MétaCan
Menu
Back to cohort

Arrhythmogenic right ventricular cardiomyopathy – evolution of electrocardiographic markers during long-term follow-up prior to ascertainment of diagnosis

2022· article· en· W4306319404 on OpenAlexaffabout
Andreas Svensson, Jonas Carlson, Henrik Kjærulf Jensen, Per Dahlberg, Henning Bundgaard, Alex Hørby Christensen, Miranda Boonstra, Jesper Hastrup Svendsen, J. Tourigny, Anneline S.J. te Riele, Pyotr G. Platonov

Bibliographic record

VenueEuropean Heart Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineCardiologyInternal medicineQRS complexRepolarizationCardiomyopathyLeft bundle branch blockElectrocardiographyArrhythmogenic right ventricular dysplasiaBundle branch blockEjection fractionHeart failure

Abstract

fetched live from OpenAlex

Abstract Background Depolarization and repolarization abnormalities are part of the diagnostic Task Force Criteria of 2010 (TFC2010) for arrhythmogenic right ventricular cardiomyopathy (ARVC). These abnormalities are thought to be progressive but have also been described as dynamic and sometimes reversible. Evolution of ECG abnormalities prior to clinical ARVC diagnosis is poorly studied. Objective To assess the evolution of ECG depolarization and repolarization characteristics in patients with ARVC prior to diagnosis and to identify markers of disease progression at a preclinical stage. Methods 353 patients with definite ARVC from Sweden, Denmark, the Netherlands and Canada with at least one 12-lead digital ECG (65% males, 67% probands, 56% mutation carriers, median age at diagnosis 42 [IQR 29–53] years and median age at first ECG 44 [30–55] years) were included. Digital ECGs were extracted from regional ECG archives. ECGs with left bundle branch block, ventricular pacing or recorded either prior to 15 years of age or after heart transplantation were excluded. Remaining 6,871 ECGs were digitally processed and automatically analysed using the Glasgow algorithm. Median values for overall QRS duration, terminal activation delay (TAD) in lead V1 as well as amplitudes of QRS-T-components in precordial leads per patient per year were used for analyses and graphically represented using Lowess smoothing with cubic splines (Figure 1). Blue lines indicate smoothed conditional mean with 95% confidence interval (shadow). Time “0” (red line) indicates the time when TFC2010 were fulfilled for definite diagnosis. A database of 18,564 anonymized digital ECGs (58% males, median age at latest ECG 41 years [IQR 32–52]) who were in contact with health care during 2020–2021 was processed using the same exclusion criteria and signal-processing methodology as in the ARVC group and used as a reference (black line). Results TAD in lead V1 and overall QRS duration demonstrated a significant increase years before ARVC diagnosis, and significant reductions were seen in QRS-T voltages measured as R wave amplitude, QRS amplitude (the absolute sum of R wave and S wave), and T wave amplitude (Table 1 and Figure 1). The changes were seen in all precordial leads, not only the right-sided, and visually diverging from the controls. Conclusion Development of the ARVC ECG phenotype started several years before diagnosis and continued afterwards. QRS duration and TAD increased, QRS voltages decrease, and T wave amplitude decreased eventually leading to T wave inversion. These changes might be visually assessed but also measured with available ECG software. These findings may be clinically useful in the screening and follow-up of ARVC relatives. Funding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Governmental funding of clinical research (ALF), Region Ostergotland, Sweden.The Swedish Heart-Lung Foundation.

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)0.002
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 score0.031
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
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 head0.007
GPT teacher head0.234
Teacher spread0.227 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueEuropean Heart JournalSame topicCardiovascular Effects of ExerciseFrench-language works237,207