External Ventricular Drains and Infection Risk: Duration as the Dominant Predictor—A Systematic Review and Meta-Analysis

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Abstract
Background/Objectives: External ventricular drains (EVDs) are widely used in the management of intracranial hemorrhage and hydrocephalus; however, they carry a significant risk of device-related central nervous system infections, including ventriculitis and meningitis, which are associated with increased morbidity, mortality, and prolonged intensive care stays. We conducted a systematic review and meta-analysis to evaluate whether prolonged EVD duration (>10 days) is associated with an increased risk of ventriculostomy-related infection compared with shorter duration (≤10 days), and to explore the association with cerebrospinal fluid (CSF) leak where data were available. Methods: A comprehensive literature search of PubMed, Google Scholar, Web of Science, and Cochrane CENTRAL was performed from database inception through September 2025, including English-language clinical trials, cohort studies, and case–control studies reporting infection outcomes related to EVD management factors. Two reviewers independently screened studies and extracted data. A random-effects meta-analysis was conducted to calculate pooled odds ratios (ORs) with 95% confidence intervals (CIs). Results: Sixteen studies comprising approximately 5500 patients met the inclusion criteria. Shorter EVD duration (≤10 days) was associated with a significantly lower risk of infection (pooled OR 0.45, 95% CI 0.30–0.68; p = 0.0002), corresponding to a 55% reduction in the odds of ventriculostomy-related infection. Prolonged EVD duration was consistently associated with increased infection risk across studies. Conclusions:These findings suggest that minimizing EVD duration may reduce infection risk and support early removal when clinically feasible. However, given the observational nature of the included studies, the results should be interpreted with caution. Further research is warranted to evaluate additional modifiable risk factors, including CSF leakage and sampling practices.

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