Sentinel Symptoms in Patients with Unexplained Cardiac Arrest: From the Cardiac Arrest Survivors with Preserved Ejection Fraction Registry (CASPER)
Bibliographic record
Abstract
BACKGROUND: Warning symptoms may provide an opportunity to diagnose genetic disorders leading to preventative therapy. We explored the symptom history of patients with apparently unexplained cardiac arrest to determine the frequency of sentinel symptoms. METHODS: Patients with apparently unexplained cardiac arrest and no evident cardiac disease underwent systematic clinical evaluation. Patients and first-degree relatives were interviewed to determine the presence of cardiac symptoms, and those with syncope underwent 2 structured Calgary Syncope Score questionnaires to determine the probable mechanism of syncope. RESULTS: One hundred consecutive cardiac arrest patients (age 43.0 ± 13.4 years, 60% male) and 63 first-degree relatives (age 37.6 ± 16.3 years, 54% female) were enrolled. Previous cardiac symptoms were present in 69% of cardiac arrest patients compared to 43% of family members (P = 0.001). Prior syncope was present in 26% of cardiac arrest patients, compared to 22% of family members (P = 0.59). Twenty-four of 25 cardiac arrest patients who completed the syncope questionnaires had a syncope versus seizure score <1 favoring syncope. The area under the receiver operator curve (ROC) for the syncope mechanism score was 0.79 for identifying patients with subsequent cardiac arrest (95% CI, 0.6328-0.9395, P = 0.004). A score of ≤-2 had a sensitivity of 68% and specificity of 85%. Thirty percent of patients with a proven genetic cause had preceding syncope versus 19% in patients with noninherited or idiopathic causes (P = 0.032). CONCLUSIONS: Syncope that may represent a sentinel event is present in a modest proportion of patients and family members, and is often suggestive of an arrhythmia.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".