Multiplexed Lateral Flow Immunoassay with Catalytic Signal Amplification for Simultaneous Quantitative Detection of Five Cardiac Biomarkers in Acute Chest Pain Triage

Abstract

Acute chest pain is a life-threatening clinical emergency requiring rapid differentiation of acute myocardial infarction (AMI), acute aortic dissection (AAD), and pulmonary embolism (PE). Conventional diagnostics are limited by bulky equipment, delayed processing, and insufficient specificity. We developed a portable dual-readout lateral flow immunoassay (Multi-AuPd@Fe_xO_y-LFIA) for one-step identification of high-risk acute chest pain etiologies, enabling simultaneous determination of five key biomarkers: soluble suppression of tumorigenicity 2 (sST2), D-Dimer, cardiac troponin I (cTnI), myoglobin (MYO), and C-reactive protein (CRP). A 3D-printed smartphone cradle and APP enabled automated signal readout. The multi-AuPd@Fe_xO_y-LFIA exhibits low limits of detection (LODs) of 0.036 ng/mL (sST2), 0.008 µg/mL (D-Dimer), 0.017 ng/mL (cTnI), 0.732 ng/mL (MYO), and 3.327 µg/mL (CRP). Based on the analysis of the concentrations of the five biomarkers in 137 clinical plasma samples, least absolute shrinkage and selection operator (LASSO) machine learning establishes a four-category classification model, with areas under curves (AUCs) reaching 0.99–1.00 for distinguishing healthy donors, AMI, AAD, and PE. The established machine learning diagnostic algorithm is further integrated into the App, enabling Multi-AuPd@Fe_xO_y-LFIA to achieve quantitative detection and early differential diagnosis of acute chest pain.

Keywords

Lateral flow immunoassay / Nanozyme / Acute chest pain / Multiplexed biomarker detection / Machine learning / Point-of-care testing

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