ObjectiveTo establish the population pharmacokinetics (PPK) of magnesium sulfate (MgSO4)in women with preeclampsia (PE), and to determine the key covariates having an effect in magnesium pharmacokinetics in Chinese PE.MethodsPregnant women with PE prescribed MgSO4 were enrolled in this prospective study from April 2021 to April 2023. On the initial day of administration, the patients were administered a loading dose of 5 g in conjunction with 10 g of magnesium sulfate as a maintenance dose. On the second day, only the maintenance dose was administration, and maternal blood samples were taken at 0, 4, 5, and 12 h after the second day’s 10 g maintenance dose. The software Phoenix was used to estimate PPK parameters of MgSO4, such as clearance (CL) and volume of distribution (V), and to model PPK models with patient demographic, clinical, and laboratory covariates.ResultsA total of 199 blood samples were collected from 51 women with PE and PPK profiles were analyzed. The PPK of MgSO4 is consistent with to a one-compartment model. The base model adequately described the maternal serum magnesium concentrations after magnesium administration. The population parameter estimates were as follows: CL was 2.98 L/h, V was 25.07 L. The model predictions changed significantly with covariates (BMI, creatinine clearance, and furosemide). Furosemide statistically influences V. The creatinine clearance, BMI and furosemide jointly affects CL. Monte Carlo simulation results showed that a loading dose combined with a maintenance dose would need to be administered daily to achieve the therapeutic blood magnesium concentrations. For the non-furosemide group, the optimal dosing regimen was a 5 g loading dose combined with a 10 g maintenance dose of MgSO4. For the furosemide group, the optimal dosing regimen was a 2.5 g loading dose combined with a 10 g maintenance dose of MgSO4.ConclusionsThe magnesium PPK model was successfully developed and evaluated in Chinese preeclampsia population, and the dose optimization of MgSO4 was completed through Monte Carlo simulation.
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