P28 Pharmacokinetics and implications for drug dosing in children with sickle cell disease: a systematic review
Bibliographic record
Abstract
Background Children with sickle cell disease (SCD) are at high risk of intractable pain and severe infections despite early and aggressive drug treatment. SCD is a multisystemic disease potentially leading to liver and renal dysfunction. Altogether, those may lead to pharmacokinetic (PK) alterations, which may contribute to therapeutic failure or drug toxicity. We performed a systematic literature review to describe the current evidence on the effect of SCD on drug disposition in children. Methods A systematic literature search was conducted by a librarian on 5 databases until 08.2018 and independently assessed by two reviewers. All full-text articles, containing PK data in children, were included. The reported differences in PK parameters between SCD and non-SCD children were examined. Results Among 4213 retrieved abstracts, 50 full-text articles were assessed and 27 studies were included (13 exclusively children). Data on 15 drugs was available from which 5 were exclusively developed for SCD (impeding any comparison). From the remaining 10 drugs, a comparison of PK parameters was available in 8. Six were investigated in adults and children. Three (37.5%) showed significant PK alterations (morphine, cefotaxime,lidocaine) while 5 did not (hydroxyurea, sulfadoxine-pyrimethamine, methadone, rofecoxib,arginine butyrate). In children with SCD, clearance was higher by 42–61% for IV morphine, and by 24–62% for cefotaxime, compared with non-SCD controls. This difference led to a new dosing recommendation only for cefotaxime (400 mg/kg/day). Hepatic drug metabolism assessed by lidocaine was impaired in children with SCD compared to healthy controls. Conclusion SCD alters drug disposition of commonly used drugs but data is scarce. A significant increase in clearance of morphine and cefotaxime, two commonly used drugs in patients with SCD, suggests that recommended doses may not be sufficient to provide adequate analgesia and antimicrobial control. PK data is urgently needed to ensure adequate drug efficacy and safety in this high-risk population. References Dong M, McGann PT, Mizuno T, et al. Development of a pharmacokinetic-guided dose individualization strategy for hydroxyurea treatment in children with sickle cell anaemia. Brit J Clin Pharmacol. 2016;81:742–52. Gremse DA, et al. Hepatic function as assessed by lidocaine metabolism in sickle cell disease. J Pediatr 1998;132:989–93. Dampier CD, et al. Intravenous morphine pharmacokinetics in pediatric patients with sickle cell disease. J Pediatr 1995;126:461–7. Kopecky EA, et al. Systemic exposure to morphine and the risk of acute chest syndrome in sickle cell disease. Clin Pharmacol Ther 2004;75:140–6. Maksoud E, et al. Population Pharmacokinetics of Cefotaxime and Dosage Recommendations in Children with Sickle Cell Disease. Antimicrob Agents Chemother. 2018;62: e00637–1. Disclosure(s) Nothing to disclose
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".