Optimization of Dosage Regimen of Meropenem in Patients Undergoing Venoarterial Extracorporeal Membrane Oxygenation: A Prospective Cohort Study

Patients receiving venoarterial extracorporeal membrane oxygenation (VA ECMO) therapy often require antibiotics to prevent and treat infections. Our objective was to determine an optimal dosage regimen of meropenem in patients receiving VA ECMO by developing a population pharmacokinetic model. Methods This was a prospective cohort study. Blood samples were collected during ECMO (ECMO-ON) and after ECMO (ECMO-OFF). The population pharmacokinetic model was developed using nonlinear mixed-effects modelling. A Monte Carlo simulation was used (n=10,000) to assess the probability of target attainment. Thirteen adult patients on ECMO receiving meropenem were included. Meropenem pharmacokinetics was best tted by a two-compartment model. Covariate analysis indicated that continuous renal replacement therapy (CRRT) was negatively correlated with clearance (CL). The nal pharmacokinetic model was: CL (L/h) = 3.79 × 0.44 CRRT ; where use of CRRT = 1, no CRRT = 0, central volume of distribution (L) = 2.4, peripheral volume of distribution (L) = 8.56, and intercompartmental clearance (L/h) = 21.3. According to the simulation results, 1–2 g q8h intravenous administration over 20 min was sucient in patients without CRRT for both susceptible (minimum inhibitory concentration (MIC) = 2 mg/L) and resistant (MIC = 8 mg/L) pathogens, regardless of ECMO use (40% fT>MIC target). However, if more aggressive treatment is needed (100% fT>MIC target), dose increment or extended infusion is recommended. We established a population pharmacokinetic model for meropenem in patients receiving VA ECMO and suggested an optimal dosage regimen. These results should improve treatment success and survival in VA ECMO patients. Renal (MDRD) study equation or patients on was performed in the NONMEM program to assess statistical signicance between the nested models. A decrease in the OFV of at least 3.84 was judged statistically signicant for an added parameter (P value < 0.05, χ2 distribution, degree of freedom = 1). For visual inspection, the goodness-of-t plot was expressed as the observed concentrations vs. population predictions (PRED) or individual predictions (IPRED), and conditional weighted residuals (CWRES) vs. PRED. or incremental dosing was appropriate. These results can help provide a clinically appropriate dosage regimen for meropenem in patients receiving both VA ECMO and CRRT.


Abstract Background
Patients receiving venoarterial extracorporeal membrane oxygenation (VA ECMO) therapy often require antibiotics to prevent and treat infections. Our objective was to determine an optimal dosage regimen of meropenem in patients receiving VA ECMO by developing a population pharmacokinetic model.

Methods
This was a prospective cohort study. Blood samples were collected during ECMO (ECMO-ON) and after ECMO (ECMO-OFF). The population pharmacokinetic model was developed using nonlinear mixed-effects modelling. A Monte Carlo simulation was used (n=10,000) to assess the probability of target attainment.

Results
Thirteen adult patients on ECMO receiving meropenem were included. Meropenem pharmacokinetics was best tted by a two-

Conclusions
We established a population pharmacokinetic model for meropenem in patients receiving VA ECMO and suggested an optimal dosage regimen. These results should improve treatment success and survival in VA ECMO patients.
Clinicaltrials.gov registration # NCT02581280 Background Venoarterial extracorporeal membrane oxygenation (VA ECMO) provides mechanical circulatory support for patients with cardiopulmonary failure. [1] There have been exponential increases in ECMO use and survival rates since 2009. [2][3][4] However, infection is still a common complication during ECMO because it requires use of percutaneously inserted devices with large-diameter catheters, and critically ill patients themselves are generally vulnerable to infection. [4,5] Consequently, broad-spectrum antibiotics such as meropenem are needed to prevent and treat infections in patients receiving ECMO support. [4,6] It is well known that VA ECMO affects the pharmacokinetics (PK) of several drugs, [7][8][9] altering their volume of distribution (Vd) and clearance (CL) because of inherent physiological changes associated with ECMO and critical illness. [10][11][12][13][14] Non-pulsatile blood ow from VA ECMO reduces glomerular ltration rate and consequently reduces the CL of drugs. [15] Patients with profound cardiogenic Several clinical studies recommend therapeutic drug monitoring to ensure 100% fT > MIC for beta-lactams in critically ill patients. [25][26][27] Other reports have suggested that PK targets maintain plasma beta-lactam concentrations of more than 4 times the MIC (fT > 4×MIC) for optimal treatment of severe infections. [28,29] Meropenem is an important antibiotic agent that can successfully treat infections during ECMO therapy, but the factors affecting PK changes and optimal dosage regimen for meropenem in patients during ECMO are still inconclusive. There have been recent investigations using population PK analysis that have dosage recommendations for meropenem in patients receiving ECMO. [30,31] However, PK changes are expected to differ depending on the type of ECMO, and these previous studies evaluated data from a mixed patient population treated with VA and venovenous (VV) ECMO. Moreover, they did not directly compare patients receiving ECMO with patients who were weaned off of ECMO.
Thus, the present study aimed to describe the PK pro les of meropenem by comparing patients receiving VA ECMO with patients after ECMO treatment. In addition, optimal dosage regimens were determined according to individual characteristics by simulating various dosing scenarios in patients on both VA ECMO and continuous renal replacement therapy (CRRT).

Ethics and study design
This prospective cohort study was conducted from May 2016 to January 2019 in the cardiac intensive care unit of Severance Hospital in Seoul, South Korea. The study was approved by the Severance Hospital Institutional Review Board (approval number: 4-2014-0919) and conducted in accordance with the principles of the Declaration of Helsinki and national and institutional standards and was registered at Clinicaltrials.gov (NCT02581280). Written informed consent was obtained from the unconscious participants' legally acceptable representatives.

Patients and treatments
Adult patients (≥ 18 years) receiving VA ECMO and concomitantly receiving meropenem were included in this study. Patients who were allergic to carbapenem, pregnant, or taking any medication that may have altered plasma meropenem concentrations were excluded. Patients with normal kidney function received 1 g meropenem q8h as an intravenous injection over 20 min as per protocol.
Patients with an estimated glomerular ltration rate (eGFR) of less than 30 mL/min/1.73 m 2 , as calculated by the Modi cation of Diet in Renal Disease (MDRD) study equation or patients on CRRT received 1 g meropenem q12h.

Data collection
Data associated with demographics, renal and hepatic functions, blood chemistry, vital signs, blood cell counts, and details of ECMO and CRRT were collected. As allowed by the clinical situation, blood samples were collected during ECMO (ECMO-ON group) through the existing radial arterial line at the following times: pre-dose (0 min); 0.5, 1, 3, and 6 h after meropenem administration; and immediately before the next dose according to administration frequency (8 h or 12 h). If the patients were administered meropenem after them weaning off of ECMO (ECMO-OFF group), blood samples were collected at the aforementioned times. The actual sampling time was recorded. The blood samples were collected in EDTA-coated tubes and immediately centrifuged (1,500 ×g at 4°C for 10 min). The plasma samples were stored at -80°C until analysis.

Meropenem assay
Meropenem concentrations were measured using liquid chromatography-mass spectrometry (LC-MS, Ultimate 3000 RS-Q-Exactive Orbitrap Plus; Thermo Fisher Scienti c, Waltham, MA, USA) in the Yonsei Center for Research Facilities. The plasma samples were deproteinized using acetonitrile with sulfamethoxine as an internal standard. The mixture was vortexed for 10 sec and then centrifuged (10 min at 10,000 g), and the supernatant was ltered using a 0.45-µm syringe lter. LC-MS was performed on an Acquity UPLC BEH C18 column (1.7 µm, 2.1 mm × 100 mm; Waters, MA, USA) with a column temperature of 40°C and a ow rate of 0.4 mL/min. The mobile phase was comprised of solvent A (0.1% formic acid in water) and solvent B (100% acetonitrile) with the following elution gradient maintained at 90% A for 4 min, reduced to 5% A over 10 min, maintained at 5% A for 1 min, increased to 90% A over 0.5 min, and maintained at 90% A for 1.5 min. The lower limit of quanti cation was 0.1 mg/L. The inter-and intra-assay coe cients of variation were < 15%.
The plasma concentration-time pro les for meropenem were tted to one-, two-, or three-compartment models using the rst-order conditional estimation method with the interaction estimation option. Interindividual variability (IIV) of PK parameters was evaluated using an exponential variance model assumed a log-normal distribution. Residual unexplained variability (RUV) was tested using an additive, exponential, and combined random error model. The model was selected based on a minimum objective function value (OFV), validity of the estimated relative standard error (RSE), shrinkage of PK parameters, and visual inspection of the goodness-of-t plot. The likelihood ratio test was performed in the NONMEM program to assess statistical signi cance between the nested models. A decrease in the OFV of at least 3.84 was judged statistically signi cant for an added parameter (P value < 0.05, χ2 distribution, degree of freedom = 1). For visual inspection, the goodness-of-t plot was expressed as the observed concentrations vs. population predictions (PRED) or individual predictions (IPRED), and conditional weighted residuals (CWRES) vs. PRED.

Covariate screening
To evaluate the in uence of covariates on the meropenem PK parameters, the following potential covariates were tested: demographic variables (sex, age, weight, and height), ECMO-associated variables (during ECMO or weaned off of ECMO and ECMO ow rate [LPM, litres per minute]), CRRT-associated variables (use of CRRT, blood ow rate, CRRT 6 h prior to urine output, dialysate ow rate), complete blood count (absolute white blood cells, red blood cells, haemoglobin, and platelets), renal function (serum creatinine [SCr], blood urea nitrogen [BUN], creatinine clearance (CrCL) estimated via the Cockcroft-Gault equation, and eGFR estimated via the MDRD equation), liver function (alanine transaminase, aspartate aminotransferase, and total bilirubin), biomarkers of in ammation (C-reactive protein and procalcitonin), blood pressure, tympanic body temperature, and social variables (smoking status and alcohol consumption). In addition, to re ect the inherent correlation with patient status and improvement in critical illness between the ECMO-ON and ECMO-OFF groups, we tested time since ECMO initiation and ECMO termination as individual covariate.
Most data were tested as time-varying covariates, except xed variables, such as sex, age, and smoking status, which were considered time-independent.
Covariates were evaluated using linear, exponential, power, and proportional models based on the stepwise covariate modelling (SCM) process. If needed, the continuous covariates were centred on their median values. For forward selection, a P value < 0.05 (OFV reduction of > 3.84) and for backward elimination, a P < 0.01 (OFV increase of > 6.64) were considered to measure signi cance. The nal covariate model selection was based on biological or clinical plausibility, RSE, shrinkage of PK parameters, a condition number of < 1,000, and visual improvement in the goodness-of-t plot.

Model validation
To evaluate the precision and robustness of the nal PK model, an automated sampling importance resampling (SIR) algorithm (sampling = 5,000, resampling = 1,000, ve iterations) and a prediction-corrected visual predictive check (pcVPC) were carried out using the Perl Speaks NONMEM toolkit version 4.9.0. [32,33] The medians with 95% con dence intervals for the replicates from the SIR algorithm were compared with the estimated PK parameters from the nal model. Furthermore, the simulated pcVPC results with the 5th percentile, median, and 95th percentile curves were visually assessed.

Simulations
Monte Carlo simulations were performed using the estimated PK parameters to assess the effect of the screened covariates on the predicted meropenem concentrations (n = 10,000). Intravenous intermittent infusion (II) over 20 min and intravenous extended infusion (EI) over 3 h and 6 h were simulated by the following dosage regimens: 1 g q12h, 2 g q12h, 0.5 g q8h, 1 g q8h, and 2 g q8h over a 24-h period since the rst meropenem administration. In addition, intravenous continuous infusion (CI) over 8 h (q8h) of 0.5, 1, and 2 g were simulated. The % fT > MIC was determined for each simulated subject by linear interpolation. The PTA was calculated by counting subjects achieving more than 40% fT > MIC and 100% fT > MIC; the dosage scenario that achieved PTA above 90% was considered to be e cient. The MIC, the clinical breakpoint for meropenem, that was used was 2 mg/L for susceptible strains and 8 mg/L for resistant strains according to EUCAST (ver. 10.0, valid from 2020-01-01).

Patients and treatments
Thirteen patients were included in our study, and eleven of them received VA ECMO because of acute myocardial infarction (MI). Five patients received CRRT concomitantly among the six patients in the ECMO-ON group; two patients received CRRT among the nine patients in the ECMO-OFF group. Two patients were sampled repeatedly based on their ECMO status. The median values of age, weight, SCr, and APACHE II score were 55 years, 65.8 kg, 1.2 mg/dL, and 30, respectively, at the initiation of ECMO. The median value of eGFR was 70.4 mL/min/1.73 m 2 , and the eGFR of all patients not receiving CRRT was above 30 mL/min/1.73 m 2 ( Table 1).

Population PK analysis
The time pro le of meropenem plasma concentrations was best tted by a two-compartment model with IIV on CL and peripheral volume of distribution (V2). The RUV was best explained by an exponential error model. After stepwise selection, use of CRRT for CL was included in the nal PK model; the CL of the patients receiving CRRT was lower than that of the patients not receiving CRRT (ΔOFV = 16.8, condition number = 164.5). As covariates, the use of ECMO and the time since ECMO initiation and ECMO termination were not selected by the SCM process because they were not shown to be statistically signi cant and did not improve the goodnessof-t of the model. The CrCL and eGFR were not selected for the same reason. The nal PK model is described as follows. where V1 is the central volume of distribution and Q is the intercompartmental clearance.
The values of CL from Eq. (1) were 3.79 L/h and 1.67 L/h in patients with CRRT and without CRRT, respectively. The parameter estimates and SIR results with 95% con dence intervals are presented in Table 3. All ETA shrinkage values were < 40% in the nal model. All parameters had acceptable RSE values, except for the IIV of V2. The goodness-of-t plots are shown in Additional le 1.
Both population and individual predictions were distributed uniformly across the line of equality. The plots of CWRES vs. PRED did not show any trends. The pcVPC plot showed that approximately 10% of the observed data was positioned outside of the 5th to 95th percentiles of the predicted data, which suggested that the predictive performance of the nal model was adequate (Fig. 1).

Simulations
The nal PK model was used for the Monte Carlo simulation (n = 10,000), and the simulated PTA vs. MIC pro les for various dosage scenarios are shown in Additional le 2. Almost all dosage scenarios were su cient to achieve a PTA above 90% at 40% fT > MIC regardless of the administration frequency, route (II, EI, or CI), pathogen susceptibility, and use of CRRT. Target PTAs could be more readily achieved with EI or CI than with II; when comparing EI over 3 h with EI over 6 h, there was little noticeable difference in achieving target PTAs. However, when more aggressive treatment was needed (i.e., PTA above 90% at 100% fT > MIC), achieving the target PTA was di cult in the simulated scenarios using II.
The recommended dosage regimens are shown in Table 3. Whether on ECMO or not, the standard doses of meropenem in patients with normal kidney function (1-2 g q8h II) and those in patients receiving CRRT (1 g q12h II or 0.5 g q8h II) were su cient to cover both susceptible (MIC = 2 mg/L) and resistant (MIC = 8 mg/L) pathogens. Moreover, lower doses (0.5 g q8h for patients with normal kidney function and 0.5 g q8h for patients during CRRT) can also be recommended via EI or CI. If more aggressive treatment is needed, EI or CI is generally recommended. In patients not receiving CRRT, 2 g q8h EI over 6 h or CI is recommended against resistant pathogens. When the patients receiving CRRT require aggressive treatment against resistant pathogens, the minimum recommended dose is 1 g q8h EI or 0.5-1 g q8h CI.

Discussion
This prospective cohort study was designed to develop a population PK model for meropenem in patients receiving VA ECMO, and to explore the appropriate dosage regimen of meropenem by analysing the probability of target attainment using Monte Carlo simulations. In our nal PK model, a two-compartment model best t the time course of plasma meropenem concentrations. This study revealed that the use of ECMO did not have a signi cant impact on the PK of meropenem. Meanwhile, meropenem CL was 0.44 times lower in patients with CRRT than in patients without CRRT (kidney function > 30 mL/min/1.73 m 2 ); however, the contributing factors related to CRRT did not help improve the nal PK model. As the result of PTA assessment, the standard dose of meropenem was deemed su cient to cover both susceptible and resistant pathogens in patients receiving CRRT (1 g q12h II or 0.5 g q8h II) or in patients with preserved renal function (1-2 g q8h II) regardless of ECMO. However, if aggressive treatment was needed, EI over 3-6 h or CI instead of II, or incremental dosing was appropriate. These results can help provide a clinically appropriate dosage regimen for meropenem in patients receiving both VA ECMO and CRRT.
In our study, CL decreased in patients receiving CRRT regardless of VA ECMO treatment. Meropenem is reported to be excreted mainly by the kidneys, and renal function indices such as eGFR estimated by the MDRD Study equation and CrCL estimated via the Cockcroft-Gault equation were also found to have a positive relationship with meropenem CL. [30,31] We assessed the relationship between renal function and meropenem CL in the univariate analysis among non-CRRT patients. However, renal function indices were excluded as covariates because they did not improve robustness of the PK model, which differed from CRRT added to CL as a covariate. This result may be explained by the small number of patients enrolled in the present study and the fact that almost all included patients without CRRT had eGFR > 30 mL/min/1.73 m 2 . In our nal PK model, eGFR was not selected as a covariate; however, this does not indicate that dose adjustments according to estimated renal function are not required.
No covariates, including the use of VA ECMO, affected the Vd of meropenem in our PK model. Patients undergoing VA ECMO generally need vigorous volume support, including resuscitation uid and transfusion, owing to the initial circuit priming volume and their haemodynamic instability. [34] This could lead to increased circulating volume, but meropenem is relatively hydrophilic; it has low protein binding a nity [35] and its sequestration on the ECMO surface may not be high. Because of these properties, VA ECMO may have little effect on the Vd of meropenem despite the larger circulating volume. Other investigators have also reported similar results, in that the use of ECMO did not in uence the Vd of meropenem. [30,31] Moreover, our ndings showed that VA ECMO did not signi cantly alter the PK of meropenem, consistent with the results of previous PK studies in patients receiving meropenem during both VA and VV ECMO. [30,31,36] A recent review suggested that the PK change in ECMO patients was more re ective of critical illness than the ECMO device. [17] Therefore, the PK changes observed for meropenem might be affected not by ECMO use but by critical illness, which includes renal and hepatic hypoperfusion, hypoxia, and systemic in ammation; thus, therapeutic drug monitoring is recommended. [7,17] In our study, the current standard dosage recommendation was still effective, but EI or CI provided better PTA, and either infusion is recommended when aggressive treatment is needed. The clinical bene ts of prolonged administration of beta-lactams, which display time-dependent activity, have previously been shown. [37][38][39][40] One issue in the prolonged administration of meropenem is time-and temperature-dependent degradation. [41][42][43] However, data from several studies have suggested that > 90% meropenem remains in vitro after 5-6 h at room temperature, [41,43] and recent evidence suggests that meropenem degradation during CI is insigni cant at the end of a 12-h dosing interval at room temperature.
[44] Therefore, we suggest that EI over 3 h or 6 h would be better than CI if the PK/PD target were to be attained, since meropenem stability during infusion would not be a concern.
To the best of our knowledge, this study is the rst to investigate the PK changes in meropenem by comparing patients during VA ECMO with those weaned off of VA ECMO and to suggest the optimal dosage of meropenem according to various scenarios between ECMO and CVVHDF as CRRT. However, this study was limited by the relatively small sample size, and therefore, the data may not have provided robust PK parameter estimates. We attempted to use the ECMO-OFF group as a control to directly compare the effects on ECMO and reduce IIV between the control and intervention groups. However, only two patients could be included in both the ECMO-ON and ECMO-OFF groups because meropenem is not a rst-line antibiotic according to our hospital protocol. Finally, our PK model was restricted to patients receiving VA ECMO and CVVHDF as CRRT, which is merely one mode of ECMO and CRRT. Therefore, the applicability of our results to all modes of ECMO is limited.

Conclusion
In conclusion, we established a population PK model for meropenem in patients receiving ECMO. Moreover, we suggest optimized dosage regimens to provide adequate bactericidal activity. The standard dosage regimen (1-2 g q8h II) was su cient to treat both susceptible and resistant pathogens. If more aggressive therapy is needed, a dose increment or EI over 3-6 h is recommended. These ndings will contribute to the successful treatment of infections with meropenem in patients receiving VA ECMO by providing proper dosage regimens.

Declarations
Ethics approval and consent to participate The study was approved by the Severance Hospital Institutional Review Board (approval number: 4-2014-0919) and was registered at Clinicaltrials.gov (NCT02581280). Written informed consent was obtained from the unconscious participants' legally acceptable representatives.

Consent for publication
Written informed consent was obtained from the participants' legal representatives for publication of their individual details in this manuscript. The consent form is held by the authors' institution and is available for review by the Editor.

Availability of data and materials
The datasets generated and/or analysed during the current study are not publicly available due to privacy concerns and institutional policy but are available from the corresponding author on reasonable request.

Competing interests
We have no con ict of interest to declare. Authors' contributions SK, JW, and MJC designed the study, performed the population PK analysis, interpreted the results of the analysis, and draft the manuscript. JW and MJC supervised the design, conducted the study, and revised the manuscript. SK, SY, JH, JYJ, and KLM collected the blood sample and patient data. SY assisted technical PK modelling and reviewed the manuscript. All authors read and approved the nal manuscript.