What Are the Current Approaches to Optimising Antimicrobial Dosing in the Intensive Care Unit?

Chai, Ming G; Cotta, Menino Osbert; Abdul‐Aziz, Mohd H.; Roberts, Jason A.

doi:10.3390/pharmaceutics12070638

Cited by 38 publications

(39 citation statements)

References 142 publications

(151 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The quantitative relationship between MIC and PK is determined by the pharmacokinetic/pharmacodynamic indices PK/PD [ 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 ]. The clinical efficacy of different groups of antibiotics depends on one of three different PK/PDs:…”

Section: The Importance Of Mic Values In Clinical Practicementioning

confidence: 99%

The Minimum Inhibitory Concentration of Antibiotics: Methods, Interpretation, Clinical Relevance

2021

View full text Add to dashboard Cite

Inefficiency of medical therapies used in order to cure patients with bacterial infections requires not only to actively look for new therapeutic strategies but also to carefully select antibiotics based on variety of parameters, including microbiological. Minimal inhibitory concentration (MIC) defines in vitro levels of susceptibility or resistance of specific bacterial strains to applied antibiotic. Reliable assessment of MIC has a significant impact on the choice of a therapeutic strategy, which affects efficiency of an infection therapy. In order to obtain credible MIC, many elements must be considered, such as proper method choice, adherence to labeling rules, and competent interpretation of the results. In this paper, two methods have been discussed: dilution and gradient used for MIC estimation. Factors which affect MIC results along with the interpretation guidelines have been described. Furthermore, opportunities to utilize MIC in clinical practice, with pharmacokinetic /pharmacodynamic parameters taken into consideration, have been investigated. Due to problems related to PK determination in individual patients, statistical estimation of the possibility of achievement of the PK/PD index, based on the Monte Carlo, was discussed. In order to provide comprehensive insights, the possible limitations of MIC, which scientists are aware of, have been outlined.

show abstract

Section: The Importance Of Mic Values In Clinical Practicementioning

confidence: 99%

The Minimum Inhibitory Concentration of Antibiotics: Methods, Interpretation, Clinical Relevance

2021

View full text Add to dashboard Cite

show abstract

“…A change in pathophysiological condition in patient with sepsis can occur which can also result in PK changes for antibiotics (Taccone et al, 2011;Bergen et al, 2017;Chai et al, 2020). The shifting of fluid used for resuscitation of sepsis from blood vessels into the extravascular space can lead to a greater total volume of distribution (V) compared to those from healthy subjects (Taccone et al, 2011;Varghese et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

“…Ertapenem is the time-dependent antibiotic, and the percentage of time that the free drug level exceeds over the MIC (%fT >MIC ) is the pharmacodynamics (PD) index that best predicts the killing effect of drug (Bader et al, 2019). However, an alteration of PK due to pathophysiological changes in patients with critical illness has the impact on the plasma concentrations of antibiotics (Bergen et al, 2017;Chai et al, 2020). The objectives of this study were (i) to determine the population PK, and (ii) to assess the probability of target attainment (PTA) of ertapenem in patients with critical illnesses.…”

Section: Introductionmentioning

confidence: 99%

NONMEM population pharmacokinetic and Monte Carlo dosing simulation of ertapenem in patients with sepsis

Jaruratanasirikul¹,

Nopparatana²,

Boonpeng³

et al. 2021

Afr. J. Pharm. Pharmacol.

View full text Add to dashboard Cite

An alteration of pharmacokinetics (PK) due to pathophysiological changes in patients with critical illnesses have the impact on the drug levels in plasma, consequently affecting the achievement of pharmacodynamics (PD) targets of antibiotics. The objectives of this study were (i) to determine the population PK, and (ii) to assess the probability of target attainment (PTA) of ertapenem in patients with critical conditions. The study examined the population PK of ertapenem using NONMEM and performed the assessment of the PTAs of achieving 40 and 80% of the time that the free drug level exceeds over the MIC (fT >MIC ). The central and peripheral volumes of distribution were 49 (with the %CV of 67.10) and 91.90 (with the %CV of 78.90) L, respectively, and total clearance of ertapenem was 15.40 (with the %CV of 46.80) L/h. Our PD analysis for achieving a target of 40% fT >MIC in patients with normal renal function, the dosing of 1 g once daily can cover a MIC of 0.5 mg/L and for a higher minimum inhibitory concentration (MIC) of 1 mg/L, the dosing should be increased to 2 g once daily. Moreover, the achievements of PTAs in patients with lower GFRs were greater than those of PTAs in patients with higher GFRs. In conclusion, higher than maximum recommended dosing of ertapenem may be required for achieving the PD targets in septic patients with critical illnesses; however, in renal impaired patients the required dosage regimens may be lower than recommended dosing.

show abstract

“…In order to explore various ways to optimize the dosage of antibacterial drugs in ICU patients, novel dosing software using AI were developed to assist in the adjustment of antibiotic treatment, one of which was Bayesian forecasting. These plans can use the monitoring results of antibiotic treatment to further personalize the antibacterial program according to the clinical characteristics of each patient (39)(40)(41)(42).…”

Section: Application Of Ai In the Management Of Patients With Sepsismentioning

confidence: 99%

Artificial Intelligence for Clinical Decision Support in Sepsis

et al. 2021

Front. Med.

View full text Add to dashboard Cite

Sepsis is one of the main causes of death in critically ill patients. Despite the continuous development of medical technology in recent years, its morbidity and mortality are still high. This is mainly related to the delay in starting treatment and non-adherence of clinical guidelines. Artificial intelligence (AI) is an evolving field in medicine, which has been used to develop a variety of innovative Clinical Decision Support Systems. It has shown great potential in predicting the clinical condition of patients and assisting in clinical decision-making. AI-derived algorithms can be applied to multiple stages of sepsis, such as early prediction, prognosis assessment, mortality prediction, and optimal management. This review describes the latest literature on AI for clinical decision support in sepsis, and outlines the application of AI in the prediction, diagnosis, subphenotyping, prognosis assessment, and clinical management of sepsis. In addition, we discussed the challenges of implementing and accepting this non-traditional methodology for clinical purposes.

show abstract

What Are the Current Approaches to Optimising Antimicrobial Dosing in the Intensive Care Unit?

Cited by 38 publications

References 142 publications

The Minimum Inhibitory Concentration of Antibiotics: Methods, Interpretation, Clinical Relevance

The Minimum Inhibitory Concentration of Antibiotics: Methods, Interpretation, Clinical Relevance

NONMEM population pharmacokinetic and Monte Carlo dosing simulation of ertapenem in patients with sepsis

Artificial Intelligence for Clinical Decision Support in Sepsis

Contact Info

Product

Resources

About