ViResiST: its contribution to our knowledge of the relationship between antimicrobial use and resistance. Dominique L. Monnet

Transcription

1 ViResiST: its contribution to our knowledge of the relationship between antimicrobial use and resistance Dominique L. Monnet

2 About antibiotics... As soon as we use it, we loose it The more we use it, the more we loose it

3 The Antimicrobial Resistance Spiral ANTIMICROBIAL RESISTANCE 4 - Cross-transmission 1 - Concern 3 - Selection New antimicrobials (promotion) 2 - Broad-spectrum empiric therapy Antimicrobial resistance Dose Duration

4 Genetic Diversity and Adaptation 2010 Tautavel (France), approx. 450,000 years ago approx. 15,000 generations humans approx generations of 10 9 E. coli Adapted from: Geberding JL, CDC/NCID/HIP, Picture from: URL:

5 Illustration: Prittie EJ. Philadeplphia, PA: JC Winston, 1930.

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10 The Antimicrobial Resistance Spiral ANTIMICROBIAL RESISTANCE 1 - Concern New antimicrobials (promotion)? 4 - Cross-transmission 3 - Selection 2 - Broad-spectrum empiric therapy Antimicrobial resistance Dose Duration

11 Study designs for the relationship between antimicrobial use and resistance

12 Pharyngeal Carriage of Macrolide-Resistant Streptococci Following Exposure to Azithromycin and Clarithromycin Source: Malhotra-Kumar S, et al. Lancet 2007;369:

13 Cumulative Hazard Estimates for Emergence of Fluoroquinolone Resistance Following Fluoroquinolone Exposure 0.20 Probability of resistance Fluoroquinone exposed No fluoroquinolone Days Source: Harbarth S, et al. Clin Infect Dis 2001;33:

14 Fluoroquinolone Use and Ciprofloxacin-Resistant P. aeruginosa, SCOPE-MMIT Hospitals, % Ciprofloxacin-Resistant Pseudomonas aeruginosa (%) y = x R 2 = 0.29 p = Total Fluoroquinolone Use (Daily Doses per 1,000 patient-days) Source: Polk RE, et al. 41st ICAAC, Chicago (IL), 2001, late-breaker abstr. UL-1.

15 Retrospective Information to Guide Empiric Prescription of Antimicrobials Source: Snyder JW, Beam L. University of Louisville Hospital, Louisville (Kentucky), 1994.

16 Before ViResiST Bzzzz...

17 5-Month Moving Average Percent Imipenem- Resistant/Intermediate P. aeruginosa and Hospital Imipenem Use, Hospital Vega Baja, Spain, Average delay = 1 month % Imipenem-resistant/intermediate Pseudomonas aeruginosa Jan-91 Jul-91 Jan-92 1 DDD/1,000 pat-days %R Jul-92 Jan-93 Jul-93 Jan-94 Jul-94 Jan-95 Jul-95 Jan-96 Jul-96 Jan-97 Jul-97 Jan-98 Jul Hospital imipenem use (DDD/1,000 patient-days) Updated from: López-Lozano JM, et al. Int J Antimicrob Agents 2000;14: ViResiST

18 Applications of ViResiST in other hospitals

19 %Carbapenem-Resistant Pseudomonas aeruginosa and Carbapenem Use in 4 Hospitals, Univ. Hospital, Ulm (D) Lepper et al. AAC 2002;46: Univ. Hospital, Utah (USA) Samore MH, et al. Unpublished data. Average delay = 0-1 month Carbapenem-resistant P.aeruginosa(%) Jan-96 Jan-97 Jan-98 Jan-99 Jan-00 Jan Carbapenem use (DDD/100 pt-days) Average delay = 0-1 month Univ. Hospital, Antwerp (B) Goossens H, et al. Unpublished data. Centre Hosp. Mulhouse (F) Aujoulat O, Delarbre JM. ViResiST. Carbapenem-resistant P.aeruginosa(%) Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan Carbapenem use (DDD/100 pt-days) Average delay = 0-2 months Imipenem-resistant P.aeruginosa (%) Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan Carbapenem use (DDD/100 pt-days) Average delay = n.a.

20 %MRSA and Monthly Use of Macrolides, Third-Generation Cephalosporins and Fluoroquinolones, Aberdeen Royal Infirmary, 01/ /2001 Explaining variable for monthly %MRSA Lag (months) Estimated coefficient %MRSA Macrolide use 1,2, Third-generation cephalosporin use 4,5,6, Fluoroquinolone use 4, Constant R 2 =0.902 Source: Monnet DL, et al. Emerg Infect Dis 2004;10:

21 Multivariate time series models to explain hospital MRSA University of Geneva Hospitals, Antrim Area Hospital, Northern Ireland, Source: Vernaz N, et al. JAC 2008;62: ; Aldeyab MA, et al. JAC 2008;62:

22 What did ViResiST achieve? Confirmation of the relationship between antimicrobial use and resistance with new methodology using routine laboratory and pharmacy data Collection of longitudinal, electronic data from several hospitals in Europe Confirm the models with data from these European hospitals (generalisation) Acceptance of the methodology Transition from research to routine practice Use models in real time to guide prescriptions in order to beat resistance before it increases

23 With ViResiST! Beat the Bug B... B... Before B... B... it Bites

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