This study was approved by the Ethics Committee of Zhongnan Hospital of Wuhan University (No. LYL2019018). Informed consent was obtained from the legal representatives of the patients before enrolment.

Plasma samples were collected from patients who received an intravenous infusion of daptomycin in the intensive care unit (ICU) of Zhongnan Hospital of Wuhan University from April 2021 to December 2022 according to the inclusion and exclusion criteria and the clinical sample sampling protocol for blood drug concentration testing. Patients who fulfilled the following criteria were eligible: ≥18 years old; treated with daptomycin for proven/probable infections caused by Gram-positive organisms that were unresponsive or intolerant to other antimicrobial agents. The exclusion criteria were pregnancy, known or suspected hypersensitivity to daptomycin and its excipients, and incomplete or missing laboratory data before and after treatment.

Demographic and clinical characteristics of the enrolled patients were also collected from the medical records, including age, sex, weight, diagnosis, comorbidities, outcome, combination of other drugs (including antimicrobials), daily complete blood counts, biochemical test results (including liver and renal function and creatinine phosphokinase (CPK)), and whether CRRT or ECMO therapy was performed. In addition, acute physiology and chronic health evaluation (APACHE) and sequential organ failure assessment (SOFA) scores were calculated for each patient to determine disease severity. The patient’s creatinine clearance (CL_CR) was calculated according to the Cockcroft-Gault formula based on serum creatinine at steady state on day 3.

Daptomycin (Jiangsu Hengrui Medicine Co., Ltd.) dissolved in 100 mL normal saline was administered as a 30-min infusion. The daptomycin dose was 500 mg every 24 h. To obtain a complete blood drug concentration time curve after administration, we took into account the equilibrium phase (near peak concentration) and elimination phase of the drug in the design of sampling time points. On the first day of administration, blood samples were collected at 0, 0.5, 1, 2, 4, 8, 12, and 24 h after infusion. On the third day of administration, blood samples were collected before administration and at 0, 0.5, 1, 2, 4, 8, 12, and 24 h after infusion. On the fifth and seventh days, blood samples were collected before administration and at 0.5 and 4 h after infusion. Blood was drawn and allowed to clot in yellow blood-collecting tubes containing separating glue and a coagulant accelerator. Serum was collected by centrifugation and stored at −80°C until assayed. As soon as the study dose was administered, the participants were monitored for potential side effects. Serious adverse events were defined as adverse events related to daptomycin that required treatment discontinuation.

Serum daptomycin concentrations were measured using a high-performance liquid chromatography-tandem mass spectrometry method developed in our laboratory, the lower limit of quantification was 0.05 μg mL⁻¹. Briefly, serum samples were analyzed after protein precipitation. Daptomycin-d5 (Beijing Hager Biotechnology Co., Ltd.) was used as an internal standard. A Waters ACQUITY UPLC C8 column (2.1 mm × 50 mm, 1.7 μm) was used for separation. The mobile phase consisted of phase A: water (0.1% formic acid), phase B: 1:1 methanol: acetonitrile (0.1% formic acid) at a flow rate of 0.4 mL min⁻¹, column temperature of 45°C, injection volume of 2 μL, and analysis time of 4 min. Ion transitions were performed using positive electrospray ionization in the multiple reaction monitoring mode.

Before measurement, the sample was restored to room temperature, 100 μL of 1:1 methanol: acetonitrile was measured into a 1.5 μL EP tube, then 10 μL of daptomycin-d5 with 40 μL of sample/standard/quality control was added, the sample was vortex shaken for 1 min, centrifuged at high speed for 8 min (14,500 r/min), and the supernatant was placed in a 96-well plate for the assay.

NONMEM (version 8.1; ICON Development Solutions, Hanover, MD, United States) was used to establish a population PK model for daptomycin and to perform Monte Carlo simulations (Bauer et al., 2007). The ADAPT-TRAN program was used for pre- and post-processing (Savic et al., 2009). This study explored one- and two-compartment models of population PK of daptomycin. The two-compartment, disposition model was parameterised in terms of total clearance (CL), volume of distribution in the central compartment (V_C), volume of distribution in the peripheral compartment (V_P), and intercompartmental clearance (Q). The first order conditional estimation with inter- and intra-subject variability interaction (FOCE-I) was employed for all model runs. The inter-individual variability (η) was described using lognormal distributions, and a mixed additive and proportional model was chosen for residual variability (Ɛ). Additionally, the importance of the off-diagonal elements of the omega variance-covariance matrix was investigated. We explored the potential effects of candidate covariates on daptomycin disposal. The main variables included body size (body Mass Index [BMI] and body weight [WT]), age, sex, creatinine clearance (CCR), albumin concentration, SOFA and APACHE II scores for daptomycin clearance (CL), and the effects of WT and sex on volume of distribution.

Stepwise screening of the covariates was performed using Perl Speaks NONMEM (version 5.3.0; Uppsala University Pharmacometrics Research Group, SE), including both forward inclusion and backward elimination processes. The level of significance for keeping the covariates in the model was set at 0.05 and 0.01, respectively.

The model development and evaluation were guided on the basis of goodness-of-fit plots and parameter estimate precision. Moreover, a visual predictive check (VPC) was carried out to confirm that model simulations could reproduce the observed data. Bootstrap analysis with 1000 samples was used to evaluate the accuracy of the parameter estimation.

NONMEM software was used to simulate 1000 virtual subjects to assess the inter-subject variability (BSV) with different clinical doses (400, 500, 600, and 700 mg) for half an hour in patients with different renal function levels (creatinine clearance rates were 20, 30, 40, 60, 90, 120 mL/min).

The Kolmogorov-Smirnov test was employed to assess whether data were normally or non-normally distributed. Continuous variables are presented as means ± standard deviations if normally distributed and as median with IQR if abnormally distributed. Categorical variables were compared by the χ2 test while continuous variables were compared using the Student’s t-test or Mann-Whitney test.

This study included 64 critically ill patients (43 males and 21 females), with no significant differences found between males and females. The specific information of all patients is shown in Table 1. Sixty-three patients weighed 45–90 kg, whereas the remaining patient was extremely obese (170 kg). Among them, 39 patients received CRRT, and different patients used different hemodialysis filters. Among these, 17 patients used the MultiFiltrate Kit Ci-Ca AV1000S (Fresenius Pharmaceuticals, Bad Homburg vor der Höhe, Germany; membrane area 1.8 m²); two patients were treated with Ultraflux AV600S (Fresenius Pharmaceuticals; membrane area 1.4 m²), and 20 were treated with Prismaflex M100AN69 (BAXTER Baite International Limited, Jinbao; membrane area 0.9 m²). The blood flow rate was maintained between 95 and 350 mL/min, and the effluent flow was maintained between 1600 and 2000 mL/h and replaced as clinically indicated. Among these 45 CRRT patients, four used ECMO in combination. In addition, two patients received ECMO alone. No increase in CPK or other adverse reactions related to daptomycin were observed in any of the patients during the treatment period. A total of 737 blood concentration values were included in the population PK analysis, and the serum concentration-time curves of all blood samples are shown in Figure 1.

One- and two-compartment models were fitted separately, and the results of the objective function value (OFV) and goodness-of-fit plots showed that the time course of daptomycin concentration was well described by a two-compartment linear model with linear elimination. Unexplained residual variability was best described by additive and proportional residual error models. CCR had a significant effect on renal clearance in non-CRRT patients. After the inclusion of CCR, no other covariates significantly improved model fit. Sex was associated with individual-specific V_P, and during the three rounds of forward inclusion, all three ΔOFV values were greater than 3.84; the V_P of males was approximately 1.4 times that of females, but in the backward elimination process, the influence of sex was not retained in the final model. The SOFA score was marginally associated with individual-specific CL and was excluded from the backward elimination process. Furthermore, no relationships were identified between the CL, V_C, or V_P of daptomycin and APACHE II score, age, or serum albumin concentration.

The final covariate model is as follows: CL L / h = 0.386 in subjects undergoing CRRT 0.229 + 0.148 ⋅ C C R 54 in others V C L = 4.14 V P L = 3.52 Q L / h = 2.09 where CCR/54 is the corresponding median standardized individual CCR calculated for the current patient population.

The goodness-of-fit plots for model checking are presented in Figure 2; the results show that the trend deviation of the final model is unbiased, and the fit is satisfactory. Table 2 lists the parameters of the final population PK models together with the bootstrap results. All PK parameters were statistically significant as the 95% confidence intervals from the bootstrap analysis did not include 0. The VPC graph is shown in Figure 3, The quantile lines of the observed concentrations were all within the 90% confidence interval of the corresponding quantile lines of the predicted concentrations, which indicates a good correlation between raw data and data obtained by simulation with the final model, so the model has good prediction ability.

Due to the lack of clear MIC values for some of the included patients undergoing preventive anti-infection treatment, we took MIC = 1 mg/L for subsequent calculations based on the clinical breakpoints identified by EUCAST for Staphylococcus spp. and Streptococcus spp. (Gregoire et al., 2021), and probability of reaching target (PTA) was defined as the probability of AUC_24h/MIC ≥666. Simulations of the dosage regimens in patients with different renal functions are shown in Table 3, and the PTA is shown in Figure 4. When the MIC value was 1 mg/L, the majority of critically ill adult patients were unable to achieve the anti-infective target when the daily dose of daptomycin was 400 mg (equivalent to a dose of 6 mg/kg/day for a patient with a body weight of 70 kg); when the daily dose was 500 mg, the probability of achieving the pharmacodynamic target value reached 90% in adult patients receiving CRRT and with different degrees of renal impairment, and the infection could be better controlled; for critically ill adult patients with normal renal function (CCR ≥90 mL/min), the daily dose needed to be increased to 700 mg (equivalent to the dose of 10 mg/kg/day for patients weighing 70 kg) in order to achieve 90% probability of reaching the pharmacodynamic target value. In patients receiving CRRT, the PTA was only 70.6% when administered at a dose of 400 mg for 24 h. It was necessary to increase the dosage to 500 mg to increase the PTA to 90.7%. Therefore, in patients with normal renal function, especially in critically ill patients with hyperrenalism, it is recommended to increase the dosage from the standard dosage recommended in the daptomycin insert and 500 mg q24 h is recommended for patients receiving CRRT.