MétaCan
Menu
Back to cohort
Record W4415424009 · doi:10.1093/ndt/gfaf116.2004

#2846 Comparison of three different amikacin guidelines for pediatric patients: virtual population insight

2025· article· en· W4415424009 on OpenAlexaff
Rasha Hussein, Felix J. Meigel, Ana Catalina Alvarez-Elías, Doris H. Fuertinger

Bibliographic record

VenueNephrology Dialysis Transplantation · 2025
Typearticle
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDosingAmikacinTarget rangePopulationTrough ConcentrationNephrotoxicity

Abstract

fetched live from OpenAlex

Abstract Background and Aims Amikacin, a key aminoglycoside for treating severe pediatric infections, requires precise dosing to achieve therapeutic efficacy while minimizing nephrotoxic risks. Effective treatment depends on achieving high peak concentrations (20–80 mg/L) to ensure bacterial eradication and maintaining low trough levels (2.5–5 mg/L) to prevent toxicity. However, dosing guidelines differ across centers and countries, leading to variations in achieving these targets across pediatric populations. We present an in-silico study to compare Amikacin peak and trough levels based on different dosing guidelines. We selected guidelines from France, the United States, and the United Kingdom, representing a diverse range of dosing strategies, with many low- and middle-income countries adopting practices that fall within these ranges. Method An in-silico pharmacokinetic (PK) model, adapted from [1] and validated against clinical data from [2], was used to simulate Amikacin dosing. A virtual pediatric population (N = 1000), accounting for maturational changes in GFR, weight, and height, was generated to match the study population in [5] (median [range] age: 6 months [0.8–89], weight: 6.6 kg [2.8–22], eGFR: 116 mL/min/1.73 m² [48–290]), where eGFR was determined based on serum creatinine using the Schwartz formula. The body surface area was calculated using Mosteller's formula. Simulations in Python evaluated 24-hour dosing regimens over 7 days, following national guidelines from France [3] (dose: 30 mg/kg, peak levels >60 mg/L, and trough levels <2.5 mg/L), Stanford's Lucile Packard Children's Hospital (US) [4] (dose: 15–30 mg/kg, peak levels >20 mg/L, and trough levels <2.5 mg/L), and Sheffield Children's NHS Foundation Trust (UK) [5] (dose: 20 mg/kg, trough levels <5 mg/L). Amikacin dosing was not held when trough levels were not met in simulations. Results Amikacin peak and trough concentrations varied across dosing guidelines (Fig. 1). Median peak levels for 30 mg/kg (French guideline) ranged from 61 to 74 mg/L over the treatment days, while 15 mg/kg (UK and US) produced lower peaks of 24–29 mg/L. The 20 mg/kg dose resulted in intermediate peaks of 42–51 mg/L. Trough levels showed distinct patterns of compliance with the defined thresholds (Table 1). For the stricter <2.5 mg/L threshold, compliance decreased over the 7-day period: 99.5% to 56.6% for 15 mg/kg, 93.5% to 34.8% for 20 mg/kg, and 71.9% to 9.6% for 30 mg/kg. For the UK's less stringent <5 mg/L threshold, compliance remained higher, with 96.3% at Day 7 for 15 mg/kg, 85.6% for 20 mg/kg, and 56.6% for 30 mg/kg. By Day 7, median trough levels for 30 mg/kg exceeded 2.5 mg/L in 90.4% of the population, while 43.4% exceeded 5 mg/L. For 15 mg/kg, 43.4% of the population exceeded 2.5 mg/L, but only 3.7% exceeded 5 mg/L. Conclusion The differences in dosing guidelines result in varying treatment efficacy and nephrotoxic risks, with substantial fractions of the pediatric population not meeting trough targets across all guidelines. Moreover, without adapting the dosing during treatment, trough levels progressively increase. This highlights the need for an improved understanding of Amikacin's nephrotoxic effects in pediatric patients and the development of optimized and harmonized dosing strategies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.037
GPT teacher head0.347
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueNephrology Dialysis TransplantationSame topicAntibiotics Pharmacokinetics and EfficacyFrench-language works237,207