National trends in rates of death and hospital admissions related to acute myocardial infarction, heart failure and stroke, 1994-2004
Bibliographic record
Abstract
BACKGROUND: Rates of death from cardiovascular and cerebrovascular diseases have been steadily declining over the past few decades. Whether such declines are occurring to a similar degree for common disorders such as acute myocardial infarction, heart failure and stroke is uncertain. We examined recent national trends in mortality and rates of hospital admission for these 3 conditions. METHODS: We analyzed mortality data from Statistic Canada's Canadian Mortality Database and data on hospital admissions from the Canadian Institute for Health Information's Hospital Morbidity Database for the period 1994-2004. We determined age- and sex-standardized rates of death and hospital admissions per 100,000 population aged 20 years and over as well as in-hospital case-fatality rates. RESULTS: The overall age- and sex-standardized rate of death from cardiovascular disease in Canada declined 30.0%, from 360.6 per 100,000 in 1994 to 252.5 per 100 000 in 2004. During the same period, the rate fell 38.1% for acute myocardial infarction, 23.5% for heart failure and 28.2% for stroke, with improvements observed across most age and sex groups. The age- and sex-standardized rate of hospital admissions decreased 27.6% for stroke and 27.2% for heart failure. The rate for acute myocardial infarction fell only 9.2%. In contrast, the relative decline in the in-hospital case-fatality rate was greatest for acute myocardial infarction (33.1%; p < 0.001). Much smaller relative improvements in case-fatality rates were noted for heart failure (8.1%) and stroke (8.9%). INTERPRETATION: The rates of death and hospital admissions for acute myocardial infarction, heart failure and stroke in Canada changed at different rates over the 10-year study period. Awareness of these trends may guide future efforts for health promotion and health care planning and help to determine priorities for research and treatment.
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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 | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".