Comparison of two methods to obtain a desired first isepamicin peak in intensive care patients

In-vitro Activity of Isepamicin against Gram-negative Bacteria in Comparison to Other Aminoglycosides Routinely used at a Teaching Hospital in Northern India

Background  Isepamicin is a 1-N-S-a-hydroxy-b-aminopropionyl derivative of gentamicin B and the spectrum of pathogenic microorganisms covered by it and its effectiveness is similar to that of amikacin except the action of aminoglycoside inhibitor enzymes is ineffectual on it. Material and Methods  We performed a prospective study in the Bacteriology section of the Department of Microbiology at a 1,600-bedded hospital in Northern India from Jan 2022 to March 2022. Isepamicin was tested for susceptibility against gram-negative bacteria, identified by routine biochemicals and matrix-assisted-desorption/ionization -time of flight-mass spectrometry (MALDI-TOF-MS) assay. The antibiotic susceptibility testing for each of the isolates was performed by Kirby Bauer's disc diffusion method, according to the CLSI 2019 guidelines. Results  The majority of isolates were obtained from blood samples (50, 39.1%). Among the non-inducible Enterobacteriaceae , Escherichia coli was least susceptible to amikacin (8/27, 29.63%) and most susceptible to isepamicin (18/27, 66.67%). Klebsiella pneumoniae followed the same pattern of susceptibility as E. coli and was least susceptible to Amikacin (20/46, 43.48%) and most susceptible to isepamicin (24/46, 52.17%). Enterobacter cloacae (6/7, 85.71%) was most susceptible to both amikacin and isepamicin, followed by 71.43% (5/7, 71.43%) susceptibility to gentamicin and tobramycin each. Enterobacter aerogenes was equally 53.33% (8/15) susceptible to all antibiotics. Pseudomonas aeruginosa was the most susceptible isolate to all antibiotics (18/21, 85.71%). Conclusion  Isepamicin is a potential antimicrobial agent for treating an array of gram-negative bacteria-associated infections and shows better in vitro activity than older aminoglycoside agents.

Investigation of isepamicin in vitro efficiency in Gram negative bacteria efficacy of isepamicin

CONTEXT

Isepamicin is a new semisynthetic aminoglycoside derived from gentamicin B and it is effective against Gram negative bacteria. Antibiotic resistance is an emerging problem and new options need for the treatment of infections caused by Gram negative bacteria.

AIMS

In this study we aimed to investigate the in vitro efficiency in carbapenem susceptible and nonsusceptible Enterobacterales and Pseudomonas aeruginosa.

METHODS AND MATERIAL

A total of 214 isolates of Gram-negative bacteria (Enterobacterales n = 129 and P. aeruginosa n = 85). Identification of the bacteria was tested in Vitek MS (Biomeriux, France). Susceptibility of isepamicin, amikacin, gentamicin, tobramycin and netilmicin was determined by Kirby Bauer disc diffusion method. The breakpoints for susceptibility to isepamicin, amikacin, gentamicin, streptomycin, tobramycin and netilmicin were evaluated according to the Comité de l'Antibiogramme dela Société Française de Microbiologie (CA-SFM) and EUCAST, respectively. Aminoglycoside modifying enzyme (AME) genes were investigated by multiplex PCR method.

RESULTS

Isepamicin susceptibility was determined as 92.3% for Enterobacterales and 67% for P. aeruginosa and 94.4% for carbapenem resistant Enterobacterales. The most common AME gene was aac (6')-Ib in both Enterobacterales (76%) and P. aeruginosa (14.1%). Seven of the isepamicin intermediate or resistant isolates were positive aac (6')-Ib in Enterobacterales and P. aeruginosa.

CONCLUSIONS

In this study, isepamicin showed good efficiency against both susceptible and carbapenem nonsusceptible Enterobacterales. But amikacin was prior to isepamicin P. aeruginosa isolates. Isepamicin could be a therapeutic option for the infections caused by Enterobacterales.

Old antibiotics for infections in critically ill patients

PURPOSE OF REVIEW

The alarming epidemic of multidrug-resistant bacteria and the reluctance of the pharmaceutical industry to invest in the development of new antibiotics have forced clinicians to reintroduce forgotten antibiotics into their practice. This review highlights the effectiveness and safety of older antibiotics when used in the treatment of infections of critically ill patients.

RECENT FINDINGS

Polymyxins emerged as useful antibiotics for the treatment of infections due to multidrug-resistant Gram-negative bacteria, in particular Acinetobacter baumannii, Pseudomonas aeruginosa and Klebsiella pneumoniae. The nephrotoxicity and neurotoxicity associated with their use are less frequent and serious than previously reported. In addition, aerosolized polymyxins may be a useful weapon in the treatment of hospital-acquired pneumonia. Fosfomycin and chloramphenicol have a wide antimicrobial spectrum, are used extensively in Europe and Africa, respectively, and may have an expanded role in our antimicrobial arsenal. Fusidic acid remains active against various staphylococcal strains, while isepamicin (an aminoglycoside used in some European countries) is slightly more effective than amikacin against some Gram-negative bacteria.

SUMMARY

The declining investment of the pharmaceutical industry in the development of new antibiotics and the increasing antimicrobial resistance create a fertile ground for the study and, probably, revival of older antibiotics for use, especially in critically ill patients.

Artificial neural network modeling to predict the plasma concentration of aminoglycosides in burn patients

The goal was to use an artificial neural network model to predict the plasma concentration of aminoglycosides in burn patients and identify patients whose plasma antibiotic concentration would be sub-therapeutic based on the patients' physiological data and taking into account burn severity. Physiological data and some indicators of burn severity were collected from 30 burn patients who received arbekacin. A three-layer artificial neural network with five neurons in the hidden layer was used to predict the plasma concentration of arbekacin. Linear modeling for prediction of plasma concentration and logistic regression modeling for the classification of patients were also used and the predictive performance was compared to results from the artificial neural network model. Dose, body mass index, serum creatinine concentration and amount of parenteral fluid were selected as covariates for the plasma concentration of arbekacin. Area of burn after skin graft was a good covariate for indicating burn severity. Predictive performance of the artificial neural network model including burn severity was much better than linear modeling and logistic regression analysis. An artificial neural network model should be helpful for the prediction of plasma concentration using patients' physiological data, and burn severity should be included for improved prediction in burn patients. Because the relationship between burn severity and plasma concentration of aminoglycosides is thought to be nonlinear, it is not surprising that the artificial neural network model showed better predictive performance compared to the linear or logistic regression models.