In-hospital Mortality Characteristics of Women With Acute Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease continues to be the leading cause of death in women and men in the United States. This study aimed to investigate differences in characteristics between those women who died and survived an acute myocardial infarction (MI). METHODS: This secondary analysis included 109 women. Demographic variables were extracted along with presenting MI symptoms, cardiovascular risk factors (family history of cardiovascular disease, patient history of cardiovascular disease, diabetes, hypercholesterolemia, hypertension, and smoking history), type of MI, time of symptom onset and time of presentation to emergency department (ED) for treatment. Descriptive statistics described the sample, t-tests and chi-square analyzed differences between the groups. RESULTS: There was a 12% mortality rate for women experiencing an acute MI. The women who died had a mean age of 79 years, approximately 7 years older than those who survived (P = 0.037). The leading MI presenting symptoms were chest pain and shortness of breath. The mean number of cardiovascular risk factors for those who died were 2.15 compared to 2.75 for those who survived (P = 0.063). The majority of those women who survived had a non ST Elevation MI (94%) compared to 54% with a non ST Elevation MI who died. Median time to ED presentation was 242.5 minutes for those who survived compared to 244 minutes who died (P = 0.951). CONCLUSIONS: These data demonstrate a MI mortality profile of women which included an older age, no family history of heart disease reported, and a high rate of hypertension. Those who died reported chest pain and shortness of breath, with several presenting with a syncopal event. In addition, the women represented in this sample had a prolonged presentation time for treatment. KEYWORDS: Myocardial infarction; Gender; Women; Mortality; Cardiovascular risk factors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".