Distributed lags time series analysis versus linear correlation analysis (Pearson's r) in identifying the relationship between antipseudomonal antibiotic consumption and the susceptibility of XXXX isolates in a single Intensive Care Unit of a tertiary hospital.

@entity796 @entity6944 @entity2177 @entity2889 @entity7120 @entity3400
The relationship between antibiotic consumption and selection of resistant strains has been studied mainly by employing conventional statistical methods. A time delay in effect must be anticipated and this has rarely been taken into account in previous studies. Therefore, distributed lags time series analysis and simple linear correlation were compared in their ability to evaluate this relationship. Data on monthly antibiotic consumption for @entity2177 , @entity3400 / @entity7120 , carbapenems and cefepime as well as @entity796 susceptibility were retrospectively collected for the period April 2006 to July 2007. Using distributed lags analysis, a significant temporal relationship was identified between @entity2177 , @entity2889 and cefepime consumption and the resistance rates of @entity796 isolates to these antibiotics. This effect was lagged for @entity2177 and @entity6944 [1 month (R=0.827, P=0.039) and 2 months (R=0.962, P=0.001), respectively] and was simultaneous for @entity2889 (lag 0, R=0.876, P=0.002). Furthermore, a significant concomitant effect of @entity2889 consumption on the appearance of multidrug-resistant @entity796 strains (resistant to three or more representatives of classes of antibiotics) was identified (lag 0, R=0.992, P<0.001). This effect was not delayed and it was therefore identified both by distributed lags analysis and the Pearson's correlation coefficient. Correlation coefficient analysis was not able to identify relationships between antibiotic consumption and bacterial resistance when the effect was delayed. These results indicate that the use of diverse statistical methods can yield significantly different results, thus leading to the introduction of possibly inappropriate infection control measures.
