Performance of a dosage individualization table for extended interval gentamicin in neonates beyond the first week of life
Bibliographic record
Abstract
OBJECTIVE: To assess the performance of a gentamicin dosing table for the individualization of extended-interval dosing (EID) in a neonatal population >7 days old. METHODS: A prospective observational study was carried out on gentamicin concentrations achieved using a dosing table in neonates >7 days old. Neonates were given 5 mg/kg IV gentamicin; then a table using 22 h post-first dose gentamicin concentrations was used to individualize dosing intervals. Pre- and post-serum gentamicin concentrations were measured and used to calculate the true peak and trough concentrations achieved. RESULTS: Use of the table resulted in dosing intervals that provided appropriate peak (mean 9.8 ± 1.8 mg/L) and trough (mean 0.6 ± 0.3 mg/L) concentrations in all neonates (n = 38). All trough concentrations were <2 mg/L, 83% were <1 mg/L. The majority of peak concentrations were in the usual target range (87%, 5-12 mg/L), with a few being in a higher, although likely safe range (13%, 12.1-15.7 mg/L). CONCLUSIONS: Use of this dosing table to individualize extended-interval gentamicin dosages in neonates >7 days old resulted in appropriate peak and trough concentrations in all neonates studied. This allows appropriate extended-interval aminoglycoside dosages in neonates early in treatment.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".