Syncope recurrence and mortality: a systematic review
Bibliographic record
Abstract
AIMS: Data on adverse events and death rates following syncope are heterogeneous among studies, and knowledge of syncope prognosis could help to better define the correct management of patients. METHODS AND RESULTS: We performed a systematic review of literature by searching for prospective observational studies enrolling consecutive patients presenting to the Emergency Department because of syncope. The outcomes considered were syncope recurrence and short- and long-term mortality. Morbidity and a composite of morbidity and mortality were also assessed. Pooled event rates and 95% confidence intervals (CI) were calculated for each outcome using the random effects model. Twenty-five studies (11 158 patients) were included. The incidence of syncope relapse linearly increased from 0.3% at 30 days to 22% at 2 years follow-up. One-year mortality rate varied between 5.7 and 15.5%; the pooled estimate was 8.4% (95% CI: 6.7-10.2%). The incidence of adverse events (morbidity) varied between 6.1 and 25.2% at 10 days and 2 years, respectively. The short-term (10 days) pooled incidence of the composite of morbidity and mortality was 9.1% (95% CI: 6.6-12.5%). We found a high statistical heterogeneity between studies. CONCLUSION: This meta-analysis of prospective observational studies shows that the chance of being asymptomatic linearly progressively decreased over time after the first syncope. Short-term (10-30 days) mortality after syncope was <2% and that the overall 10-day rate of the composite endpoint of death and major events was ∼9%. The knowledge of syncope prognosis could help clinicians to understand syncope patients' prognosis and researchers to design future studies.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".