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|Title: ||Exploring the association between resistance and outpatient antibiotic use expressed as DDDs or packages|
|Authors: ||BRUYNDONCKX, Robin|
CORTIÑAS ABRAHANTES, José
|Issue Date: ||2015|
|Citation: ||JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY, 70 (4), p. 1241-1244|
|Abstract: ||Objectives: The objective of this study was to explore the association between resistance and outpatient antibiotic use, expressed as either DDDs per 1000 inhabitants per day (DID) or packages per 1000 inhabitants per day (PID).
Methods: IMS Health data on outpatient penicillin and cephalosporin (β-lactam) and tetracycline, macrolide, lincosamide and streptogramin (TMLS) use, aggregated at the level of the active substance (WHO version 2011) expressed as DID and PID (2000–07) were linked to European Antimicrobial Resistance Surveillance System (EARSS) data on proportions of penicillin-non-susceptible Streptococcus pneumoniae (PNSP) and erythromycin-non-susceptible S. pneumoniae (ENSP) (2000–09). Combined data for 27 European countries were analysed with a generalized linear mixed model. Model fit for use in DID, PID or both and 0, 1 or 2 year time lags between use and resistance was assessed and predictions of resistance were made for decreasing use expressed as DID, PID or both.
Results: When exploring the association between β-lactam use and PNSP, the best model fit was obtained for use in PID without time lag. For the association between TMLS use and ENSP, the best model fit was obtained for use in both PID and DID with a 1 year time lag. PNSP and ENSP are predicted to decrease when use decreases in PID, but not when use decreases in DID.
Conclusions: Associations between outpatient antibiotic use and resistance and predictions of resistance were inconsistent whether expressing antibiotic use as DID or PID. We recommend that data on antibiotic use be expressed as PID and that time lags between use and resistance be considered when exploring these associations.|
|Notes: ||Corresponding author. Tel: +32-11-268246; Fax: +32-11-268299; E-mail: email@example.com|
|ISI #: ||000354708600042|
|Type: ||Journal Contribution|
|Validation: ||ecoom, 2016|
|Appears in Collections: ||Research publications|
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