How to Perform and Interpret Provocative Testing for the Diagnosis of Brugada Syndrome, Long-QT Syndrome, and Catecholaminergic Polymorphic Ventricular Tachycardia
Bibliographic record
Abstract
S udden cardiac death (SCD) is predominantly related to coronary artery disease and its sequelae, cardiomyopathy, and congenital or valvular heart disease.No structural abnormalities are detectable in 5-8% of SCDs. 1 Identified ion channelopathies such as Brugada syndrome, long-QT syndrome (LQTS), and catecholaminergic polymorphic ventricular tachycardia (CPVT) contribute to this incidence.The diagnosis requires a high level of suspicion because of a resting ECG that is often borderline, intermittently normal, or frankly normal.Genetic testing does not provide a simple solution to this issue, as it is often neither sensitive nor specific even when the phenotype points to a specific entity and may yield results that are difficult to interpret (ie, variants of unknown significance).Pharmacological and/or exercise testing by manipulation/stressing the cardiac action potential can accentuate the desired abnormality or provoke a characteristic arrhythmia response.A systematic approach to clinical testing that includes drug provocation results in unmasking of the cause of apparently unexplained aborted SCD in Ͼ50% of patients and is very helpful in directing genetic testing of the index case and family to diagnose genetically mediated arrhythmia syndromes. 2This review will seek to highlight the clinical utility of provocative testing and describe how to perform and interpret provocative testing for the diagnosis of Brugada syndrome, LQTS, and CPVT.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".