Reduced incidence of acute myocardial infarction in the first year after implementation of a public smoking ban in Graubuenden, Switzerland
Bibliographic record
Abstract
OBJECTIVE: On March 1st, 2008 a smoking ban in public buildings became effective in the Canton of Graubuenden, Switzerland. The aim of our study was to investigate, whether implementation of this new regulation was followed by a decrease in the incidence of acute myocardial infarction (AMI). PATIENTS AND METHODS: The Kantonsspital Graubuenden serves as a tertiary care hospital, possessing the only cardiac catheterization laboratory in the Canton of Graubuenden. Based on an excellent functioning network including all hospitals in the Canton of Graubuenden, virtually all patients experiencing an AMI in the Canton of Graubuenden are transferred to our hospital for either acute or early coronary angiography. Data of all patients with AMI undergoing coronary angiography at our hospital between March 1st, 2008 and February 28th, 2009 were collected prospectively. The data were then compared with those of the two corresponding 12-month periods preceding implementation of the public smoking ban. RESULTS: In the two years before adoption of smoke-free legislation, the number of patients with AMI was 229 and 242, respectively (p = ns). In the 12 months after implementation of the public smoking ban, the number of AMI patients dropped to 183 (p <0.05 vs. each of the previous 12-month periods), representing an overall 22% reduction in the AMI incidence within the first year after enactment of the new regulation. This reduction was driven by a significant decrease in the AMI incidence in men, nonsmokers, and individuals with established coronary artery disease, including those with prior AMI or prior percutaneous coronary intervention. CONCLUSIONS: Similar to other countries in Europe and various regions of the USA and Canada, implementation of a public smoking ban was followed by a significant early decline in the incidence of AMI in the Canton of Graubuenden, Switzerland.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".