External validation of the Canadian Syncope Risk Score for patients presenting with undifferentiated syncope to the emergency department
Bibliographic record
Abstract
OBJECTIVE: To validate the accuracy and safety of the Canadian Syncope Risk Score (CSRS) for patients presenting with syncope. METHODS: Single centre prospective observational study in Brisbane, Australia. Adults presenting to the ED with syncope within the last 24 h were recruited after applying exclusion criteria. Study was conducted over 1 year, from March 2018 to March 2019. Thirty-day serious adverse events (SAE) were reported based on the original derivation study and standardised outcome reporting for syncope. Individual patient CSRS was calculated and correlated with 30-day SAE and disposition status from ED. RESULTS: Two hundred and eighty-three patients were recruited to the study. Average age was 55.6 years (SD 22.7 years), 37.1% being male with a 39.9% admission rate. Thirty-day SAE occurred in seven patients (2.5%) and no recorded deaths. The CSRS performed with a sensitivity of 71.4% (95% confidence interval [CI] 30.3-94.9%), specificity 72.8% (95% CI 67.1-77.9%) for a threshold score of 1 or higher. CONCLUSION: Syncope patients in our study were predominantly very low to low risk (72%). The prevalence of 30-day SAE was low, majority occurring following hospital discharge. Sensitivity estimates for CSRS was lower than the derivation study but lacked robustness with wide CIs because of a small sample size and number of events observed. However, the CSRS did not miss any clinically relevant outcomes in low risk patients making it potentially useful in aiding their disposition. Larger validation studies in Australia are encouraged to further test the diagnostic accuracy of the CSRS.
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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 | 0.012 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".