Literature DB >> 31349296

Using Microbiological Data Analysis to Tackle Antibiotic Resistance of Klebsiella Pneumoniae.

Georgios Feretzakis1,2,3, Evangelos Loupelis2, Stavroula Petropoulou2, Constantinos Christopoulos4, Malvina Lada4, Maria Martsoukou5, Nikoleta Skarmoutsou5, Katerina Sakagianni6, Sophia Michelidou6, Katerina Velentza5, Konstantinos Valakis6, Emmanouil Koutalas7.   

Abstract

Optimal antibiotic use for the treatment of nosocomial infections plays a central role in the effort to control the rapidly increasing prevalence of multidrug-resistant bacteria. Antibiotic selection should be based on accurate knowledge of local susceptibility rates. Traditional methods of resistance reporting, which are in routine use by microbiology laboratories could be enhanced by using statistically significant results. We present a method of reporting based on antibiotic susceptibility data analysis which offers an accurate tool that reduces clinician uncertainty and enables optimization of the antibiotic selection process.

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Keywords:  Antibiotic resistance; K. pneumoniae; Microbiological data analysis; Multidrug resistance; antibiotic susceptibility

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Year:  2019        PMID: 31349296     DOI: 10.3233/SHTI190047

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  1 in total

1.  Using Machine Learning Techniques to Aid Empirical Antibiotic Therapy Decisions in the Intensive Care Unit of a General Hospital in Greece.

Authors:  Georgios Feretzakis; Evangelos Loupelis; Aikaterini Sakagianni; Dimitris Kalles; Maria Martsoukou; Malvina Lada; Nikoletta Skarmoutsou; Constantinos Christopoulos; Konstantinos Valakis; Aikaterini Velentza; Stavroula Petropoulou; Sophia Michelidou; Konstantinos Alexiou
Journal:  Antibiotics (Basel)       Date:  2020-01-31
  1 in total

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