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Record W4414457940 · doi:10.1001/jamacardio.2025.3055

Electrocardiogram vs Electrophysiological Study and Major Conduction Delays in Myotonic Dystrophy Type 1

2025· article· en· W4414457940 on OpenAlexaff
Nicolas Clémenty, Fabien Labombarda, François Grolleau, Vincent Algalarrondo, Guillaume Bassez, Henri-Marc Bécane, Anthony Béhin, Françoise Chapon, Mohamed El Hachmi, Abdallah Fayssoil, Bertrand Fontaine, Rodrigue Garcia, Pascal Laforêt, Arnaud Lazarus, Marion Masingue, Armelle Magot, Yann Péréon, Vincent Probst, Leslie Motté, Malika Saadi, Denis Duboc, Tanya Stojkovic, Raphaël Porcher, Karim Wahbi

Bibliographic record

VenueJAMA Cardiology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsMyotonic dystrophyRisk stratificationElectrocardiographyElectrophysiologyCohortPR intervalConduction abnormalitiesElectrodiagnosisElectrical conduction system of the heart

Abstract

fetched live from OpenAlex

Importance: For the prevention of sudden cardiac death in myotonic dystrophy type 1 (dystrophia myotonica; DM1), professional practice guidelines recommend pacemaker implantation in asymptomatic patients with a PR interval greater than or equal to 240 milliseconds and/or QRS duration greater than or equal to 120 milliseconds on electrocardiogram (ECG), or a His-ventricular (HV) interval greater than or equal to 70 milliseconds during electrophysiological study (EPS), as class IIa indications. Objective: To determine which of these strategies-ECG or EPS based-is more effective in predicting major bradyarrhythmic events (MBAEs). Design, Setting, and Participants: This was a cohort analysis of retrospectively collected longitudinal data from the DM1 Heart Registry. The setting included cardiology and neurology departments of 6 French university hospitals. Study participants were selected from individuals enrolled in the DM1 Heart Registry between 2000 and 2020. The DM1 Heart Registry includes adults with genetically confirmed DM1. Included patients had a history of first EPS after 1999 and no personal history of advanced atrioventricular block or sustained ventricular tachycardia. Study data were analyzed from January to July 2025. Exposures: ECG- and EPS-based strategies. Main Outcomes and Measures: The primary outcome was MBAEs, defined as sudden cardiac death, resuscitated cardiac arrest, or second-degree type II or complete atrioventricular block. Results: Of 1778 adults with genetically confirmed DM1 enrolled in the DM1 Heart Registry, a total of 706 patients (mean [SD] age, 42 [13] years; 359 male [51%]) were included in this study. At baseline, 273 patients (38%) had an HV interval greater than or equal to 70 milliseconds, and 232 (32%) met ECG criteria. Over a median (IQR) follow-up of 5.9 (2.3-9.7) years, 99 patients (14%) experienced an MBAE. In multivariable Cox and joint models incorporating baseline and time-varying values of PR and QRS durations, the HV interval was the only variable significantly associated with the incidence of MBAEs (hazard ratio [HR], 1.77; 95% CI, 1.46-2.16; P < .001 and HR, 1.78; 95% CI, 1.40-2.22; P = .001, respectively). Compared with ECG-based criteria, the EPS criterion proved to be a more reliable (HR, 2.89; 95% CI, 1.92-4.34 vs HR, 1.95; 95% CI, 1.31-2.89) and more sensitive (performance index [SE], 68.35% [6.24%] vs 34.76% [6.47%]) predictor of MBAE and accurately reclassified 28.8% of patients with an MBAE. Lowering the threshold to HV greater than or equal to 65 milliseconds further improved sensitivity (performance index [SE], 90.18% [3.85%]) and net reclassification improvement (33.7%; 95% CI, 19.6%-48.2%) for MBAE prediction. Conclusions and Relevance: In this cohort of patients with DM1, the HV interval outperformed ECG criteria in predicting MBAEs. An HV threshold greater than or equal to 65 milliseconds may enhance risk stratification for prophylactic pacing.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.744

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.281
Teacher spread0.263 · 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 designBench or experimental
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

Citations7
Published2025
Admission routes1
Has abstractyes

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