Empirical antibiotic therapy for pneumonia in intensive care units: a multicentre, retrospective analysis of potentially pathogenic microorganisms identified by endotracheal aspirates cultures

Dielectrophoresis assisted rapid, selective and single cell detection of antibiotic resistant bacteria with G-FETs

The rapid increase in antibiotic resistant pathogenic bacteria has become a global threat, which besides the development of new drugs, requires rapid, cheap, scalable, and accurate diagnostics. Label free biosensors relying on electrochemical, mechanical, and mass based detection of whole bacterial cells have attempted to meet these requirements. However, the trade-off between selectivity and sensitivity of such sensors remains a key challenge. In particular, point-of-care diagnostics that are able to reduce and/or prevent unneeded antibiotic prescriptions require highly specific probes with sensitive and accurate transducers that can be miniaturized and multiplexed, and that are easy to operate and cheap. Towards achieving this goal, we present a number of advances in the use of graphene field effect transistors (G-FET) including the first use of peptide probes to electrically detect antibiotic resistant bacteria in a highly specific manner. In addition, we dramatically reduce the needed concentration for detection by employing dielectrophoresis for the first time in a G-FET, allowing us to monitor changes in the Dirac point due to individual bacterial cells. Specifically, we realized rapid binding of bacterial cells to a G-FET by electrical field guiding to the device to realize an overall 3 orders of magnitude decrease in cell-concentration enabling a single-cell detection limit, and 9-fold reduction in needed time to 5 min. Utilizing our new biosensor and procedures, we demonstrate the first selective, electrical detection of the pathogenic bacterial species Staphylococcus aureus and antibiotic resistant Acinetobacter baumannii on a single platform.

Temporal trends of the in vitro activity of tigecycline and comparator antibiotics against clinical aerobic bacterial isolates collected in Germany, 2006-2014: results of the Tigecycline Evaluation and Surveillance Trial (TEST)

Given the rapidly changing landscape of antimicrobial resistance, continuous monitoring of antimicrobial susceptibility in clinically relevant bacterial isolates plays an important role in the management of infectious diseases. The Tigecycline Evaluation and Surveillance Trial (TEST) is an ongoing worldwide surveillance programme monitoring the in vitro activity of tigecycline and a panel of representative comparator antibiotics. We report longitudinal susceptibility data on a large set of isolates (n=36,044) from clinically significant bacterial species collected in 25 microbiological laboratories from 2006 to 2014. Trends include a strong increase of carbapenem and levofloxacin resistance in Acinetobacter spp., and smaller increasing rates of ESBL-producing Escherichia coli and vancomycin-resistant enterococci. Across the reporting period, the tigecycline minimum inhibitory concentrations (MICs) at which 50% and 90% of isolates were inhibited remained stable and susceptibility rates were consistently high (93–100%) for all bacterial species.

An antibiotic decision-making tool for patients with pneumonia admitted to a medical intensive care unit

Pneumonia is a leading cause of death in medical intensive care units (MICUs). Delayed or inappropriate antibiotic therapy largely increases morbidity and mortality. Multidrug-resistant (MDR) micro-organisms are major reasons for inappropriate antibiotic use. Currently there is no good antibiotic decision-making tool designed for critically ill patients. The objective of this study was to develop a convenient MDR prediction scoring system for patients admitted to MICUs with pneumonia. A retrospective cohort study was conducted using databases and chart reviews of pneumonia patients admitted to a 30-bed MICU from 2012 to 2013. Forward logistic regression was applied to identify independent MDR risk factors for prediction tool development. A total of 283 pneumonia episodes from 263 patients with positive cultures from blood or respiratory secretions were recruited, of which 154 (54.4%) were MDR episodes. Long-term ventilation (OR = 11.09; P = 0.026), residence in a long-term care facility (OR = 2.50; P = 0.005), MDR infection/colonisation during the preceding 90 days (OR = 2.08; P = 0.041), current hospitalisation ≥2 days (OR = 1.98; P = 0.019) and stroke (OR = 1.81; P = 0.035) were identified as independent predictors for MDR pneumonia. The area under the ROC curve of this prediction tool was much higher than that of ATS/IDSA classification (0.69 vs. 0.54; P <0.001). The prediction accuracy of this tool with risk score ≥1 for MDR infections was 63.7%. This simple five-item, one-step scoring tool for critically ill patients admitted to the MICU could help physicians provide timely appropriate empirical antibiotics.