Does any therapy really work for neurocardiogenic syncope?
Bibliographic record
Abstract
Effectiveness of a treatment for neurocardiogenic syncope can be defined in terms of symptom response, quality-of-life, healthcare utilization, treatment side effects and cost-effectiveness. Most trials have focused on syncope recurrence or burden, without assessing quality-of-life formally. Drug and device interventions are characterized by a dearth of randomized controlled trials, with those few of robust design demonstrating little impact on recurrence of syncope. General advice includes hydration, trigger recognition and counter pressure maneuvers to attenuate episodes. Lifestyle recommendations have limited comparative effectiveness evidence, but are favored due to lack of side effects and low cost. The frequency of syncope improves in many patients regardless of the intervention, although ultimate recurrence of syncope remains high. In the minority of patients seeking treatment due to recurrence, midodrine has reasonable supporting evidence for effectiveness with some evidence for beta-blockers in older age patients. Emerging evidence favors pacing in patients with asystole during spontaneous (as opposed to provoked) syncope. Combining long-term implantable cardiac monitoring, tilt and adenosine triphosphate testing may yet accurately define the optimal minority who benefit from pacing. In the remaining majority, pharmacologic and device interventions should be used sparingly until clear benefits are established. Better understanding of patient fears, beliefs and behaviors may help develop cognitive therapies and improve quality-of-life alongside the focus on physical symptoms.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".