Integrating drug concentrations and minimum inhibitory concentrations with Bayesian-dose optimisation for multidrug-resistant tuberculosis
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چکیده
منابع مشابه
Integrating drug concentrations and minimum inhibitory concentrations with Bayesian-dose optimisation for multidrug-resistant tuberculosis.
The problems of multidrug-resistant (MDR) tuberculosis (TB), extensively drug-resistant (XDR) TB, and even ‘‘totally drug-resistant’’ TB (a term that is still debated), have exposed two important clinical issues [1, 2]. The first issue involves figuring out a way to prevent these difficult-to-treat diseases. The second issue is treating patients with drug-resistant TB [3]. In the meantime even ...
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A total of 92 isolates of Mycobacterium tuberculosis consisting of equal numbers of sensitive and resistant strains was tested for their susceptibility to sulbactam and ampicillin (in the ratio of 1:2) on Lowenstein-Jensen (LJ) and 7H11 agar media. The geometric mean MIC was 63.97 micrograms/ml for the drug sensitive strains and 65.92 micrograms/ml for the resistant strains, and the overall mea...
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1 Grønseth R, Vollmer WM, Hardie JA, et al. Predictors of dyspnoea prevalence: results from the BOLD study. Eur Respir J 2014; 43: 1610–1620. 2 NHS Sustainable Development Unit. Sustainability in the NHS: Health Check 2012. Cambridge, NHS Sustainable Development Unit, 2012. Available from: www.sduhealth.org.uk/documents/publications/Sustainability_in_the_ NHS_Health_Check_2012_On-Screen_Version...
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Minimum inhibitory concentrations (MICs) are defined as the lowest concentration of an antimicrobial that will inhibit the visible growth of a microorganism after overnight incubation, and minimum bactericidal concentrations (MBCs) as the lowest concentration of antimicrobial that will prevent the growth of an organism after subculture on to antibiotic-free media. MICs are used by diagnostic la...
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Aminoglycosides, such as amikacin, are used to treat multidrug-resistant tuberculosis. However, ototoxicity is a common problem and is monitored using peak and trough amikacin concentrations based on World Health Organization recommendations. Our objective was to identify clinical factors predictive of ototoxicity using an agnostic machine learning method. We used classification and regression ...
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ژورنال
عنوان ژورنال: European Respiratory Journal
سال: 2013
ISSN: 0903-1936,1399-3003
DOI: 10.1183/09031936.00081313