Urine Cofilin-1 Detection for Predicting Type 1 Cardiorenal Syndrome in the Coronary Care Unit: A Gold Nanoparticle- and Laser-Based Approach

尿液 Cofilin-1 检测用于预测冠心病监护室中的 1 型心肾综合征:基于金纳米粒子和激光的方法

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作者:Hsing-Yu Chen, Chien Chou, Chih-Hsiang Chang, Nien-Gen Lee, Pei-Chun Yu, Yu-Chi Chen, Heng-Chih Pan, Pei-Chun Fan, Chih-Wei Yang, Wen-Jin Cherng, Yung-Chang Chen

Background

Type 1 cardiorenal syndrome (CRS) is a severe complication for acute decompensated heart failure patients. This study aimed at evaluating the feasibility of using the gold nanoparticle-based localized surface plasmon-coupled fluorescence biosensor (LSPCFB) to detect urine cofilin-1 as a biomarker for predicting CRS among patients in the coronary care unit (CCU).

Conclusions

The gold nanoparticle-based immunoassay LSPCFB could exploit the potential of urine cofilin-1 as a single biomarker to predict CRS among CCU patients.

Methods

A total of 44 patients were included with prospectively collected urine and blood samples. Both LSPCFB and conventional enzyme-linked immunosorbent assays (ELISAs) were used to measure urine cofilin-1 at admission to the CCU. The occurrence of CRS was judged within 7 days after admission. The discrimination presented as the area under the receiver operating characteristic curve (AUROC) and calibration of both detection methods were used to assess the predictive ability of urine cofilin-1 measured by the LSPCFB and ELISA.

Results

Thirteen patients were diagnosed with CRS, while the other 31 patients were classified into a non-CRS group. For predicting CRS by measuring urine cofilin-1, the LSPCFB had higher accuracy (AUROC: 0.707, p = 0.031; overall accuracy: 79.55%) than the ELISA (AUROC: 0.479, p = 0.827; overall accuracy: 53.27%). The positive and negative predictive values of the LSPCFB were also higher than those of the ELISA (positive predictive value: 70.0 vs. 34.8%; negative predictive value: 82.4 vs. 76.2%). Conclusions: The gold nanoparticle-based immunoassay LSPCFB could exploit the potential of urine cofilin-1 as a single biomarker to predict CRS among CCU patients.

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