Microalbuminuria and the Risk for Early Progressive Renal Function Decline in Type 1 Diabetes
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Bibliographic record
Abstract
This study aimed to establish the time of initiation and the determinants of renal function decline in type 1 diabetes. Until now, such decline has been assumed to be a late-occurring event associated with proteinuria. A total of 267 patients with normoalbuminuria and 301 patients with microalbuminuria were followed for 8 to 12 yr. Linear trends (slopes) in GFR were estimated by serial measurement of serum cystatin C. Cases of early renal function decline were defined by loss in cystatin C GFR that exceeded -3.3%/yr, a threshold that corresponds to the 2.5th percentile of the distribution of GFR slopes in an independent nondiabetic normotensive population. Cases of early renal function decline occurred in 9% (mean slope -4.4; range -5.9 to -3.3%/yr) of the normoalbuminuria group and 31% (mean slope -7.1; range -23.8 to -3.3%/yr) of the microalbuminuria group (P < 0.001). Risk for early renal function decline depended on whether microalbuminuria regressed, remained stable, or progressed, rising from 16 to 32 and 68%, respectively (P < 0.001). In multivariate analysis, risk for decline was higher after age 35 yr or when glycosylated hemoglobin exceeded 9% but did not vary with diabetes duration, smoking, BP, or angiotensin-converting enzyme inhibitor treatment. Contrary to the existing paradigm of diabetic nephropathy, progressive renal function decline in type 1 diabetes is an early event that occurs in a large proportion of patients with microalbuminuria. Together with testing for microalbuminuria, clinical protocols using cystatin C to diagnose early renal function decline and track response to therapeutic interventions should be developed.
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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 | 0.000 |
| 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 it