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Record W4389731875 · doi:10.1148/ryct.230155

Cardiac MRI and Clinical Outcomes in <i>TMEM43</i> Arrhythmogenic Cardiomyopathy

2023· article· en· W4389731875 on OpenAlexaff
João Matos, Emmi Helle, Melanie Care, Yasbanoo Moayedi, Michael H. Gollob, Paaladinesh Thavendiranathan, Danna Spears, Kate Hanneman

Bibliographic record

VenueRadiology Cardiothoracic Imaging · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineCardiologyCardiomyopathyInternal medicineArrhythmogenic right ventricular dysplasiaHeart failure

Abstract

fetched live from OpenAlex

Arrhythmogenic cardiomyopathy is an inherited cardiomyopathy that can involve both ventricles. Several genes have been identified as pathogenic in arrhythmogenic cardiomyopathy, including TMEM43. However, there are limited data on cardiac MRI findings in patients with TMEM43 variants to date. In this case series, cardiac MRI findings and clinical outcomes are described in 14 patients with TMEM43 variants, including eight (57%) with the pathogenic p.Ser358Leu variant (six female patients; mean age, 33 years ± 15 [SD]) and six (43%) with a TMEM43 variant of unknown significance (three female patients; mean age, 38 years ± 11). MRI findings demonstrated left ventricular systolic dysfunction in eight (57%) patients and right ventricular dysfunction in four (29%) patients. Among the nine patients with late gadolinium enhancement imaging, left ventricular late gadolinium enhancement was present in seven (78%; all subepicardial) patients. In summary, TMEM43 variants are associated with high prevalence of subepicardial late gadolinium enhancement and left ventricular dysfunction. Keywords: Arrhythmogenic Cardiomyopathy, Arrhythmogenic Right Ventricular Cardiomyopathy, TMEM43, Cardiac MRI, Genetic Variants Supplemental material is available for this article. © RSNA, 2023

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.326
Teacher spread0.315 · 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 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

Citations8
Published2023
Admission routes1
Has abstractyes

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