Trends in death attributed to myocardial infarction, heart failure and pulmonary embolism in Europe and Canada over the last decade
Bibliographic record
Abstract
BACKGROUND: Worldwide, cardiovascular diseases and cancer account for ∼40% of deaths. Certain reports have shown a progressive decrease in mortality. Our main objective was to assess mortality trends related to myocardial infarction (MI), heart failure (HF) and pulmonary embolism (PE). METHODS: MI, HF and PE were studied as cause of death based on the analysis of death certificates in Canada (C), England and Wales (E), France (F) and Sweden (S). We also used a multiple cause approach. Age-standardized death rates (SDR) were calculated. RESULTS: The SDR for MI, HF or PE as the underlying cause of death, all decreased during the last decade. The decrease in SDR secondary to MI exceeded that for HF or PE. Concerning multiple cause of death, a greater decrease was also found for MI, compared with HF or PE. CONCLUSIONS: We confirm the beneficial trends in SDR with MI, HF or PE both as underlying or multiple causes in the studied countries. For HF and PE, multiple cause approach seems more accurate to describe the burden of these two pathologies. Our study also suggests that more efforts should be dedicated to HF and PE in order to achieve similar trends than in MI.
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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 | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".