-phenotype distinctionInternal medicineGene

Abstract

fetched live from OpenAlex

Aims: To clarify the clinical characteristics and outcomes of children with SCN5A-mediated disease and to improve their risk stratification. Methods and results: A multicentre, international, retrospective cohort study was conducted in 25 tertiary hospitals in 13 countries between 1990 and 2015. All patients ≤16 years of age diagnosed with a genetically confirmed SCN5A mutation were included in the analysis. There was no restriction made based on their clinical diagnosis. A total of 442 children {55.7% boys, 40.3% probands, median age: 8.0 [interquartile range (IQR) 9.5] years} from 350 families were included; 67.9% were asymptomatic at diagnosis. Four main phenotypes were identified: isolated progressive cardiac conduction disorders (25.6%), overlap phenotype (15.6%), isolated long QT syndrome type 3 (10.6%), and isolated Brugada syndrome type 1 (1.8%); 44.3% had a negative electrocardiogram phenotype. During a median follow-up of 5.9 (IQR 5.9) years, 272 cardiac events (CEs) occurred in 139 (31.5%) patients. Patients whose mutation localized in the C-terminus had a lower risk. Compound genotype, both gain- and loss-of-function SCN5A mutation, age ≤1 year at diagnosis in probands and age ≤1 year at diagnosis in non-probands were independent predictors of CE. Conclusion: In this large paediatric cohort of SCN5A mutation-positive subjects, cardiac conduction disorders were the most prevalent phenotype; CEs occurred in about one-third of genotype-positive children, and several independent risk factors were identified, including age ≤1 year at diagnosis, compound mutation, and mutation with both gain- and loss-of-function.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.100
Threshold uncertainty score0.261

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.263
Teacher spread0.253 · 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 teacher head, 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

Citations49
Published2018
Admission routes1
Has abstractyes

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