Syncope in a Working-Age Population: Recurrence Risk and Related Risk Factors
Bibliographic record
Abstract
Syncope in a worker undertaking risky tasks may result in fatalities for the individual or for third parties. We aimed at assessing the rate of syncope recurrence and the risk factors underlying the likelihood of syncope relapse in a working-age population. A prospective cohort of all patients aged 18⁻65 years consecutively admitted to the Emergency Department for syncope was enrolled. Risk of syncope relapse was assessed at a six-month, 1-year, and 5-year follow-up. Predictors of syncope recurrence have been evaluated at six months and 1 year from the syncope index by a multivariable logistic regression analysis. 348 patients were enrolled. Risk of syncope relapse was 9.2% at 6 months, 11.8% at 1 year, and 23.4% at 5 years. At 6-month follow-up, predictor of syncope recurrence was ≥3 prior lifetime syncope episodes. At 1-year, ≥3 prior lifetime syncope episodes, diabetes mellitus, and anaemia were risk factors for syncope relapse. There was an exceeding risk of recurrence in the first 6 months and a reduced risk of 3.5% per year after the first year. Anaemia, diabetes mellitus, and prior lifetime syncope burden are of importance when giving advice about the resumption of "high risk" jobs following a syncope episode.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".