An observational analysis of trends in rheumatic heart disease incidence and mortality in EU15+ countries over 29 years
Bibliographic record
Abstract
Abstract Background Rheumatic heart disease (RHD) is a debilitating sequela of acute rheumatic fever (ARF), caused by Group A streptococcus (GAS) infection. Repeated episodes of ARF results in valvular damage over time. As a preventable disorder which was once common worldwide, RHD has largely been eradicated in affluent nations due to widespread availability of penicillin, improvement in socioeconomic standards and advancements in health and social infrastructures. However, it has been speculated that the global refugee crisis, especially in Europe, might contribute to a resurgence of RHD cases in these regions. Purpose This observational study aimed to analyse trends in RHD incidence and mortality rates in European Union 15+ (EU15+) over a 29-year period. Methods Data was obtained from the Global Burden of Disease database. Age-standardised mortality and incidence rates for RHD were extracted for the EU15+ countries for the years 1990–2019. Trends were subsequently analysed using Joinpoint regression analysis. Results Over the 29-year period, an overall declining trend in RHD incidence and mortality across EU 15+ nations was observed. The United Kingdom demonstrated the largest decrease in RHD incidence amongst females (−54.9%) and Finland amongst males (−55.3%). Both RHD incidence and mortality were higher among females compared to males across EU15+ countries over the observed period. The most recent incidence trends, starting predominantly after 2014, demonstrated a rise in RHD incidence in most countries. For both sexes, increases were seen in Australia, Belgium, Ireland, Italy, Netherlands, Norway, Sweden and USA. For males specifically, increase in RHD incidence was seen in Spain, and Finland, and for females only in Canada and Ireland. The recent increasing RHD incidence rates ranged from +0.4% to + 24.7% for males and +0.6% to +11.4% for females. Conclusion Whilst overall there are decreases in incidence and mortality from RHD, we observe more than half of EU15+ countries have increasing incidence trends in RHD in recent years. This increasing trend primarily started after 2014, overlapping with the start of the European migration crisis. Although speculative, disparities in access to healthcare for migrants, amongst other socioeconomic factors, may be potential causes; subsequently, further efforts by governments and public health officials are required to recognise and control the resurgence of RHD in high income nations. Funding Acknowledgement Type of funding sources: None.
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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 | 0.001 | 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 | 0.000 |
| 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".