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: We included 8183 patients, of whom 743 (9.1%) were admitted; 658/743 (88.6%) were matched. Admitted patients had higher odds of detection of a serious adverse event (odds ratio [OR] 5.0, 95% confidence interval [CI] 3.3–7.4), nonfatal arrhythmia (OR 5.1, 95% CI 2.9–8.8) and nonarrhythmic serious adverse event (OR 6.3, 95% CI 2.9–13.5). There were no significant differences between the 2 groups in death (OR 1.0, 95% CI 0.4–2.7) or detection of ventricular arrhythmia (OR 2.0, 95% CI 0.7–6.0). Differences between admitted and discharged patients in detection of serious adverse events were greater for those with a CSRS indicating medium to high risk (p = 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 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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".