Oh, Hyun-Kyung, Park, Jinhee, Sonstein, William J, Maher, Simon and Kim, Min-Gon 
ORCID: 0000-0002-3525-0048
(2024)
Development and Clinical Validation of a Hook Effect-Based Lateral Flow Immunoassay Sensor for Cerebrospinal Fluid Leak Detection.
Neurosurgery.
Abstract
<h4>Background and objectives</h4>Rapid detection of cerebrospinal fluid (CSF) leaks is vital for patient recovery after spinal surgery. However, distinguishing CSF-specific transferrin (TF) from serum TF using lateral flow immunoassays (LFI) is challenging due to their structural similarities. This study aims to develop a novel point-of-care diagnostic assay for precise CSF leak detection by quantifying total TF in both CSF and serum.<h4>Methods</h4>Capitalizing on the substantial 100-fold difference in TF concentrations between CSF and serum, we designed a diagnostic platform based on the well-known "hook effect" resulting from excessive analyte presence. Clinical samples from 37 patients were meticulously tested using the novel LFI sensor, alongside immunofixation as a reference standard.<h4>Results</h4>The hook effect-based LFI sensor exhibited outstanding performance, successfully discriminating positive clinical CSF samples from negative ones with remarkable statistical significance (positive vs negative t-test; P = 1.36E-05). This novel sensor achieved an impressive 100% sensitivity and 100% specificity in CSF leak detection, demonstrating its robust diagnostic capabilities.<h4>Conclusion</h4>In conclusion, our study introduces a rapid, highly specific, and sensitive point-of-care test for CSF leak detection, harnessing the distinctive TF concentration profile in CSF compared with serum. This novel hook effect-based LFI sensor holds great promise for improving patient outcomes in the context of spinal surgery and postsurgical recovery. Its ease of use and reliability make it a valuable tool in clinical practice, ensuring timely and accurate CSF leak detection to enhance patient care.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Biotechnology, 4 Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies |
| Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 05 Apr 2024 13:54 |
| Last Modified: | 24 Apr 2024 06:00 |
| DOI: | 10.1227/neu.0000000000002914 |
| Open Access URL: | https://journals.lww.com/neurosurgery/fulltext/990... |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3180110 |
Dimensions
Dimensions
