Pathogenesis of Sudden Unexpected Death in a Clinical Trial of Patients With Myocardial Infarction and Left Ventricular Dysfunction, Heart Failure, or Both
Bibliographic record
Abstract
BACKGROUND: The frequency of sudden unexpected death is highest in the early post-myocardial infarction (MI) period; nevertheless, 2 recent trials showed no improvement in mortality with early placement of an implantable cardioverter-defibrillator after MI. METHODS AND RESULTS: To better understand the pathophysiological events that lead to sudden death after MI, we assessed autopsy records in a series of cases classified as sudden death events in patients from the VALsartan In Acute myocardial infarctioN Trial (VALIANT). Autopsy records were available in 398 cases (14% of deaths). We determined that 105 patients had clinical circumstances consistent with sudden death. On the basis of the autopsy findings, we assessed the probable cause of sudden death and evaluated how these causes varied with time after MI. Of 105 deaths considered sudden on clinical grounds, autopsy suggested the following causes: 3 index MIs in the first 7 days (2.9%); 28 recurrent MIs (26.6%); 13 cardiac ruptures (12.4%); 4 pump failures (3.8%); 2 other cardiovascular causes (stroke or pulmonary embolism; 1.9%); and 1 noncardiovascular cause (1%). Fifty-four cases (51.4%) had no acute specific autopsy evidence other than the index MI and were thus presumed arrhythmic. The percentage of sudden death due to recurrent MI or rupture was highest in the first month after the index MI. By contrast, after 3 months, the percentage of presumed arrhythmic death was higher than recurrent MI or rupture (chi(2)=23.3, P<0.0001). CONCLUSIONS: Recurrent MI or cardiac rupture accounts for a high proportion of sudden death in the early period after acute MI, whereas arrhythmic death may be more likely subsequently. These findings may help explain the lack of benefit of early implantable cardioverter-defibrillator therapy.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".