Early nephropathy in type 1 diabetes: the importance of early renal function decline
Bibliographic record
Abstract
PURPOSE OF REVIEW: The results of recent clinical trials in early diabetic nephropathy demonstrate that current therapies designed to suppress microalbuminuria do not prevent renal function decline. However, recent observational studies refined the traditional model of early nephropathy in type 1 diabetes and may inform more effective therapies for the prevention of chronic kidney disease. RECENT FINDINGS: A contemporary model of early nephropathy in type 1 diabetes has emerged in which initiation of renal function decline occurs soon after the onset of microalbuminuria and is not conditional on progression to proteinuria. Early renal function decline can be diagnosed using serial measurement of serum cystatin C. Abnormal levels of markers of protein glycation, uric acid metabolism, and chronic inflammation appear to represent mechanisms unique to early renal function decline and distinct from those involved in microalbuminuria. SUMMARY: Recent findings refine the existing paradigm of early nephropathy in type 1 diabetes and have significant implications for research. Clinical tests--such as an algorithm for the serial determination of serum cystatin C--should be developed for monitoring early renal function decline for use as an outcome in clinical trials.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".