Age-Dependent Effect of β-Blockers in Preventing Vasovagal Syncope
Bibliographic record
Abstract
BACKGROUND: β-blockers have little effectiveness in preventing vasovagal syncope in unselected populations, but they might be effective in older patients. We determined whether β-blockers prevent vasovagal syncope in an age-related fashion. METHODS AND RESULTS: Two populations were studied. A proportional hazards analysis was performed on an observational cohort study of 153 patients with vasovagal syncope, 52 of whom received β-blockers. A multivariable proportional hazards model stratified by center was performed on 208 participants in the randomized Prevention of Syncope Trial (POST), examining the interaction between age group and treatment with metoprolol. Age-specific hazard ratios were estimated for both studies and combined using the inverse variance meta-analytic method. In the cohort study, the hazard ratio for syncope if treated with β-blockers was 1.54 (95% CI, 0.78-3.05) for patients aged <42 years and 0.48 (95% CI, 0.12-1.92) for patients aged ≥ 42 years. In POST, the proportional hazards model showed interactions between age and treatment effect (P=0.026). The hazard ratio for patients aged ≥ 42 years who received metoprolol was 0.53 (95% CI, 0.25-1.10); in patients aged <42 years, the hazard ratio was 1.62 (95% CI, 0.85-3.10). A pooled analysis of both studies yielded an estimate of the hazard ratio of 1.58 (CI, 1.00-2.31) for patients aged <42 years, and the hazard ratio was 0.52 (CI, 0.27-1.01) for patients aged ≥ 42 years. The 2 age groups differed significantly in response to β-blockers (P=0.007). CONCLUSIONS: β-blocker treatment may suppress vasovagal syncope in middle-aged patients aged >42 years.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".