Bibliographic record
Abstract
Piperacillin-tazobactam (TZP) is frequently used to treat severe hospital-acquired infections in children. We performed a single-center, pharmacokinetic (PK) trial of TZP in children ranging in age from 2 months to 6 years from various clinical subpopulations. Children who were on TZP per the standard of care were prospectively included and assigned to receive a dose of 80 mg/kg of body weight every 6 h infused over 2 h (ages 2 to 5 months) or a dose of 90 mg/kg every 8 h infused over 4 h (ages 6 months to 6 years). Separate population PK models were developed for piperacillin and tazobactam using nonlinear mixed-effects modeling. Optimal dosing was judged based on the ability to maintain free piperacillin concentrations above the piperacillin MIC for enterobacteria and <i>Pseudomonas aeruginosa</i> for ≥50% of the dosing interval. Any untoward event occurring during treatment was collected as an adverse event. A total of 79 children contributed 174 PK samples. The median (range) age and weight were 1.7 years (2 months to 6 years) and 11.4 kg (3.8 to 27.6 kg), respectively. A 2-compartment model with first-order elimination best described the piperacillin and tazobactam data. Both final population PK models included weight and concomitant furosemide administration on clearance and weight on the volume of distribution of the central compartment. The optimal dosing regimens in children with normal renal function, based on the piperacillin component, were 75 mg/kg/dose every 4 h infused over 0.5 h in infants ages 2 to ≤6 months and 130 mg/kg/dose every 8 h infused over 4 h in children ages >6 months to 6 years against bacteria with MICs up to 16 mg/liter. A total of 44 children (49%) had ≥1 adverse event, with 3 of these (site infiltrations) considered definitely associated with the extended infusions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.127 | 0.004 |
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; both teacher heads agree on what is shown here.
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".