Tubular Injury and Cell-Cycle Arrest Biomarkers To Predict Acute Kidney Injury in Noncritically Ill Children Receiving Aminoglycosides
Bibliographic record
Abstract
Aim: NGAL, IL-18, KIM-1 as well as urinary TIMP2 and IGFBP7 and their mathematical product (TIMP2*IGFBP7) were evaluated for detecting pediatric aminoglycoside acute kidney injury (AG-AKI). Methods: In a prospective study, noncritically ill children received aminoglycosides (AG) ≥3 days. The area under the curve (AUC) for biomarkers to detect AKI was calculated by a) days before AKI onset; b) treatment days. Results: There were 113 AG episodes (68% febrile neutropenia). The AKI group had a higher proportion with febrile neutropenia. The AKI group had significantly lower NGAL 3 days before AKI, as patients with febrile neutropenia had a lower NGAL during AG treatment (p < 0.05). NGAL, IL-18 and TIMP2*IGFBP7 had AUC ≥0.73 at 3, 2 and 2 days before AKI onset. Conclusion: NGAL, IL-18 and TIMP2*IGFBP7 were modest early biomarkers of AG-AKI. Febrile neutropenia was associated with lower NGAL.
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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 | 0.003 |
| 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 | 0.000 | 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".