Utility of the Cell Index in Predicting External Ventricular Drain-Related Ventriculo-Meningitis.

Abstract

Ventriculo-meningitis (VM) is an important complication of external ventricular drains (EVDs) in neurosurgical patients. Consequences include increased morbidity, mortality, and duration of hospital stay. Early diagnosis of EVD-associated VM allows earlier treatment intervention. The cell index (CI) may provide a simple measure that overcomes the limitations of isolated cerebrospinal fluid (CSF) parameters and other diagnostic tests, allowing earlier prediction of VM. All patients admitted to a tertiary hospital and requiring EVD insertion during 2015 and 2016 were assessed for inclusion in this retrospective case-control study. Patients with a known or suspected intracranial infection were excluded. Of the 186 patients who underwent EVD insertion, 95 patients were included in the final cohort. Data pertaining to patient characteristics and laboratory indices were extracted from health records and the microbiology laboratory database. The CI was calculated as the ratio of temporally related CSF leukocytes/erythrocytes to peripheral blood leukocytes/erythrocytes. Data from patients with microbiologically confirmed VM were analyzed in comparison with those not developing VM during the course of their stay. Categorical and continuous variables with skewed distributions were analyzed by Chi square and Mann-Whitney tests, respectively. EVD-associated VM developed in 7.4% of patients. The highest CSF CI (within 3days prior to diagnosis of VM or at any time for those not developing VM) differed significantly between the two groups (16; IQR 10.8-48.5 vs. 3.3; IQR 1.0-12.8, respectively; p = .046). The area under the receiver operating characteristic curve (AUROC) for the highest CI was 0.727 (95% confidence interval [CI] 0.526-0.929; p = .027). A CI of 10.4 provided a sensitivity and specificity of 80.5% and 70.5%, respectively, for the early diagnosis of VM. In neurosurgical patients with an EVD, the CSF CI significantly predicted the development of VM.