Renal Outcomes in Patients with Type 1 Diabetes and Macroalbuminuria
Bibliographic record
Abstract
Macroalbuminuria, defined as urine albumin excretion rate (AER)≥300 mg/d, has long been considered a stage of irreversible kidney damage that leads reliably to GFR loss. We examined the long-term renal outcomes of persons with type 1 diabetes who developed incident macroalbuminuria during the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study. One hundred fifty-nine participants developed incident macroalbuminuria and were subsequently followed for a median duration of 9 years (maximum of 25 years). At the time of macroalbuminuria diagnosis, mean (SD) age was 37 (9) years, mean (SD) duration of diabetes was 17 (5) years, median AER was 524 mg/d, and mean (SD) eGFR was 108 (20) ml/min per 1.73 m(2). Ten years after macroalbuminuria diagnosis, the cumulative incidence of a sustained reduction in AER to <300 mg/d was 52%, mostly but not entirely under treatment with renin-angiotensin system inhibitors. The cumulative incidence of impaired GFR (sustained eGFR<60 ml/min per 1.73 m(2)) 10 years after macroalbuminuria diagnosis was 32%, including 16% who developed ESRD. Lower hemoglobin A1c and BP and regression to AER<300 mg/d were associated with reduced risk of developing impaired GFR. In conclusion, people with type 1 diabetes who develop macroalbuminuria are at high risk of progressive kidney disease. However, through at least 10 years of follow-up, AER could often be controlled, and GFR frequently remained in the normal range.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".