Mortality from abdominal aortic aneurysm: trends in European Union 15+ countries from 1990 to 2017
Bibliographic record
Abstract
BACKGROUND: This observational study assessed trends in abdominal aortic aneurysm (AAA) death rates in European Union (EU) 15+ countries for the years 1990 to 2017. METHODS: Age-standardized death rates (ASDRs) were extracted from the Global Burden of Disease Study Global Health Data Exchange. Trends were analysed using joinpoint regression analysis. RESULTS: Between 1990 and 2017, ASDRs from AAA decreased in all 19 EU15+ countries for women, and in 18 of 19 countries for men. Increasing AAA mortality was observed only for men in Greece (+5·3 per cent). The largest relative decreases in ASDR between 1990 and 2017 were observed in Australia (men -65·6 per cent, women -50·4 per cent) and Canada (men -60·8 per cent, women -48·6 per cent). Over the 28-year interval, the smallest decreases in ASDR for women were noted in Greece (-2·3 per cent) and in Italy (-2·5 per cent). In 2017, the highest mortality rates were observed in the UK for both men and women (7·5 per 100 000 and 3·7 per 100 000 respectively). The lowest ASDR was observed in Portugal for men (2·8 per 100 000) and in Spain for women (1·0 per 100 000). ASDRs for AAA in 2017 were higher for men than women in all 19 EU15+ countries. The most recent trends demonstrated increasing AAA ASDRs in 14 of 19 countries for both sexes; the increases were relatively small compared with the improvements in the preceding years. CONCLUSION: This observational study identified decreasing mortality from AAA across EU15+ countries since 1990. The most recent trends demonstrated relatively small increases in AAA mortality across the majority of EU15+ countries since 2012.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".