Indicators of external ventricular drainage-related infections--a retrospective observational study.

Wiegand, Jan; Hickson, Liz; Merz, Tobias Michael (2016). Indicators of external ventricular drainage-related infections--a retrospective observational study. Acta neurochirurgica, 158(3), pp. 595-601. Springer 10.1007/s00701-016-2709-4

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BACKGROUND

External ventricular drainage (EVD) is frequently used in different groups of patients in neurocritical care. Despite the frequent use of EVD, no consensus regarding the diagnosis of EVD-related infection currently exists, and diagnosis is commonly based on criteria for the diagnosis of non-EVD-related CNS infections. This study evaluates the diagnostic accuracy of clinical and laboratory parameters for the prediction of EVD-related infection in patients with proven EVD-related infection.

METHODS

In two tertiary care centers, data on EVD insertions were matched with a microbiologic database of cultured microorganisms and positive Gram stains of cerebrospinal fluid (CSF) to identify patients with EVD-related infections. Available clinical data and results of blood tests and CSF analysis were retrospectively collected. Predefined potential clinical and laboratory predictors of EVD-related infection were compared between three time points: at the time EVD insertion and 48 h before and at the time of occurrence of EVD-related infection.

RESULTS

Thirty-nine patients with EVD-associated infection defined by positive CSF culture or positive CSF Gram stains and concomitant clinical signs of infection were identified. At the time of infection, a significantly higher incidence of abnormal temperature, high respiratory rate, and a slightly but significantly higher incidence of decreased mental state were observed. The assessed blood and CSF parameters did not significantly differ between the different assessment time points.

CONCLUSIONS

Our analysis of 39 patients with culture positive EVD-related infection showed that commonly used clinical and laboratory parameters are not reliable infection predictors.

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