Global Burden of Stroke Attributable to Kidney Dysfunction, 1992-2021: Age-Period-Cohort Analysis and Projected Trends
Bibliographic record
Abstract
ABSTRACT BACKGROUND Kidney dysfunction is an important modifiable risk factor for stroke, yet its attributable global burden remains understudied. This analysis quantifies its impact across demographics and projects future trends. METHODS AND RESULTS Using Global Burden of Disease 2021 data, we analyzed stroke-related deaths and disability-adjusted life years (DALYs) attributable to kidney dysfunction globally, regionally, and nationally, stratified by age, sex, and socio-demographic index (SDI). Trends (1992–2021) were assessed via age-period-cohort (APC) modeling and estimated annual percentage change (EAPC). Contributions of aging, population growth, and epidemiological shifts were quantified through decomposition analysis. Bayesian models projected trends to 2040. Globally, age-standardized mortality rate (ASMR) and age-standardized disability-adjusted life year rate (ASDR) declined (EAPC: −1.85% (95% CI −1.95 to −1.74) and −1.73% (95% CI −1.82 to −1.63)), yet absolute deaths and DALYs rose to 676,000 and 15.009 million in 2021. The burden surged after age 80, disproportionately affecting males and low-SDI regions. Middle-SDI regions showed the steepest declines, while Southern Sub-Saharan Africa experienced rising ASMR and ASDR. Projections suggest continued declines, particularly in females, though disparities persist. CONCLUSIONS Despite global declines, stroke burden attributable to kidney dysfunction remains elevated in older males and low-SDI regions. Targeted interventions addressing kidney health and equitable healthcare access are critical to mitigating disparities and reducing future burden.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".