Journal
INFECTION
Volume 38, Issue 3, Pages 205-209Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s15010-010-0006-3
Keywords
Meningitis; Venticulitis; Nosocomial infection; Intensive care unit; Device-associated; Infection; Infection rate; Surveillance
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Data on time-dependency of external ventricular drainage (EVD)- and lumbar drainage (LD)-associated meningoventriculitis (MV) are scarce and discussions on the subject are controversial; no data exist for infection rates (IR) relative to drainage-days. For this reason, we conducted an observational study to determine time-dependent IRs and to perform a risk factor analysis. All patients (n = 210) requiring an EVD or LD during an 18-month period in 2007 and 2008 were enrolled and characterized. Data on type and duration of drainage, ICP measurement, number of drainage manipulations, hospital stay and time point of MV were analysed statistically. A total of 34 MV cases were reported with 17 for each kind of drainage accounting for an IR of 7.5 and 24.7 MV/1000 EVD- and LD-days, respectively. Of these, 28/34 MV (82%) occurred within the first 12 days, and IRs were highest between days 4 and 9. Longer drainage duration (> 5 and > 9 days, respectively) was correlated with a significant lower risk of MV (p = 0.03; p < 0.001). In this study, significant risk factors for MV were LD [vs. EVD, OR: 2.3 (1.1-4.7); p = 0.01], a previous MV [OR: 7.0 (2.1-23.3); p = 0.002], and neoplasm [OR: 11.6 (3.4-39); p = 0.001]. Simultaneous drainage, ICP and a previous drainage showed no influence on infection. To the best of our knowledge, this study is the first to provide data on time dependency of EVD- and LD-associated MV-IR based on drainage-days. However, because of the limited scale of our study, it would be desirable to confirm these results in a more powerful larger study. In conclusion, we recommend that future efforts should be made to better identify preventable risk factors as well as to define time periods of higher risk for the difficult-to-diagnose MV infection as a first step in profiling high risk patients.
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