Detection of antibiotic resistances of Mycobacterium tuberculosis on DNA microarrays

Abstract

Background: This study describes the development of an automated surveillance system using antimicrobial consumption data for the prediction of potential emergence of carbapenem-resistant organisms. It was derived from a retrospective analysis of an intervention to contain a prolonged OXA-48 producing K. pneumoniae outbreak. Methods & Materials: A time series analysis (May 2005-April 2013) was conducted around an intervention to contain an outbreak (Jan2008-April 2010)of anOXA-48-producingK. pneumoniae in the renal unit of a West London teaching hospital. The intervention focused on reinforcement of the renal antimicrobial policy and the decrease of carbapenem usage, as part of the overall stewardship strategy. Three mechanisms were promoted: awareness, education and feedback. A multivariate ARIMA model was developed utilising meropenem consumption data (defined daily dose per 100 occupied bed-days; DDD/100OBD) as a predictor of the incidence of OXA-48-producing organisms. Results: Meropenem usage was increasing by 7.13DDD/100OBD/year (95%CI 3.46-10.80; p<0.001) from 6.30DDD/100OBD/year prior to the intervention but decreased steadily for 4 years thereafter. The changes in slope of the time series were -10.18DDD/100OBD/year (95% CI, -16.63-3.73). Analysis of consumption of other gram negative antimicrobials was also undertaken and showed a significant increase in amikacin usage post-intervention from 0.56 to 4.07DDD/100OBD/year (slope= +0.83; 95%CI, 0.13-1.53). The incidence of OXA-48producing organisms was significantly increasing by 2.2 cases per year pre-intervention, and decreased thereafter. Meropenem usage at lag-1 year was highly correlated to the incidence of OXA-48-producing organisms (r =0.74, pvalue =0.04) and was included as a predictor within the ARIMA model for forecasting the incidence of resistant isolates. Conclusion: Our findings support an association between reinforcement of a specific antimicrobial policy and both meropenem usage, and a decreasing incidence of OXA-48-producing K. pneumoniae. Meropenem usage at lag-1 year was found to be a good predictor of the incidence of OXA-48-producing K. pneumoniae in the ARIMA model, although we need to remain cautious about the causality. This prediction model requires further development but shows early signs of how close surveillance of antimicrobial consumption can act as a warning indicator to anticipate potential outbreaks of drug resistance organisms and should be considered as part of healthcare organisations’ antimicrobial stewardship programmes.