Trends in peripheral arterial disease incidence and mortality in EU15+ countries 1990–2017
Bibliographic record
Abstract
AIMS: The aim was to assess trends in peripheral arterial disease (PAD) incidence and mortality rates in European Union(15+) countries between 1990 and 2017. METHODS AND RESULTS: This observational study used data obtained from the 2017 Global Burden of Disease study. Age-standardised mortality and incidence rates from PAD were extracted from the Global Health Data Exchange for EU15+ countries for the years 1990-2017. Trends were analysed using Joinpoint regression analysis.Between 1990 and 2017, the incidence of PAD decreased in all 19 EU15+ countries for females, and in 18 of 19 countries for males. Increasing PAD incidence was observed only for males in the United States (+1.4%). In 2017, the highest incidence rates were observed in Denmark and the United States for males (213.6 and 202.3 per 100,000, respectively) and in the United States and Canada for females (194.8 and 171.1 per 100,000, respectively). There was a concomitant overall trend for increasing age-standardised mortality rates in all EU15+ countries for females, and in 16 of 19 EU15+ countries for males between 1990 and 2017. Italy (-25.1%), Portugal (-1.9%) and Sweden (-0.6%) were the only countries with reducing PAD mortality rates in males. The largest increases in mortality rates were observed in the United Kingdom (males +140.4%, females +158.0%) and the United States (males +125.7%, females +131.2%). CONCLUSIONS: We identify shifting burden of PAD in EU15+ countries, with increasing mortality rates despite reducing incidence. Strong evidence supports goal-directed medical therapy in reducing PAD mortality - population-wide strategies to improve compliance to optimal goal-directed medical therapy are warranted.
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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 | 0.002 | 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".