External Evaluation of Two Pediatric Population Pharmacokinetics Models of Oral Trimethoprim and Sulfamethoxazole
Bibliographic record
Abstract
The antibiotic combination trimethoprim (TMP)-sulfamethoxazole (SMX) has a broad spectrum of activity and is used for the treatment of numerous infections, but pediatric pharmacokinetic (PK) data are limited. We previously published population PK (popPK) models of oral TMP-SMX in pediatric patients based on sparse opportunistically collected data (POPS study) (J. Autmizguine, C. Melloni, C. P. Hornik, S. Dallefeld, et al., Antimicrob Agents Chemother 62:e01813-17, 2017, https://doi.org/10.1128/AAC.01813-17). We performed a separate PK study of oral TMP-SMX in infants and children with more-traditional PK sample collection and independently developed new popPK models of TMP-SMX using this external data set. The POPS data set and the external data set were each used to evaluate both popPK models. The external TMP model had a model and error structure identical to those of the POPS TMP model, with typical values for PK parameters within 20%. The external SMX model did not identify the covariates in the POPS SMX model as significant. The external popPK models predicted higher exposures to TMP (median overprediction of 0.13 mg/liter for the POPS data set and 0.061 mg/liter for the external data set) and SMX (median overprediction of 1.7 mg/liter and 0.90 mg/liter) than the POPS TMP (median underprediction of 0.016 mg/liter and 0.39 mg/liter) and SMX (median underprediction of 1.2 mg/liter and 14 mg/liter) models. Nonetheless, both models supported TMP-SMX dose increases in infants and young children for resistant pathogens with a MIC of 1 mg/liter, although the required dose increase based on the external model was lower. (The POPS and external studies have been registered at ClinicalTrials.gov under registration no. NCT01431326 and NCT02475876, respectively.).
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".