Benefit of hospital admission for detecting serious adverse events among emergency department patients with syncope: a propensity-score–matched analysis of a multicentre prospective cohort
Bibliographic record
Abstract
BACKGROUND: The benefit of hospital admission after emergency department evaluation for syncope is unclear. We sought to determine the association between hospital admission and detection of serious adverse events, and whether this varied according to the Canadian Syncope Risk Score (CSRS). METHODS: We conducted a secondary analysis of a multicentre prospective cohort of patients assessed in the emergency department for syncope. We compared patients admitted to hospital and discharged patients, using propensity scores to match 1:1 for risk of a serious adverse event. The primary outcome was detection of a serious adverse event in hospital for admitted patients or within 30 days after emergency department disposition for discharged patients. RESULTS: = 0.04). INTERPRETATION: Patients with syncope were more likely to have serious adverse events identified within 30 days if they were admitted to hospital rather than discharged from the emergency department. However, the benefit of hospital admission is low for patients at low risk of a serious adverse event.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".