Study On Population Pharmacokinetics Of Meropenem In Patients With Severe Infection

Patients with severe infections often cause decreased immune function due to their physiological and pathological characteristics and repeated chemotherapy.This can easily lead to serious consequences.Failure to timely and appropriate antibacterial therapy is an important risk factor for the death of critically ill patients.Meropenem,a novel carbapenem antibiotic,has a wide range of antibacterial properties and can be used to treat a variety of different infections,and it is more commonly used in critically ill patients.The aim of this study was to collect blood drug concentration monitoring data from hospitalized patients in the clinical department of meropenem and various physiological,pathological and biochemical indicators of patients,to establish a population pharmacokinetics(PPK)model,and analyze meropenem in critically ill patients.The influencing factors of pharmacokinetics in vivo provide the best individual administration of meropenem to reduce the occurrence of drug resistance,then providing guidance for clinical individualized drug delivery.Objective: 1.Establish a stable pharmacokinetic model of meropenem in clinically critically ill patients 2.To study the pharmacokinetics of meropenem in critically ill patients,to verify its stability,and to analyze and evaluate the influencing factors of meropenem in vivoMethods: 1.Establish a high-performance liquid Chromatography(HPLC)method for the treatment of critically ill patients with high-performance liquid Chromatography(HPLC)to determine blood drug concentration data in critically ill patients.2.This study collected 48 clinical inpatients from the First Affiliated Hospital of Bengbu Medical College from October 2017 to October 2018.The clinical blood concentration test data after meropenem(total blood collection point of 220)was nonlinear mixed effect.The model(NLME)method was used to establish a population pharmacokinetic model.This study collected data on patient history and investigated the body weight,sex,age,dose,creatinine,urea nitrogen,white blood cell count,platelet count,hemoglobin,combined medication,etc.for meropenem clearance(CL)and apparent volume of distribution in critically ill patients.)Impact.3.Visually predictive check(VPC)and bootstrap(Bootstrap)verification for the established population model.By resampling the original data set,forming a virtual data set,and then validating the model with virtual data,it is repeated several times to obtain the stability of the model by comparing the parameters of the multiple bootstrap model with the parameter values of the final model.Results: In this HPLC method,meropenem and internal standard metronidazole are well separated and do not interfere with each other.The standard curve equation of meropenem was obtained by regression calculation: y=0.0151x-0.0123(R2=0.9992),meropenem has a good linear relationship between 5 ~200.0 ?g/ml,and meropenem at low,medium and high concentrations.The intra-day and inter-day precision are less than 14.34%;the accuracy is between 96.92% and 103.39%,and it has good stability after being placed at 4 ? for 24 hours and at-80 ? for 2 months.This method is accurate and reliable.The final model of meropenem PPK based on 220 blood concentration points and physiological and biochemical data of 48 patients was: CL=tv CL *CLCRd CLd CLCR *exp(?CL)V=tv V*CLCRd Vd CLCR *exp(?V);final model of meropenem clearance Typical value of the rate(CL): 6.00 L / h,typical volume of apparent distribution(V): 18.04LConclusions: 1.The high-performance liquid chromatography of meropenem blood concentration established in this study is simple and effective,and can accurately determine blood drug concentration,which can be used to monitor the blood concentration of meropenem.2.This study established the meropenem PPK model in patients with severe infections.The results showed that creatinine clearance was the main influencing factor for meropenem clearance and apparent volume of distribution in critically ill patients.The results of the validation show that the model is stable and effective,and has certain predictive ability.In the future,it will provide guidance for the meropenem drug regimen for patients with severe clinical infection.