Implications of serum creatinine measurements on GFR estimation and vancomycin dosing in children
Bibliographic record
Abstract
BACKGROUND: Different serum creatinine (sCr) assays may obtain different values in the same patient, causing discrepancies in estimated glomerular filtration rate (eGFR) and sCr-based vancomycin dosing calculations. OBJECTIVE: To identify potential discrepancies in sCr concentrations obtained by different assays, the compensated Jaffe (sCr-Jaffe) and the enzymatic (sCr-enz), and to compare between the eGFR and vancomycin daily dose, based on these sCr values. METHOD: sCr-Jaffe and, sCr-enz concentrations of 890 healthy children, aged 1-18 years, were available from the Canadian Laboratory Initiative in Pediatric Reference Intervals study in Ontario. For each subject, eGFR (eGFR-Jaffe, eGFR-enz) was calculated using the revised Schwartz equation, and vancomycin daily dose (Vdose-Jaffe, Vdose-enz) was calculated using a sCr-based pharmacokinetic model. RESULT: Significant, age-related differences were found in sCr concentrations, and in subsequent eGFR and Vdose, between the two assays. In children aged 1-5 years, mean sCr-Jaffe was higher than sCr-enz (44.0 ± 5.0 vs. 27.7 ± 7.3 μmol/L, P < 0.001), leading to lower eGFR-Jaffe (83.2 ± 9.0 vs. 137.9 ± 27.1 mL/min/1.73m2, P < 0.001) and lower Vdose-Jaffe (44.7 ± 2.5 vs. 53.5 ± 5.1 mg/kg/24 h, P < 0.001). CONCLUSION: Based on these findings, young children may be at risk for vancomycin under-treatment. Further research is needed to define the more accurate sCr assay in young children treated with renally excreted drugs.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".