Rapid Diagnostic Test Kit for Point-of-Care Cerebrospinal Fluid Leak Detection.

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ID: 52098
2019
Article Quality & Performance Metrics
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Abstract
Cerebrospinal fluid (CSF) leaks can occur when there is communication between the intracranial cavities and the external environment. They are a common and serious complication of numerous procedures in otolaryngology, and if not treated, persistent leaks can increase a patient's risk of developing life-threatening complications such as meningitis. As it is not uncommon for patients to exhibit increased secretions postoperatively, distinguishing normal secretions from those containing CSF can be difficult. Currently, there are no proven, available tests that allow a medical provider concerned about a CSF leak to inexpensively, rapidly, and noninvasively rule out the presence of a leak. The gold standard laboratory-based test requires that a sample be sent to a tertiary site for analysis, where days to weeks may pass before results return. To address this, our group recently developed a semiquantitative, barcode-style lateral-flow immunoassay (LFA) for the quantification of the beta-trace protein, which has been reported to be an indicator of the presence of CSF leaks. In the work presented here, we created a rapid diagnostic test kit composed of our LFA, a collection swab, dilution buffers, disposable pipettes, and instructions. Validation studies demonstrated excellent predictive capabilities of this kit in distinguishing between clinical specimens containing CSF and those that did not. Our diagnostic kit for CSF leak detection can be operated by an untrained user, does not require any external equipment, and can be performed in approximately 20 min, making it well suited for use at the point of care. This kit has the potential to transform patient outcomes.
Reference Key
bradbury2019rapidslas Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Bradbury, Daniel W;Kita, Ashley E;Hirota, Kensuke;St John, Maie A;Kamei, Daniel T;
Journal slas technology
Year 2019
DOI
10.1177/2472630319877377
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