Implementation and validation of a Bayesian method for accurately forecasting duration of optimal pharmacodynamic target attainment with dalbavancin during long-term use for subacute and chronic staphylococcal infections
Jazyk angličtina Země Nizozemsko Médium print-electronic
Typ dokumentu časopisecké články
PubMed
37981075
DOI
10.1016/j.ijantimicag.2023.107038
PII: S0924-8579(23)00327-8
Knihovny.cz E-zdroje
- Klíčová slova
- Bayesian prediction, MwPharm, TDM, dalbavancin,
- MeSH
- antibakteriální látky * terapeutické užití farmakologie MeSH
- Bayesova věta MeSH
- lidé MeSH
- mikrobiální testy citlivosti MeSH
- stafylokokové infekce * farmakoterapie MeSH
- Staphylococcus MeSH
- teikoplanin terapeutické užití farmakologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- antibakteriální látky * MeSH
- dalbavancin MeSH Prohlížeč
- teikoplanin MeSH
Dalbavancin is increasingly being used for long-term treatment of subacute and chronic staphylococcal infections. In this study, a new Bayesian model was implemented and validated using MwPharm software for accurately forecasting the duration of pharmacodynamic target attainment above the efficacy thresholds of 4.02 mg/L or 8.04 mg/L against staphylococci. Forecasting accuracy improved substantially with the a posteriori approach compared with the a priori approach, particularly when two measured concentrations were used. This strategy may help clinicians to estimate the duration of optimal exposure with dalbavancin in the context of long-term treatment.
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