Evaluation of Current Amikacin Dosing Recommendations and Development of an Interactive Nomogram: The Role of Albumin

Risk factors of infective endocarditis-associated acute kidney injury: benefits of low-dose amikacin and surgery

OBJECTIVE

Acute kidney injury (AKI) is a frequent presentation in patients with infective endocarditis (IE), and is associated with poor outcomes. The primary aim of the study was to determine the risk factors for AKI in patients with IE.

METHODS

A retrospective study was conducted in a tertiary hospital in China from August 2012 to April 2022. The primary outcome was AKI. Logistic regression was used to identify risk factors for AKI.

RESULTS

A total of 594 patients with IE were included, of which 256 (43.1%) experienced AKI. The following variables were found to be independent risk factors for AKI: hypertension (OR 1.96, p = 0.011), Staphylococcus aureus infection (OR 2.69, p = 0.008), heart failure (OR 5.99, p < 0.001), shock (OR 5.93, p = 0.015) and hematuria (OR 2.38, p < 0.001). The use of low-dose amikacin (400 mg daily) was associated with a lower incidence of AKI (OR 0.38, p < 0.001). Among patients with IE complicated by heart failure, surgery was associated with a lower incidence of AKI (OR 0.21, p = 0.010).

CONCLUSION

AKI is common in IE. Hypertension, Staphylococcus aureus infection, heart failure, shock and hematuria are risk factors of IE-associated AKI, whereas low-dose amikacin is a protective factor. Surgery is a protective factor of AKI in the setting of IE complicated by heart failure.

Pharmacodynamic target attainment of the synergism of ceftazidime-avibactam in combination with amikacin against OXA-producing extensively drug-resistant or pan drug-resistant (XDR/PDR) Pseudomonas aeruginosa

To investigate the pharmacodynamic target attainment of ceftazidime-avibactam (CZA) in combination with amikacin against OXA-producing extensively drug-resistant/ pan-drug-resistant Pseudomonas aeruginosa (XDR/PDR-PA). The minimum inhibitory concentrations (MICs) of CZA and amikacin against OXA-producing XDR/PDR-PA were determined by the checkerboard method, and the combined inhibitory index (FICI) was calculated to evaluate whether the combination of the two antimicrobials has a synergistic effect on OXA-producing XDR/PDR-PA in vitro. The pharmacokinetic (PK) and pharmacodynamic (PD) parameters of CZA and amikacin were combined by Monte Carlo simulation (MCS) to evaluate the cumulative fraction of response (CFR) of the two antimicrobials for the treatment of OXA-producing XDR/PDR-PA infection. The results of synergy tests of CZA in combination with amikacin suggested that 77.3% of XDR/PDR-PA showed synergistic effects. When the PK/PD target was greater than 50, CFR was 97.84% for CZA 2.5 g q8h when CZA in combination with amikacin. CZA in combination with AMK has a synergistic effect in vitro and could be a potential option for treating OXA-producing XDR/PDR-PA infections.

Amikacin Dosing Adjustment in Critically Ill Oncologic Patients: A Study with Real-World Patients, PBPK Analysis, and Digital Twins

Background/Objectives: Guidelines recommend adjusting amikacin dosing based on patients' renal function. Nevertheless, for critically ill cancer patients, the renal function equations based on serum creatinine levels have low or no correlation with amikacin clearance. Considering this, using real-world data, we built an amikacin PBPK model to predict amikacin plasma concentrations in critically ill oncologic patients stratified by renal impairment levels. Further, the model was applied for dose stratification and individualization (digital twin strategy) in this population. Methods: In the Therapeutic Drug Monitoring (TDM) study, 368 amikacin pharmacokinetic analyses from 184 critically ill cancer patients were enrolled in three cohorts. A full-body PBPK model was developed using PK-Sim v. 11.3. Results: The final PBPK model accounted for two groups of critically ill cancer patients with mild (creatinine clearance; CLcr ≥ 60 mL/min) or severe (CLcr < 60 mL/min) renal dysfunction. In the dose stratification strategy, at the 7th dose, cancer patients with CLcr ≥ 60 mL/min under regimens 20 mg/kg (q24h); 25 mg/kg (q24h); 25 mg/kg (q48h); and 30 mg/kg (q72h) have probability of ≥69% of the patients achieving the efficacy target (AUC/MIC > 80, MIC of 4 mg/L), while cancer patients with CLcr < 60 mL/min under regimens 7.5 mg/kg (q24h); 15 mg/kg (q24h); 15 mg/kg (q48h); and 20 mg/kg (q36h) have ≥90% probability of achieving the same efficacy target. Conclusions: Our MIPD approach demonstrates potential in optimizing amikacin dosing for critically ill cancer patients. However, it does not eliminate the need for TDM due to unexplained variability still not accounted for by the PBPK model.

Does Antibiotic Use Contribute to Biofilm Resistance in Sink Drains? A Case Study from Four German Hospital Wards

Backgound. As biofilms are known to harbour (multi-)resistant species, their presence in health settings must be considered critical. Although there is evidence that bacteria spread from drains to the outside, there is still a lack of research data focusing on drain biofilms from hospitals. Methods. We sampled biofilms from various wards of Helios Hospital Krefeld (Germany), where comprehensive antibiotic consumption data were available. Biofilms were analysed by cell counting, isolation of relevant bacterial groups and genetic and phenotypical resistance parameters. Data were correlated with the prescribed antibiotics of the respective ward. Furthermore, an ex situ biofilm model was employed to investigate the influence of sub-inhibitory antibiotics on the bacterial community and the prevalence of class 1 integrons. Results. Our results show that every ward harboured medically relevant bacterial species. While no significant differences were found in cell counts, the median prevalence of the resistance marker gene intI1 correlated with the amount of prescribed antibiotics. In contrast, phenotypical resistances showed no similar tendency. In addition, melting curve analysis data and changes in intI1 prevalence show that the composition of the bacterial community shifted depending on the biofilm and antibiotic. Conclusions. To the best of our knowledge, our study is the first considering possible correlations between the consumption data of hospital wards and resistances in drain biofilms the way we did. Based on our results, we conclude that sub-inhibitory concentrations of antibiotics have no general effect on biofilms in terms of bacterial community shift and occurrence of antibiotic-resistant species. Amongst other things, the effect depends on the initial composition of the bacterial community, the antibiotic used and the intrinsic bacterial resistance, e.g., prevalence of class 1 integrons.

Prediction of tissue exposures of polymyxin-B, amikacin and sulbactam using physiologically-based pharmacokinetic modeling

Background

The combination antimicrobial therapy consisting of amikacin, polymyxin-B, and sulbactam demonstrated in vitro synergy against multi-drug resistant Acinetobacter baumannii.

Objectives

The objectives were to predict drug disposition and extrapolate their efficacy in the blood, lung, heart, muscle and skin tissues using a physiologically-based pharmacokinetic (PBPK) modeling approach and to evaluate achievement of target pharmacodynamic (PD) indices against A. baumannii.

Methods

A PBPK model was initially developed for amikacin, polymyxin-B, and sulbactam in adult subjects, and then scaled to pediatrics, accounting for both renal and non-renal clearances. The simulated plasma and tissue drug exposures were compared to the observed data from humans and rats. Efficacy was inferred using joint probability of target attainment of target PD indices.

Results

The simulated plasma drug exposures in adults and pediatrics were within the 0.5 to 2 boundary of the mean fold error for the ratio between simulated and observed means. Simulated drug exposures in blood, skin, lung, and heart were consistent with reported penetration ratio between tissue and plasma drug exposure. In a virtual pediatric population from 2 to <18 years of age using pediatric dosing regimens, the interpretive breakpoints were achieved in 85-90% of the population.

Conclusion

The utility of PBPK to predict and simulate the amount of antibacterial drug exposure in tissue is a practical approach to overcome the difficulty of obtaining tissue drug concentrations in pediatric population. As combination therapy, amikacin/polymyxin-B/sulbactam drug concentrations in the tissues exhibited sufficient penetration to combat extremely drug resistant A. baumannii clinical isolates.

Therapeutic drug monitoring of Amikacin in hospitalized patients: A pilot study

Background

Amikacin, an aminoglycoside, is a widely used parenteral antibiotic. Therapeutic drug monitoring (TDM) is recommended for aminoglycosides to avoid toxicity. However, the lack of infrastructure at most places precludes it. This pilot and novel study attempt to estimate the real-world serum levels of Amikacin in hospitalised patients.

Methods

Thirty admitted patients, given Amikacin injections, were included in the study. In addition, 15 clinical specimens isolated with gram-negative bacteria were tested for minimum inhibitory concentration (MIC) value of Amikacin. Trough and peak serum levels of Amikacin were estimated by high-pressure liquid chromatography (HPLC).

Results

The average MIC value of Amikacin estimated in our laboratory was 3.92 mcg/mL. Peak and trough serum levels of Amikacin ranged from 12.1 to 66.4 mcg/ml and 1.1 to 20.7 mcg/ml, respectively. More than 83% of our patients achieved peak Amikacin levels of 15 mcg/mL, and 37% had trough levels above 5 mcg/mL. These levels are desirable watersheds as per available literature.

Conclusion

Trough levels of Amikacin in all cases and a review of dosing according to MIC values are recommended to achieve drug safety and therapeutic efficacy.

Development of a Predictive Dosing Nomogram to Achieve PK/PD Targets of Amikacin Initial Dose in Critically Ill Patients: A Non-Parametric Approach

French guidelines recommend reaching an amikacin concentration of ≥8 × MIC 1 h after beginning infusion (C_1h), with MIC = 8 mg/L for probabilistic therapy. We aimed to elaborate a nomogram guiding clinicians in choosing the right first amikacin dose for ICU patients in septic shock. A total of 138 patients with 407 observations were prospectively recruited. A population pharmacokinetic model was built using a non-parametric, non-linear mixed-effects approach. The total body weight (TBW) influenced the central compartment volume, and the glomerular filtration rate (according to the CKD-EPI formula) influenced its clearance. A dosing nomogram was produced using Monte Carlo simulations of the amikacin amount needed to achieve a C_1h ≥ 8 × MIC. The dosing nomogram recommended amikacin doses from 1700 mg to 4200 mg and from 28 mg/kg to 49 mg/kg depending on the patient's TBW and renal clearance. However, a C_through ≤ 2.5 mg/L 24 h and 48 h after an optimal dose of amikacin was obtained with probabilities of 0.20 and 0.81, respectively. Doses ≥ 30 mg/kg are required to achieve a C_1h ≥ 8 × MIC with MIC = 8 mg/L. Targeting a MIC = 8 mg/L should depend on local ecology.

Amikacin pharmacokinetics in elderly patients with severe infections

OBJECTIVE

The aim of this study was to characterize the population pharmacokinetics of amikacin in elderly patients by means of nonlinear mixed effects modelling and to propose initial dosing schemes to optimize therapy based on PK/PD targets.

METHOD

A total of 137 elderly patients from 65 to 94 years receiving intravenous amikacin and routine therapeutic drug monitoring at Hospital Universitario Severo Ochoa were included. Concentration-time data and clinical information were retrospectively collected; initial doses of amikacin ranged from 5.7 to 22.5 mg/kg/day and each patient provided between 1 and 10 samples.

RESULTS

Amikacin pharmacokinetics were best described by a two-compartment open model; creatinine clearance (CrCL) was related to drug clearance (2.75 L/h/80 mL/min) and it was augmented 28% when non-steroidal anti-inflammatory drugs were concomitantly administered. Body mass index (BMI) influenced the central volume of distribution (17.4 L/25 kg/m²). Relative absolute prediction error was reduced from 33.2% (base model) to 17.9% (final model) when predictive performance was evaluated with a different group of elderly patients. A nomogram for initial amikacin dosage was developed and evaluated based on stochastic simulations considering final model to achieve PK/PD targets (Cmax/MIC>10 and AUC/MIC>75) and to avoid toxic threshold (Cmin<2.5 mg/L).

CONCLUSION

Initial dosing approach for amikacin was designed for elderly patients based on nonlinear mixed effects modeling to maximize the probability to attain efficacy and safety targets considering individual BMI and CrCL.