Syncope and Structural Heart Disease: Historical Criteria for Vasovagal Syncope and Ventricular Tachycardia
Bibliographic record
Abstract
INTRODUCTION: to develop evidence-based criteria that distinguish syncope due to ventricular tachycardia (VT) from vasovagal syncope (VVS) in patients with structural heart disease (SHD). METHODS AND RESULTS: one hundred and thirty-four patients with syncope and SHD completed a 118-item questionnaire and underwent noninvasive and invasive diagnostic assessments in a prospective cohort study. The contributions of symptoms to diagnoses were estimated with logistic regression and a point score was developed and then tested using receiver-operator characteristic analysis. The effectiveness of the decision rule was evaluated with long-term outcome. There were 21 patients with tilt-positive VVS, 78 with clinically declared or inducible VT, and 35 with no identified cause of syncope. Six features were significant predictors. Factors that predicted VT included male sex and age at onset >35 years; factors predicting VVS included prolonged sitting or standing; developing presyncope preceded by stress; recurrent headaches; and experiencing fatigue, which lasts longer than 1 minute after syncope. The point score correctly classified 92% of patients, diagnosing VT with 99% sensitivity and 68% specificity. The negative predictive value is ≥ 96%. Fully 67% of patients with undiagnosed syncope were classified as having VT based upon their symptoms. The decision rule predicted 9-year arrhythmia-free survival (VVS 84%, VT 39%, hazard ratio 4.32) and 9-year overall survival (VVS 66%, VT 37%, hazard ratio 2.87). CONCLUSIONS: the causes of syncope in patients with SHD, and their clinical outcomes, can be estimated accurately based on the clinical history. The history safely screens out the possibility of VT as a cause of syncope.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".