β-Trace Protein, Cystatin C, β2-Microglobulin, and Creatinine Compared for Detecting Impaired Glomerular Filtration Rates in Children
Bibliographic record
Abstract
BACKGROUND: Because of the limitations of serum creatinine as a marker of glomerular filtration rate (GFR) in children, we assessed the diagnostic accuracy of the novel marker beta-trace protein (BTP) in comparison with cystatin C (Cys-C), beta(2)-microglobulin (beta(2)-MG), and creatinine as conventional indicators of reduced GFR. METHODS: We obtained serum samples from 225 children (age range, 0.2-18 years) with various renal pathologies who were referred for nuclear medicine clearance investigations (technetium-diethylenetriamine pentaacetic acid or chromium-EDTA). We measured Cys-C, BTP (nephelometric tests; Dade Behring), beta(2)-MG (Tinaquant; Roche), and creatinine (enzymatic assay; Creatinine-PAP; Roche). RESULTS: Seventy-five children had reduced GFR (<90 mL x min(-1) x 1.73 m(-2)). One hundred fifty children (independent of gender and age) with values >90 mL x min(-1) x 1.73 m(-2) comprised the control group with gaussian distributions of BTP and Cys-C concentrations. The upper reference limits (97.5 percentile) were 1.01 mg/L for BTP and 1.20 mg/L for Cys-C. The correlations of nuclear medicine clearance with the reciprocals of BTP, Cys-C, and the Schwartz GFR estimate were significantly higher (r = 0.653, 0.765, and 0.706, respectively; P <0.05) than with the reciprocal of creatinine or beta(2)-MG (r = 0.500 and 0.557, respectively). ROC analysis showed a significantly higher diagnostic accuracy of BTP, Cys-C, and the GFR estimate for the detection of impaired GFR than serum creatinine (P <0.05). Compared to creatinine, BTP increased the diagnostic sensitivity by approximately 30%, but it was not more sensitive than Cys-C or the Schwartz GFR estimate. CONCLUSIONS: BTP is superior to serum creatinine and an alternative for Cys-C to detect mildly reduced GFR in children, but it is not better than the Schwartz GFR estimate.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".