BACKGROUND: In haematology/oncology units, the frequent and heavy use of broad-spectrum antimicrobials can lead to outbreaks of antimicrobial resistance. Increasing antimicrobial heterogeneity might be a useful strategy for preventing such resistance. METHODS: A real-time antimicrobial use density (AUD) monitoring system (RAMS) was developed to precisely assess antimicrobial heterogeneity. This study was prospectively conducted over a 39 month period and involved 970 patients. Patient-specific antimicrobial therapy with five carbapenems (meropenem, biapenem, panipenem/betamipron, imipenem/cilastatin and doripenem) and four non-carbapenems (piperacillin/tazobactam, ceftazidime, cefozopran and cefepime) was prescribed in the first 12 months. A first-line antimicrobial was selected from among nine antimicrobials according to a predetermined schedule for the next 15 months. AUD-based antimicrobial selection was implemented using the RAMS during the last 12 months. We compared our findings for the RAMS period with those for the other periods to determine the effects of RAMS-based AUD monitoring on antimicrobial resistance. RESULTS: The mean absolute difference between the AUD values of carbapenems and non-carbapenems (AUD deviation) was 6.0% in the RAMS period (range 0.5%-15.8%) and antimicrobial heterogeneity (AUD deviation <10%) was achieved in 10 out of 12 months (83.3%). Furthermore, during the RAMS period, AUD deviation was significantly smaller and the frequency of outbreaks of antimicrobial-resistant strains other than Stenotrophomonas maltophilia was significantly decreased (from 7.9% to 3.5%; P < 0.01) compared with the other periods. CONCLUSIONS: The longer period of stable antimicrobial heterogeneity achieved by the RAMS strengthened its preventive effects against antimicrobial resistance. Optimal antimicrobial heterogeneity based on real-time AUD monitoring could reduce the frequency of outbreaks of antimicrobial resistance.
BACKGROUND: In haematology/oncology units, the frequent and heavy use of broad-spectrum antimicrobials can lead to outbreaks of antimicrobial resistance. Increasing antimicrobial heterogeneity might be a useful strategy for preventing such resistance. METHODS: A real-time antimicrobial use density (AUD) monitoring system (RAMS) was developed to precisely assess antimicrobial heterogeneity. This study was prospectively conducted over a 39 month period and involved 970 patients. Patient-specific antimicrobial therapy with five carbapenems (meropenem, biapenem, panipenem/betamipron, imipenem/cilastatin and doripenem) and four non-carbapenems (piperacillin/tazobactam, ceftazidime, cefozopran and cefepime) was prescribed in the first 12 months. A first-line antimicrobial was selected from among nine antimicrobials according to a predetermined schedule for the next 15 months. AUD-based antimicrobial selection was implemented using the RAMS during the last 12 months. We compared our findings for the RAMS period with those for the other periods to determine the effects of RAMS-based AUD monitoring on antimicrobial resistance. RESULTS: The mean absolute difference between the AUD values of carbapenems and non-carbapenems (AUD deviation) was 6.0% in the RAMS period (range 0.5%-15.8%) and antimicrobial heterogeneity (AUD deviation <10%) was achieved in 10 out of 12 months (83.3%). Furthermore, during the RAMS period, AUD deviation was significantly smaller and the frequency of outbreaks of antimicrobial-resistant strains other than Stenotrophomonas maltophilia was significantly decreased (from 7.9% to 3.5%; P < 0.01) compared with the other periods. CONCLUSIONS: The longer period of stable antimicrobial heterogeneity achieved by the RAMS strengthened its preventive effects against antimicrobial resistance. Optimal antimicrobial heterogeneity based on real-time AUD monitoring could reduce the frequency of outbreaks of antimicrobial resistance.
Authors: In Young Jung; Jung Ju Kim; Se Ju Lee; Jinnam Kim; Hye Seong; Wooyong Jeong; Heun Choi; Su Jin Jeong; Nam Su Ku; Sang Hoon Han; Jun Yong Choi; Young Goo Song; Jung Won Park; June Myung Kim Journal: Biomed Res Int Date: 2017-12-31 Impact factor: 3.411