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Record W2088180977 · doi:10.1093/europace/euu141

Atrial arrhythmias in the young: early onset atrial arrhythmias preceding a diagnosis of a primary muscular dystrophy

2014· article· en· W2088180977 on OpenAlexaff
Nik Stoyanov, Jeffrey R. Winterfield, Niraj Varma, Michael H. Gollob

Bibliographic record

VenueEP Europace · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineMuscular dystrophyCardiologyAtrial fibrillationInternal medicineElectrocardiography

Abstract

fetched live from OpenAlex

AIMS: The aetiology of atrial arrhythmias in the otherwise healthy and young is usually unrecognized. We hypothesized that rare cases of atrial arrhythmias in the young may represent the initial manifestation of a muscular dystrophy syndrome. METHODS AND RESULTS: We describe the clinical characteristics, disease progression, results of electrophysiological study, and genetic findings in four patients (age <40 years) presenting with idiopathic atrial arrhythmias who subsequently received a diagnosis of a muscular dystrophy syndrome. The mean age at presentation with atrial arrhythmias was 29.5 years (range, 21-37 years), and the mean delay to diagnosis of muscular dystrophy was 3.6 years (range, 0.5-6 years). Two patients received a subsequent diagnosis of myotonic dystrophy type 1 and 2 a diagnosis of Emery-Dreifuss muscular dystrophy. Disease-causing genetic defects were identified in all four patients. One patient underwent catheter ablation of atrial flutter, experiencing improvement in arrhythmia symptoms. Two patients required device therapy, each receiving cardiac resynchronization therapy-defibrillator implantation for progressive left ventricular dysfunction. CONCLUSION: Early onset atrial arrhythmias may be the first clinical manifestation of a muscular dystrophy syndrome. Appropriate clinical assessment and surveillance may uncover this primary cause and provide an opportunity for timely genetic counselling and family screening.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.105
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.250
Teacher spread0.232 · 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

Citations24
Published2014
Admission routes1
Has abstractyes

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