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Record W4381598047 · doi:10.1093/eurheartj/ehad295

Use, misuse, and pitfalls of the drug challenge test in the diagnosis of the Brugada syndrome

2023· review· en· W4381598047 on OpenAlexafffund
Arthur A.M. Wilde, Ahmad S. Amin, Hiroshi Morita, Rafik Tadros

Bibliographic record

VenueEuropean Heart Journal · 2023
Typereview
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersCanada Excellence Research Chairs, Government of CanadaCanada Research ChairsCardiovascular Research Foundation
KeywordsBrugada syndromeMedicineAsymptomaticGold standard (test)Internal medicineCardiologyPediatricsIntensive care medicine

Abstract

fetched live from OpenAlex

The diagnosis of Brugada syndrome (BrS) requires the presence of a coved (Type 1) ST segment elevation in the right precordial leads of the electrocardiogram (ECG). The dynamic nature of the ECG is well known, and in patients with suspected BrS but non-diagnostic ECG at baseline, a sodium channel blocker test (SCBT) is routinely used to unmask BrS. There is little doubt, however, that in asymptomatic patients, a drug-induced Brugada pattern is associated with a much better prognosis compared to a spontaneous Type 1 ECG. The SCBT is also increasingly used to delineate the arrhythmogenic substrate during ablation studies. In the absence of a "gold standard" for the diagnosis of BrS, sensitivity and specificity of the SCBT remain elusive. By studying patient groups with different underlying diseases, it has become clear that the specificity of the test may not be optimal. This review aims to discuss the pitfalls of the SCBT and provides some directions in whom and when to perform the test. It is concluded that because of the debated specificity and the overall very low risk for future events in asymptomatic individuals, patients should be properly selected and counseled before SCBT is performed and that SCBT should not be performed in asymptomatic patients with a Type 2 Brugada pattern and no family history of BrS or sudden death.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.459
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.091
GPT teacher head0.331
Teacher spread0.241 · 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 designNot applicable
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

Citations32
Published2023
Admission routes2
Has abstractyes

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