Renal Hyperfiltration and the Development of Microalbuminuria in Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to examine prospectively whether renal hyperfiltration is associated with the development of microalbuminuria in patients with type 1 diabetes, after taking into account known risk factors. RESEARCH DESIGN AND METHODS: The study group comprised 426 participants with normoalbuminuria from the First Joslin Kidney Study, followed for 15 years. Glomerular filtration rate was estimated by serum cystatin C, and hyperfiltration was defined as exceeding the 97.5th percentile of the sex-specific distribution of a similarly aged, nondiabetic population (134 and 149 ml/min per 1.73 m(2) for men and women, respectively). The outcome was time to microalbuminuria development (multiple albumin excretion rate >30 microg/min). Hazard ratios (HRs) for microalbuminuria were calculated at 5, 10, and 15 years. RESULTS: Renal hyperfiltration was present in 24% of the study group and did not increase the risk of developing microalbuminuria. The unadjusted HR for microalbuminuria comparing those with and without hyperfiltration at baseline was 0.8 (95% CI 0.4-1.7) during the first 5 years, 1.0 (0.6-1.7) during the first 10 years, and 0.8 (0.5-1.4) during 15 years of follow-up. The model adjusted for baseline known risk factors including A1C, age at diagnosis of diabetes, diabetes duration, and cigarette smoking resulted in similar HRs. In addition, incorporating changes in hyperfiltration status during follow-up had minimal impact on the HRs for microalbuminuria. CONCLUSIONS: Renal hyperfiltration does not have an impact on the development of microalbuminuria in type 1 diabetes during 5, 10, or 15 years of follow-up.
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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 | 0.000 |
| 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".