Development and Clinical Validation of a Hook Effect-Based Lateral Flow Immunoassay Sensor for Cerebrospinal Fluid Leak Detection

基于钩状效应的侧向流动免疫分析传感器在脑脊液泄漏检测中的开发和临床验证

阅读:1

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.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。