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Record W2037514737 · doi:10.2217/fca.10.27

The Genetic and Clinical Features of Cardiac Channelopathies

2010· review· en· W2037514737 on OpenAlexaff
Jason D. Roberts, Michael H. Gollob

Bibliographic record

VenueFuture Cardiology · 2010
Typereview
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCatecholaminergic polymorphic ventricular tachycardiaMedicineBrugada syndromeShort QT syndromeSudden cardiac deathLong QT syndromeDiseaseCardiologyInternal medicineVentricular tachycardiaChannelopathyImplantable cardioverter-defibrillatorPathophysiologyIntensive care medicineQT intervalRyanodine receptor 2

Abstract

fetched live from OpenAlex

Sudden cardiac death, secondary to malignant ventricular arrhythmias, has traditionally been associated with structural heart disease. An important exception includes a group of clinical entities referred to as 'channelopathies' that develop secondary to genetic mutations, which alter cardiac ion channel activity. Otherwise healthy individuals affected by these forms of primary electrical disease are vulnerable to fatal arrhythmic events from a very young age. At present, there are four distinct conditions that are classified as cardiac channelopathies, namely congenital long-QT syndrome, Brugada syndrome, catecholaminergic polymorphic ventricular tachycardia and short-QT syndrome. Our growing insight into the genetics of these conditions has led to an improved understanding of the molecular pathophysiology responsible for the malignant arrhythmias characterizing these disorders. However, despite our knowledge of these conditions, the success of medical therapy remains modest and the prevention of sudden cardiac death may necessitate insertion of an implantable cardioverter-defibrillator. The young age of affected patients makes this a particularly undesirable treatment strategy and emphasizes the importance of translating our insight into the molecular pathophysiology defining these conditions into more effective forms of therapy.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.002
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 head0.016
GPT teacher head0.323
Teacher spread0.308 · 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.

Study designOther design
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

Citations19
Published2010
Admission routes1
Has abstractyes

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