Abstract 18555: Global Burden of Congenital Heart Disease and Its Trend From 1990-2019 in 38 OECD Countries: A Benchmarking Analysis for the Global Burden of Disease Study
Bibliographic record
Abstract
Introduction: Congenital heart disease (CHD) is the 1st leading cause of deaths among all deaths associated with congenital birth defects in (Organization for Economic Cooperation and Development) OECD countries, constituting a significant health concern that imposes a substantial burden on healthcare systems and society. Methods: Using the Global Burden of Disease methodology, this study assesses the prevalence, incidence, mortality, and disability-adjusted life years (DALYs) associated with CHD in 38 OECD countries by sex, year, and location, covering the period from 1990 to 2019. The results are presented in both all age counts and age standardized rates (ASR) per 100,000 person-years. Results: From 1990 to 2019, the total number of prevalent cases of CHD increased from 1,469,128 (95%UI: 1,292,909-1,671,743) to 1,590,654 (1,387,114-1,815,338). In contrast, CHD-related deaths decreased from 37,291 (31,629-47,869) in 1990 to 13,886 (10,668-16,919) in 2019. The annual percentage of change (APC) in age-standardized mortality (ASMR) decreased by 60%, while the ASIR showed almost no change but decreased by 3%. Notably, the highest APC in ASIR was observed in Czechia (27%), Sweden (21%), Hungary (18%), and the United States (11%), while Turkey (28%) and Canada (21%) had the lowest APC increases. The highest APC increase in ASIR among females was observed in France (29%) Conclusions: Despite a decrease in the burden of CHD over the last three decades, it remains a significant concern in OECD countries. The impact of CHD is felt by individuals, families, healthcare systems, and the economy, emphasizing the ongoing need for comprehensive strategies to address this burden.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| 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) | 0.002 | 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".