Multivariable risk scores for predicting short‐term outcomes for emergency department patients with unexplained syncope: A systematic review
Bibliographic record
Abstract
ABSTRACT Objectives Emergency department (ED) patients with unexplained syncope are at risk of experiencing an adverse event within 30 days. Our objective was to systematically review the accuracy of multivariate risk stratification scores for identifying adult syncope patients at high and low risk of an adverse event over the next 30 days. Methods We conducted a systematic review of electronic databases (MEDLINE, Cochrane, Embase, and CINAHL) from database creation until May 2020. We sought studies evaluating prediction scores of adults presenting to an ED with syncope. We included studies that followed patients for up to 30 days to identify adverse events such as death, myocardial infarction, stroke, or cardiac surgery. We only included studies with a blinded comparison between baseline clinical features and adverse events. We calculated likelihood ratios and confidence intervals (CIs). Results We screened 13,788 abstracts. We included 17 studies evaluating nine risk stratification scores on 24,234 patient visits, where 7.5% (95% CI = 5.3% to 10%) experienced an adverse event. A Canadian Syncope Risk Score (CSRS) of 4 or more was associated with a high likelihood of an adverse event (LR score≥4 = 11, 95% CI = 8.9 to 14). A CSRS of 0 or less (LR score≤0 = 0.10, 95% CI = 0.07 to 0.20) was associated with a low likelihood of an adverse event. Other risk scores were not validated on an independent sample, had low positive likelihood ratios for identifying patients at high risk, or had high negative likelihood ratios for identifying patients at low risk. Conclusion Many risk stratification scores are not validated or not sufficiently accurate for clinical use. The CSRS is an accurate validated prediction score for ED patients with unexplained syncope. Its impact on clinical decision making, admission rates, cost, or outcomes of care is not known.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".