Recent History of Vasovagal Syncope in a Young, Referral‐Based Population Is a Stronger Predictor of Recurrent Syncope Than Lifetime Syncope Burden
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Bibliographic record
Abstract
INTRODUCTION: accurate selection of patients for vasovagal syncope studies requires strong risk stratification and knowledge of the natural history of syncope. We aimed to test the hypothesis that recent history of vasovagal syncope compared to distant history better predicts subsequent recurrence of syncope. METHODS AND RESULTS: in all, 208 subjects with a positive tilt test and ≥ 3 lifetime syncope spells were followed for 1 year. Syncope episodes in the preceding year and total historical spells were compared for their ability to predict a syncope recurrence using the criteria of optimal statistical significance, best linear separation of risk populations, and impact on power calculations. The number of vasovagal syncope spells in the preceding year better predicted syncope recurrence when compared to total number of historical spells (likelihood ratio statistic 28.4, P < 0.0001; versus 20.4, P = 0.001), and showed a substantial effect as the number of syncope events increased. For example, syncope recurred in 22% of those with <2 spells in the previous year compared to 69% in those with >6 spells. A history of no syncope compared to any syncope in the preceding year was associated with a 1-year probability of 7% versus 46% for syncope recurrence. A study designed to detect a 50% decrease in syncope recurrence at P = 0.05 with 80% power would require 159 patients with at least 3 lifetime spells, and only 108 patients with at least 3 spells in the previous year. CONCLUSIONS: the number of syncope events in the year preceding clinical evaluation is the best predictor of syncope recurrence.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it