Article ; Online: Development and Clinical Validation of a Hook Effect-Based Lateral Flow Immunoassay Sensor for Cerebrospinal Fluid Leak Detection.
2024
Abstract: Background and objectives: 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 ... ...
Abstract | Background and objectives: 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. Methods: 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. Results: 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. Conclusion: 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. |
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Language | English |
Publishing date | 2024-04-05 |
Publishing country | United States |
Document type | Journal Article |
ZDB-ID | 135446-2 |
ISSN | 1524-4040 ; 0148-396X |
ISSN (online) | 1524-4040 |
ISSN | 0148-396X |
DOI | 10.1227/neu.0000000000002914 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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