Ventricular Tachycardia Burden and Mortality: Association or Causality?
Bibliographic record
Abstract
Ventricular tachycardia (VT) is a potentially fatal cardiac rhythm disorder. Implantable cardioverter defibrillators (ICDs) are the primary management strategy for VT and have been shown to reduce the incidence of death but, ICDs do not reduce VT recurrences. Further, mounting evidence indicates that high VT burden, defined as the cumulative number of recurrent VTs or ICD shocks, is associated with an elevated risk of death; however, it is unclear if high VT burden is a cause of death or a marker of severe heart disease. Proposed mechanisms for a causal pathway suggest that multiple VT episodes or potential deleterious effects from ICDs might alter the myocardium of the ventricles to induce worsening heart disease, which might translate to an increased risk of mortality. In this review, we present the evidence to support association and causation hypotheses for the relationship between VT burden and risk of mortality and indicate potential gaps in evidence. Overall, there is insufficient evidence to prove causal hypotheses for the relationship between VT burden and mortality. Consistent definitions for VT burden, randomized controlled trials that assess the relationship between VT burden and mortality, and observational studies that capture VT burden are warranted to investigate if a potential causal relationship exists.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".