Outcome of Apparently Unexplained Cardiac Arrest
Bibliographic record
Abstract
BACKGROUND: The Cardiac Arrest Survivors with Preserved Ejection Fraction Registry (CASPER) enrolls patients with apparently unexplained cardiac arrest and no evident cardiac disease to identify the pathogenesis of cardiac arrest through systematic clinical testing. Exercise testing, drug provocation, advanced cardiac imaging, and genetic testing may be useful when a cause is not apparent. METHODS AND RESULTS: The first 200 survivors of unexplained cardiac arrest from 14 centers across Canada were evaluated to determine the results of investigation and follow-up (age, 48.6±14.7 years, 41% female). Patients were free of evidence of coronary artery disease, left ventricular dysfunction, or evident repolarization syndromes. Advanced testing determined a diagnosis in 34% of patients at baseline, with a diagnosis emerging during follow-up in 7% of patients. Of those who were diagnosed, 28 (35%) had an underlying structural condition and 53 (65%) had a primary electric disease. During a mean follow-up of 3.15±2.34 years, 23% of patients had either a shock or an appropriate antitachycardia pacing from their implantable cardioverter defibrillator, or both. The implantable cardioverter defibrillator appropriate intervention rate was 8.4% at 1 year and 18.1% at 3 years, with no clear difference between diagnosed and undiagnosed subjects, or between those diagnosed with a primary electric versus structural pathogenesis. CONCLUSIONS: Obtaining a diagnosis in previously unexplained cardiac arrest patients requires systematic clinical testing and regular follow-up to unmask the cause. Nearly half of apparently unexplained cardiac arrest patients ultimately received a diagnosis, allowing for improved treatment and family screening. A substantial proportion of patients received appropriate implantable cardioverter defibrillator therapy during medium-term follow-up. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00292032.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".