Multicentre external validation of the Canadian Syncope Risk Score to predict adverse events and comparison with clinical judgement
Bibliographic record
Abstract
BACKGROUND: The Canadian Syncope Risk Score (CSRS) has been proposed for syncope risk stratification in the emergency department (ED). The aim of this study is to perform an external multicenter validation of the CSRS and to compare it with clinical judgement. METHODS: Using patients previously included in the SyMoNE database, we enrolled subjects older than 18 years who presented reporting syncope at the ED. For each patient, we estimated the CSRS and recorded the physician judgement on the patients' risk of adverse events. We performed a 30-day follow-up. RESULTS: From 1 September 2015 to 28 February 2017, we enrolled 345 patients; the median age was 71 years (IQR 51-81), 174 (50%) were men and 29% were hospitalised. Serious adverse events occurred in 43 (12%) of the patients within 30 days. The area under the curve of the CSRS and clinical judgement was 0.75 (95% CI 0.68 to 0.81) and 0.68 (95% CI 0.61 to 0.74), respectively. The risk of adverse events of patients at low risk according to the CSRS and clinical judgement was 6.7% and 2%, with a sensitivity of 70% (95% CI 54% to 83%) and 95% (95% CI 84% to 99%), respectively. CONCLUSION: This study represents the first validation analysis of CSRS outside Canada. The overall predictive accuracy of the CSRS is similar to the clinical judgement. However, patients at low risk according to clinical judgement had a lower incidence of adverse events as compared with patients at low risk according to the CSRS. Further studies showing that the adoption of the CSRS improve patients' outcomes is warranted before its widespread implementation.
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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 | 0.001 | 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) | 0.004 | 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".