The Association Between Subclinical Reductions in Kidney Function and Major Adverse Cardiovascular Events in Young Adults: A Population-Based Retrospective Cohort Study
Bibliographic record
Abstract
Background: Cardiovascular risk factors and disease in young adults (18-39 years) are on the rise. Whether early reductions in kidney function (i.e., estimated glomerular filtration rate [eGFR] above the current accepted threshold for chronic kidney disease [>60 mL/min/1.73m2], but below age-expected values) are associated with elevated risk is unknown. We aim to examine age-specific associations of subclinical eGFR reductions in young adults with major adverse cardiovascular events (MACE). Methods: We conducted a retrospective cohort study of 8.7 million individuals (3.6 million aged 18-39 years) using linked provincial healthcare datasets from Ontario, Canada from January 2008-March 2021. Cox models examined the association of categorized eGFR (50-120 mL/min/1.73m2) with MACE (first of cardiovascular mortality, acute coronary syndrome, ischemic stroke) and MACE-plus-heart failure (MACE+), stratified by age (18-39, 40-49, 50-65 years). Results: In our cohort (mean age 41.3, mean eGFR 104.2, median follow-up 9.2 years), a stepwise increase in the relative risk of MACE and MACE+ was observed as early as eGFR<90 in young adults (e.g., for MACE, at eGFR 70-80, ages 18-30: 2.37 events per 1000 person-years(p-y), HR 1.31(1.27-1.40); ages 40-49: 6.26/1000p-y, HR 1.09(1.06-1.12); ages 50-65: 14.9/1000p-y, HR 1.07(1.05-1.08)). Elevations in relative risk occurred for 18-39-year-olds at higher eGFR levels than ages 40-49 and 50-65. This persisted when examining each component individually and in additional analyses (stratified by past CV disease, accounting for index albuminuria, defining index eGFR from repeated measures). Conclusions: In young adults, eGFR levels above the current threshold for chronic kidney disease associated with an elevated risk for MACE and MACE+, warranting ageappropriate risk stratification, proactive monitoring, and timely intervention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".