Changes in Albuminuria Predict Mortality and Morbidity in Patients with Vascular Disease
Bibliographic record
Abstract
The degree of albuminuria predicts cardiovascular and renal outcomes, but it is not known whether changes in albuminuria also predict similar outcomes. In two multicenter, multinational, prospective observational studies, a central laboratory measured albuminuria in 23,480 patients with vascular disease or high-risk diabetes. We quantified the association between a greater than or equal to twofold change in albuminuria in spot urine from baseline to 2 years and the incidence of cardiovascular and renal outcomes and all-cause mortality during the subsequent 32 months. A greater than or equal to twofold increase in albuminuria from baseline to 2 years, observed in 28%, associated with nearly 50% higher mortality (HR 1.48; 95% CI 1.32 to 1.66), and a greater than or equal to twofold decrease in albuminuria, observed in 21%, associated with 15% lower mortality (HR 0.85; 95% CI 0.74 to 0.98) compared with those with lesser changes in albuminuria, after adjustment for baseline albuminuria, BP, and other potential confounders. Increases in albuminuria also significantly associated with cardiovascular death, composite cardiovascular outcomes (cardiovascular death, myocardial infarction, stroke, and hospitalization for heart failure), and renal outcomes including dialysis or doubling of serum creatinine (adjusted HR 1.40; 95% CI 1.11 to 1.78). In conclusion, in patients with vascular disease, changes in albuminuria predict mortality and cardiovascular and renal outcomes, independent of baseline albuminuria. This suggests that monitoring albuminuria is a useful strategy to help predict cardiovascular risk.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".