Development of the Canadian Syncope Risk Score to predict serious adverse events after emergency department assessment of syncope
Bibliographic record
Abstract
BACKGROUND: Syncope can be caused by serious conditions not evident during initial evaluation, which can lead to serious adverse events, including death, after disposition from the emergency department. We sought to develop a clinical decision tool to identify adult patients with syncope who are at risk of a serious adverse event within 30 days after disposition from the emergency department. METHODS: We prospectively enrolled adults (age ≥ 16 yr) with syncope who presented within 24 hours after the event to 1 of 6 large emergency departments from Sept. 29, 2010, to Feb. 27, 2014. We collected standardized variables at index presentation from clinical evaluation and investigations. Adjudicated serious adverse events included death, myocardial infarction, arrhythmia, structural heart disease, pulmonary embolism, serious hemorrhage and procedural interventions within 30 days. RESULTS: We enrolled 4030 patients with syncope; the mean age was 53.6 years, 55.5% were women, and 9.5% were admitted to hospital. Serious adverse events occurred in 147 (3.6%) of the patients within 30 days after disposition from the emergency department. Of 43 candidate predictors examined, we included 9 in the final model: predisposition to vasovagal syncope, heart disease, any systolic pressure reading in the emergency department < 90 or > 180 mm Hg, troponin level above 99th percentile for the normal population, abnormal QRS axis (< -30° or > 100°), QRS duration longer than 130 ms, QTc interval longer than 480 ms, emergency department diagnosis of cardiac syncope and emergency department diagnosis of vasovagal syncope (C statistic 0.88, 95% confidence interval [CI] 0.85-0.90; optimism 0.015; goodness-of-fit p = 0.11). The risk of a serious adverse event within 30 days ranged from 0.4% for a score of -3 to 83.6% for a score of 11. The sensitivity was 99.2% (95% CI 95.9%-100%) for a threshold score of -2 or higher and 97.7% (95% CI 93.5%-99.5%) for a threshold score of -1 or higher. INTERPRETATION: The Canadian Syncope Risk Score showed good discrimination and calibration for 30-day risk of serious adverse events after disposition from the emergency department. Once validated, the tool will be able to accurately stratify the risk of serious adverse events among patients presenting with syncope, including those at low risk who can be discharged home quickly.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".