Population pharmacokinetic model of subcutaneous fentanyl in older acute care patients
Autor: | Rami Tadros, Lorraine Mackenzie, Michael D. Wiese, Patrick Russell, Craig Phillips, Aymen Ali Al-Qurain, Richard N. Upton, Michael S. Roberts, Desmond B. Williams |
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Přispěvatelé: | Al-Qurain, Aymen A, Upton, Richard, Williams, Desmond B, Mackenzie, Lorraine, Phillips, Craig, Russell, Patrick T, Tadros, Rami, Roberts, Michael S, Wiese, Michael D |
Rok vydání: | 2021 |
Předmět: |
Population
subcutaneous injection Cmax Context (language use) frailty fentanyl 030226 pharmacology & pharmacy Fentanyl 03 medical and health sciences Subcutaneous injection 0302 clinical medicine Pharmacokinetics Medicine Pharmacology (medical) 030212 general & internal medicine education Pharmacology Volume of distribution education.field_of_study Subcutaneous Absorption business.industry General Medicine older patients Anesthesia population pharmacokinetic business medicine.drug |
Zdroj: | European Journal of Clinical Pharmacology. 77:1357-1368 |
ISSN: | 1432-1041 0031-6970 |
Popis: | Purpose Subcutaneous fentanyl injection is commonly prescribed to manage acute pain in older patients; however, there is a gap in the literature describing the pharmacokinetic parameters for this route of administration in this population. The aim of this study was to develop and evaluate a population pharmacokinetic model for subcutaneous fentanyl injection in older patients. Methods Twenty-one patients who received subcutaneous fentanyl injections (50 to 75 mu g) were recruited. Fentanyl concentrations were determined using a validated liquid chromatography/tandem mass spectrometry method. A population pharmacokinetic model was developed using non-linear mixed-effects modelling. A base model was selected based on the Akaike information criterion. Age, sex, body weight, number of previous fentanyl doses, number of prescribed medications, creatinine clearance, Charlson Comorbidity Index, Identification of Seniors at Risk score and concurrent use of CYP3A4 inhibitors were covariates considered for inclusion. A p value of < 0.05 was considered statistically significant for inclusion of covariates in the final model by stepwise addition. The simulation performance of the model was assessed by visual predictive check. Results A one-compartment, first-order absorption with lag time and linear elimination model was the best to fit to the fentanyl concentration data. The absorption rate constant was 0.136 h(-1) (between subject variability (BSV), 46%), lag time 0.66 h (BSV 51%), apparent volume of distribution 6.28 L (BSV 30%), and apparent clearance 16.3 L.h(-1) (BSV 54%). The Charlson Comorbidity Index was the only covariate included in the final model, where a higher value of the index increased fentanyl exposure and C-max. Conclusion This is the first report of subcutaneous fentanyl population pharmacokinetic model to evaluate fentanyl pharmacokinetic in older patients. The between subject variability in clearance and subcutaneous absorption rate was relatively high, and some patients recorded high fentanyl concentrations in the context of their titration to effect. Refereed/Peer-reviewed |
Databáze: | OpenAIRE |
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