TY - JOUR
T1 - Factors Affecting Vancomycin Trough Concentration; a Population Pharmacokinetic Model in Non-Critical Care Saudi Patients
AU - Alqurain, Aymen Ali
AU - Alrashidi, Laila Nasser
AU - Aloraifej, Shatha Khalid
AU - Alkhalifah, Moayd
AU - Alsayed, Hawra Ali
AU - Abohelaika, Salah
AU - Alshabeeb, Mohammad A.
AU - Aldhafeeri, Amal Shibak
AU - Almuslim, Moyad
AU - Bumozah, Thuraya Nasser
AU - Alomar, Mukhtar Jawad
AU - Alshehab, Azhar Abdullah
AU - Alamer, Ahmed Abdulwahab
AU - Al-Matouq, Jenan
AU - Bidasee, Keshore R.
AU - Alomar, Fadhel A.
N1 - Publisher Copyright:
© 2024 Alqurain et al.
PY - 2024
Y1 - 2024
N2 - Background and Objective: Vancomycin is commonly prescribed in treatment of methicillin-resistant Staphylococcus aureus infections. While, vancomycins’ pharmacokinetic vary among older patients, there is a paucity of data regarding specific characteristics influencing pharmacokinetics in Saudi adult patients. This study aims to establish a population-pharmacokinetic (Pop-PK) model for vancomycin in patients admitted to medical wards, with the focus on identification of patient characteristics influencing vancomycin trough concentrations. Methods: A multicenter retrospective study was conducted involving patients aged ≥40 years admitted to medical wards in the Eastern Province, Saudi Arabia and initiated on vancomycin, between January to December 2022. Non-linear mixed-effects modelling (Monolix) was employed to develop the Pop-PK model. A base model was selected based on the Akaike information criterion. Covariates considered included age, sex, body weight, C-reactive protein (CRP), serum creatinine, creatinine clearance (CrCl), and albumin levels. 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 plot. The final model was simulated using Simulx software to assess the effect of the included covariates on vancomycin trough concentration. Results: A total of 172 vancomycin trough concentrations from 124 patients were analyzed. The final Pop-PK model characterized vancomycin trough concentrations was one compartment distribution with linear elimination. CrCl and CRP were the only covariates included in the final model, as they reduced the between-subject variability (BSV) for clearance (from 173% to 81%). The simulated model demonstrated that high CRP value and low CrCl contributed to increased vancomycin trough concentrations. Conclusion: This study highlights large BSV in trough concentrations among patients and emphasizes the influencing of CrCl and CRP on vancomycin pharmacokinetics in medical care settings.
AB - Background and Objective: Vancomycin is commonly prescribed in treatment of methicillin-resistant Staphylococcus aureus infections. While, vancomycins’ pharmacokinetic vary among older patients, there is a paucity of data regarding specific characteristics influencing pharmacokinetics in Saudi adult patients. This study aims to establish a population-pharmacokinetic (Pop-PK) model for vancomycin in patients admitted to medical wards, with the focus on identification of patient characteristics influencing vancomycin trough concentrations. Methods: A multicenter retrospective study was conducted involving patients aged ≥40 years admitted to medical wards in the Eastern Province, Saudi Arabia and initiated on vancomycin, between January to December 2022. Non-linear mixed-effects modelling (Monolix) was employed to develop the Pop-PK model. A base model was selected based on the Akaike information criterion. Covariates considered included age, sex, body weight, C-reactive protein (CRP), serum creatinine, creatinine clearance (CrCl), and albumin levels. 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 plot. The final model was simulated using Simulx software to assess the effect of the included covariates on vancomycin trough concentration. Results: A total of 172 vancomycin trough concentrations from 124 patients were analyzed. The final Pop-PK model characterized vancomycin trough concentrations was one compartment distribution with linear elimination. CrCl and CRP were the only covariates included in the final model, as they reduced the between-subject variability (BSV) for clearance (from 173% to 81%). The simulated model demonstrated that high CRP value and low CrCl contributed to increased vancomycin trough concentrations. Conclusion: This study highlights large BSV in trough concentrations among patients and emphasizes the influencing of CrCl and CRP on vancomycin pharmacokinetics in medical care settings.
KW - C-reactive protein
KW - creatinine clearance
KW - medical care patients
KW - population pharmacokinetics
KW - vancomycin trough concentration
UR - https://www.scopus.com/pages/publications/85213445164
U2 - 10.2147/DDDT.S496512
DO - 10.2147/DDDT.S496512
M3 - Article
C2 - 39722680
AN - SCOPUS:85213445164
SN - 1177-8881
VL - 18
SP - 6185
EP - 6198
JO - Drug Design, Development and Therapy
JF - Drug Design, Development and Therapy
ER -