Urinary Biomarkers in Obstructive Nephropathy
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Obstructive nephropathy is a leading cause of CKD in children. The assessment of severity of renal impairment and the prediction of which children will progress to renal failure are, however, challenging. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This case-control study measured the urinary excretion of candidate biomarkers in 27 prevalent case-patients with posterior urethral valves (PUVs) and 20 age-matched controls, correlated their urinary concentration with GFR, and analyzed receiver-operating characteristic (ROC) curve and regression analyses to assess their performance as tests for low GFR. RESULTS: The median urinary protein-to-creatinine ratio was higher in children with PUV (45 g/mol; range, 5-361 g/mol) than in controls (7 g/mol; range, 3-43 g/mol) (P<0.01) and correlated inversely with renal function (r = -0.44; P<0.05). In whole urine, excretion of aquaporin-2 was significantly decreased, whereas that of TGFβ and L1 cell adhesion molecule (L1CAM) was significantly increased. Whole-urine TGFβ excretion correlated inversely with GFR (r = -0.53; P<0.05). As tests for low GFR, whole-urine TGFβ, L1CAM, and urinary protein-to-creatinine ratio performed best, with areas under the ROC curves of 0.788, 0.795, and 0.814, respectively. By linear regression analysis, whole-urine TGFβ, L1CAM, and urinary protein-to-creatinine ratio were associated with low GFR in the case-patients. CONCLUSIONS: Candidate biomarkers of obstructive nephropathy can be readily measured in whole urine and in urine exosomes. In boys with PUV, these biomarkers correlate with GFR.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".