Explaining trends in Scottish coronary heart disease mortality between 2000 and 2010 using IMPACTSEC model: retrospective analysis using routine data
Bibliographic record
Abstract
OBJECTIVE: To quantify the contributions of prevention and treatment to the trends in mortality due to coronary heart disease in Scotland. DESIGN: Retrospective analysis using IMPACTSEC, a previously validated policy model, to apportion the recent decline in coronary heart disease mortality to changes in major cardiovascular risk factors and to increases in more than 40 treatments in nine non-overlapping groups of patients. SETTING: Scotland. PARTICIPANTS: All adults aged 25 years or over, stratified by sex, age group, and fifths of Scottish Index of Multiple Deprivation. MAIN OUTCOME MEASURE: Deaths prevented or postponed. RESULTS: 5770 fewer deaths from coronary heart disease occurred in 2010 than would be expected if the 2000 mortality rates had persisted (8042 rather than 13,813). This reflected a 43% fall in coronary heart disease mortality rates (from 262 to 148 deaths per 100,000). Improved treatments accounted for approximately 43% (95% confidence interval 33% to 61%) of the fall in mortality, and this benefit was evenly distributed across deprivation fifths. Notable treatment contributions came from primary prevention for hypercholesterolaemia (13%), secondary prevention drugs (11%), and chronic angina treatments (7%). Risk factor improvements accounted for approximately 39% (28% to 49%) of the fall in mortality (44% in the most deprived fifth compared with only 36% in the most affluent fifth). Reductions in systolic blood pressure contributed more than one third (37%) of the decline in mortality, with no socioeconomic patterning. Smaller contributions came from falls in total cholesterol (9%), smoking (4%), and inactivity (2%). However, increases in obesity and diabetes offset some of these benefits, potentially increasing mortality by 4% and 8% respectively. Diabetes showed strong socioeconomic patterning (12% increase in the most deprived fifth compared with 5% for the most affluent fifth). CONCLUSIONS: Increases in medical treatments accounted for almost half of the large recent decline in mortality due to coronary heart disease in Scotland. Furthermore, the Scottish National Health Service seems to have delivered these benefits equitably. However, the substantial contributions from population falls in blood pressure and other risk factors were diminished by adverse trends in obesity and diabetes. Additional population-wide interventions are urgently needed to reduce coronary heart disease mortality and inequalities in future decades.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".