Sex and Racial Differences in Autopsy-Defined Causes of Presumed Sudden Cardiac Death
Bibliographic record
Abstract
Background: Sudden cardiac death (SCD) studies report higher incidence in men and Black people but presume cardiac cause. We sought to identify sex and racial differences in rates and causes of presumed SCDs in a prospective postmortem study in San Francisco County. Methods: All incident presumed SCDs meeting the World Health Organization definition ages 18 to 90 were autopsied via active surveillance of consecutive out-of-hospital deaths in the POST SCD study (Postmortem Systematic Investigation of Sudden Cardiac Death; February 1, 2011, to March 1, 2014). Autopsy-defined sudden arrhythmic deaths had no extracardiac cause or acute heart failure. Results: Among 541 presumed SCDs, 525 (97%) were autopsied; 362 (69%) were men, 110 Asian (21%), 81 Black (15%), 40 Hispanic (8%), 279 White (53%), and 15 other race (3%). Adjusted for age and race, women had more noncardiac causes of presumed SCD, including pulmonary emboli (8% versus 2%) and neurological causes (10% versus 3%, both P <0.01). Of autopsy-defined sudden arrhythmic death, men had 3-fold higher rates while women had more primary electrical disease (4% versus 2%; P =0.02) and nonischemic causes (53% versus 39%; P <0.01). Age-adjusted incidence rate ratios were higher for Black women (2.55; P <0.01) and lower for Asian and Hispanic men (0.51 for both; P <0.05) than their White counterparts. Myocardial infarction with nonobstructive coronary arteries was more common among sudden arrhythmic deaths in Asians than Whites (7% versus 1%; adjusted P <0.05). Sudden neurological deaths were more common in Asians, endocrine causes more common in Blacks, and gastrointestinal causes more common in Hispanics than in Whites (adjusted P , all <0.05). Conclusions: In this countywide postmortem study of presumed SCDs, women had more nonischemic and noncardiac causes. Black women had higher rates of autopsy-defined sudden arrhythmic death than White women while Asian and Hispanic men had lower rates than White men. These findings have implications for risk stratification and prevention of sudden mortality in women and minority populations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".