Abstract 4373276: Global Trends in Ischemic Heart Disease Attributable to Kidney Dysfunction: A 204-Country Analysis of Mortality and Disability from 1990 to 2021
Bibliographic record
Abstract
Background: Kidney dysfunction is an under-recognized yet growing contributor to ischemic heart disease (IHD) burden worldwide. As chronic kidney disease (CKD) prevalence rises globally, its cardiovascular sequelae—especially IHD—pose serious challenges to health systems, particularly in low- and middle-income regions. Understanding the long-term burden of IHD attributable to kidney dysfunction is essential for informing global health priorities and integrated disease management strategies. Methods: We analyzed trends in mortality and disability attributable to IHD due to kidney dysfunction across 204 countries and territories from 1990 to 2021 utilizing global burden of disease study 2021 framework. Age-standardized mortality rates (ASMR), Years Lived with Disability (YLDs), and Disability-Adjusted Life Years (DALYs) were extracted. Annualized Percentage Change (APC) was calculated for each measure, and results were stratified by geography, age group, and Socio-Demographic Index (SDI) region. Results: Globally, the APC in ASMR due to IHD attributable to kidney dysfunction ranged from +1.47% in Madagascar to −5.04% in Australia between 1990 and 2021. Sub-Saharan African nations such as Nigeria (+1.24%) and Central African Republic (+1.10%) experienced significant increases, whereas countries like Canada (−3.26%) and Germany (−2.79%) showed notable declines. For YLDs, the APC ranged from +1.18% in Nigeria to −1.56% in Australia, with upward trends clustered in West Africa, South Asia, and parts of Southeast Asia. Age-specific trends revealed a substantial rise in total deaths from 2,420 in the 25–29 age group in 1990 to 14,866 in the 70–74 age group in 2021. DALYs showed similar growth, with 8,890 DALYs in the 40–44 age group in 1990 increasing to 52,189 in the 70–74 age group by 2021. YLDs also increased from 2,756 in the 30–34 age group in 1990 to 9,683 in the 70–74 age group in 2021, indicating an expanding burden of non-fatal disease across aging populations. Conclusion: From 1990 to 2021, mortality and disability due to IHD attributable to kidney dysfunction declined in many high-income countries but increased sharply in Sub-Saharan Africa and parts of Asia. With some countries experiencing APCs exceeding +1% annually, targeted interventions to manage renal risk factors and integrated care models for IHD and CKD are urgently needed, particularly in low-SDI settings facing rising disease burdens.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.006 |
| 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) | 0.002 | 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".