Elisabeth Meyer1, Frank Schwab, Petra Gastmeier, Henning Ruden, Alexandra Heininger. 1. Institute of Environmental Medicine and Hospital Epidemiology, University Medical Centre Freiburg, Freiburg University Hospital, Breisacher Str. 115B, 79106 Freiburg, Germany. elisabeth.meyer@uniklinik-freiburg.de
Abstract
OBJECTIVES: To provide benchmarking data on antifungal use in intensive care units (ICUs), to analyse risk factors and to look for correlations with antibiotic use data and structure parameters. METHODS: Antimicrobial use data for 13 ICUs were obtained from computerized databases from January 2004 through June 2005. Antimicrobial usage density (AD) is expressed as daily defined doses/1000 patient-days. Correlations were calculated by the Spearman correlation or for binomic variables by the two-sided Wilcoxon test. A multivariate regression analysis was performed to identify independent risk factors for the outcome 'antifungal use'. RESULTS: Mean systemic antifungal drug use was 93.0, the range being between ADs of 18.9 and 232.2. ICUs treating transplant patients had a significantly higher mean antifungal usage at 152.9 compared with ICUs not treating transplant patients where the AD was 46.0. Fluconazole was the most frequently prescribed antifungal (mean AD 69.6) followed by amphotericin B (11.4) and voriconazole (6.2). Antifungal use correlated significantly with the consumption of quinolones, carbapenems and extended-spectrum penicillins, but not with total antibiotic use and not with the type of ICU or university status. In the multivariate linear regression analysis, two parameters, i.e. high quinolone use (P = 0.002) and ICUs which treat transplant patients (P = 0.027), were independent risk factors for a high level of antifungal use. CONCLUSIONS: Antifungal use was heterogeneous in German ICUs with the mean AD lying at 93. Benchmarking data might provide a useful method for assessing strategies that aim to reduce antifungal use in ICUs. However, data should be stratified for ICUs with and without transplant patients.
OBJECTIVES: To provide benchmarking data on antifungal use in intensive care units (ICUs), to analyse risk factors and to look for correlations with antibiotic use data and structure parameters. METHODS: Antimicrobial use data for 13 ICUs were obtained from computerized databases from January 2004 through June 2005. Antimicrobial usage density (AD) is expressed as daily defined doses/1000 patient-days. Correlations were calculated by the Spearman correlation or for binomic variables by the two-sided Wilcoxon test. A multivariate regression analysis was performed to identify independent risk factors for the outcome 'antifungal use'. RESULTS: Mean systemic antifungal drug use was 93.0, the range being between ADs of 18.9 and 232.2. ICUs treating transplant patients had a significantly higher mean antifungal usage at 152.9 compared with ICUs not treating transplant patients where the AD was 46.0. Fluconazole was the most frequently prescribed antifungal (mean AD 69.6) followed by amphotericin B (11.4) and voriconazole (6.2). Antifungal use correlated significantly with the consumption of quinolones, carbapenems and extended-spectrum penicillins, but not with total antibiotic use and not with the type of ICU or university status. In the multivariate linear regression analysis, two parameters, i.e. high quinolone use (P = 0.002) and ICUs which treat transplant patients (P = 0.027), were independent risk factors for a high level of antifungal use. CONCLUSIONS: Antifungal use was heterogeneous in German ICUs with the mean AD lying at 93. Benchmarking data might provide a useful method for assessing strategies that aim to reduce antifungal use in ICUs. However, data should be stratified for ICUs with and without transplant patients.
Authors: E Ramírez; J García-Rodríguez; A M Borobia; J M Ortega; S Lei; A Barrios-Fernández; M Sánchez; A J Carcas; A Herrero; J M de la Puente; J Frías Journal: Eur J Clin Microbiol Infect Dis Date: 2011-07-01 Impact factor: 3.267
Authors: M Ruhnke; J A Paiva; W Meersseman; J Pachl; I Grigoras; G Sganga; F Menichetti; P Montravers; G Auzinger; G Dimopoulos; M Borges Sá; P J Miller; T Marček; M Kantecki Journal: Clin Microbiol Infect Date: 2012-03-08 Impact factor: 8.067