Is Routine Therapeutic Drug Monitoring of Anti-Retroviral Agents Warranted in Children Living with HIV?
Bibliographic record
Abstract
OBJECTIVE: The utility of routine therapeutic drug monitoring (TDM) in children living with HIV has not been extensively studied. The purpose of this study was to assess this strategy. METHODS: This was a single-center, prospective observational study of routine TDM for protease inhibitors (PIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), and integrase strand transfer inhibitors (INSTIs) in children living with HIV who were receiving antiretroviral therapy (ART) between February and December 2014. Outcome measures included the proportion of serum antiretroviral (ARV) medication concentrations in the therapeutic range (target values extrapolated from adult data) and the effect of serum concentrations on virologic control, medication adherence, and toxicity. RESULTS: Forty-eight children with a median age of 13 years (interquartile range, 3-18) were included. Median viral load (VL) and CD4% were <40 copies/mL (range, <40-124) and 37.4% (range, 8.4-47.9), respectively. Adherence was considered excellent in 95.8% of patients. Of the 50 serum trough concentrations (PI n = 19 [38%]; NNRTI n = 27 [54%]; INSTI n = 4 [8%]), 66% (n = 33) were in the therapeutic range, 12% (n = 6) were subtherapeutic, and 22% (n = 11) were supratherapeutic. There was no statistically significant correlation between serum ARV concentrations and patient demographics, VL, CD4%, or adherence. No clinically significant adverse events were noted. One dose adjustment was made for a subtherapeutic serum raltegravir concentration, likely attributable to interaction with ritonavir. CONCLUSIONS: This study does not support routine TDM in healthy children living with HIV who are well controlled on antiretroviral medication regimens. A more targeted strategy, such as when adherence is questioned or when there are suspected drug interactions, may be more appropriate.
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 | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".