Informed Switching Strongly Decreases the Prevalence of Antibiotic Resistance in Hospital Wards

Antibiotic resistant nosocomial infections are an important cause of mortality and morbidity in hospitals. Antibiotic cycling has been proposed to contain this spread by a coordinated use of different antibiotics. Theoretical work, however, suggests that often the random deployment of drugs (“mixing”) might be the better strategy. We use an epidemiological model for a single hospital ward in order to assess the performance of cycling strategies which take into account the frequency of antibiotic resistance in the hospital ward. We assume that information on resistance frequencies stems from microbiological tests, which are performed in order to optimize individual therapy. Thus the strategy proposed here represents an optimization at population-level, which comes as a free byproduct of optimizing treatment at the individual level. We find that in most cases such an informed switching strategy outperforms both periodic cycling and mixing, despite the fact that information on the frequency of resistance is derived only from a small sub-population of patients. Furthermore we show that the success of this strategy is essentially a stochastic phenomenon taking advantage of the small population sizes in hospital wards. We find that the performance of an informed switching strategy can be improved substantially if information on resistance tests is integrated over a period of one to two weeks. Finally we argue that our findings are robust against a (moderate) preexistence of doubly resistant strains and against transmission via environmental reservoirs. Overall, our results suggest that switching between different antibiotics might be a valuable strategy in small patient populations, if the switching strategies take the frequencies of resistance alleles into account

Quantifying antibiotic use in paediatrics: a proposal for neonatal DDDs

The defined daily dose (DDD) as defined by the World Health Organization (WHO) has been the most frequently used unit of measurement to measure antibiotic use. However, measuring antibiotic use in paediatrics is a problem as the WHO DDD methodology is not applicable in children (aged >1 month) due to the large variation in body weight within this population. Based on the narrow range of body weights in the neonatal population, we therefore aimed to develop a set of neonatal DDDs for antibiotics. Eight well-respected (inter)national sources for dosage recommendations of antibiotics in children and neonates were consulted for the assumed maintenance dose of the ten most frequently used antibiotics in neonatal intensive care units in its main indication for neonates. A set of neonatal DDDs for ten commonly used antibiotics in neonates based on an assumed neonatal weight of 2 kg was proposed. Primarily in children DDDs are not applicable to quantify antibiotic use since there is large variation in body weight. In the neonatal population, however, based on its narrow range of body weights and when access to patient level data is not available, neonatal DDDs can be used as a unit of measurement

The Pharmacogenomics Research Network Translational Pharmacogenetics Program: Outcomes and Metrics of Pharmacogenetic Implementations Across Diverse Healthcare Systems

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138257/1/cpt630-sup-0001-suppinfo1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138257/2/cpt630_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138257/3/cpt630.pd