Cystatin C Does Not Detect Acute Changes in Glomerular Filtration Rate in Early Diabetic Nephropathy
Bibliographic record
Abstract
BACKGROUND: The measurement of renal functional reserve (acute change in glomerular filtration rate [GFR] after protein load) allows the detection of sub-clinical renal dysfunction and has prognostic implications in diabetes. Our aim was to test cystatin C as an index of GFR and renal functional reserve. METHODS: GFR was measured by C(Sinistrin) at baseline and after protein load in 28 diabetic patients with serum creatinine <1.2 mg/dL. The C(Sinistrin) was compared with cystatin C, serum creatinine, creatinine clearance, and Cockcroft-Gault formula. RESULTS: Baseline C(Sinistrin) ranged from 67-172 mL/min. Regression analysis showed an overall low relationship between C(Sinistrin) and the indirect markers of GFR. The highest correlation with C(Sinistrin) was obtained for cystatin C clearance (R(2) = 0.58, r = 0.76, p < 0.001), the 1/serum cystatin C (R(2) = 0.58, r = 0.76, p < 0.001), and serum cystatin C (R(2) = 0.52, r = 0.72, p < 0.001). Renal functional reserve was preserved in 6 of 28 patients. There was no significant change in cystatin C in response to protein load. CONCLUSION: Wide variation in baseline GFR emphasizes the need for the early detection of renal dysfunction. Cystatin C correlated best with C(Sinistrin) at baseline, but did not detect renal functional reserve.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".