Predicting Short‐term Risk of Arrhythmia among Patients With Syncope: The Canadian Syncope Arrhythmia Risk Score
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Syncope can be caused by serious occult arrhythmias not evident during initial emergency department (ED) evaluation. We sought to develop a risk tool for predicting 30-day arrhythmia or death after ED disposition. METHODS: We conducted a multicenter prospective cohort study at six tertiary care EDs and included adults (≥16 years) with syncope. We collected standardized variables from clinical evaluation and investigations including electrocardiogram and troponin at index presentation. Adjudicated outcomes included death or arrhythmias including procedural interventions for arrhythmia within 30 days. We used multivariable logistic regression to derive the prediction model and bootstrapping for interval validation to estimate shrinkage and optimism. RESULTS: A total of 5,010 patients (mean ± SD age = 53.4 ± 23.0 years, 54.8% females, and 9.5% hospitalized) were enrolled with 106 (2.1%) patients suffering 30-day arrhythmia/death after ED disposition. We examined 39 variables and eight were included in the final model: lack of vasovagal predisposition, heart disease, any ED systolic blood pressure < 90 or > 180 mm Hg, troponin (>99th percentile), QRS duration > 130 msec, QTc interval > 480 msec, and ED diagnosis of cardiac/vasovagal syncope (optimism corrected C-statistic 0.90 [95% CI = 0.87-0.93]; Hosmer-Lemeshow p = 0.08). The Canadian Syncope Arrhythmia Risk Score had a risk ranging from 0.2% to 74.5% for scores of -2 to 8. At a threshold score of ≥0, the sensitivity was 97.1% (95% CI = 91.6%-99.4%) and specificity was 53.4% (95% CI = 52.0%-54.9%). CONCLUSIONS: The Canadian Syncope Arrhythmia Risk Score can improve patient safety by identification of those at risk for arrhythmias and aid in acute management decisions. Once validated, the score can identify low-risk patients who will require no further investigations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it