Electrochemical detection of cardiovascular diseases and treatment platform based on microfluidic technology

Cardiovascular diseases (CVDs) have recently exhibited a younger age of onset, along with high incidence and mortality rates, posing a severe threat to human health. Traditional clinical laboratory diagnostic methods for CVDs are time-consuming and labor-intensive, relying heavily on specialized equipment and professional personnel, which limits their efficiency and accessibility. In contrast, electrochemical technology offers inherent advantages in terms of high sensitivity and simple detection procedures, while microfluidic chips - characterized by miniaturization, integration, low sample consumption, and the ability to simulate biomimetic microenvironments - provide an innovative technical platform for addressing the unmet needs in precise diagnosis and treatment of CVDs. This review first summarizes the research progress of electrochemical technology in the detection of key cardiovascular biomarkers, including blood lipid-related indicators, cardiac troponin, and myoglobin. It covers major sensing strategies such as enzymatic/non-enzymatic catalytic sensing and immuno/aptamer-based detection, highlighting their potential for rapid and accurate diagnosis. Secondly, in the context of therapeutic applications, the review elaborates on how microfluidic technology enables the simulation of pathological scenarios and high-throughput drug screening through the construction of biomimetic models (e.g., vascular chips and heart chips). Furthermore, the combination of microfluidic technology with nanocarrier-based drug delivery systems is discussed, which can optimize targeted delivery efficiency and controlled release of therapeutic agents. Looking forward, microfluidic electrochemical technology is expected to develop towards intelligent multi-biomarker detection, integration of organ-on-a-chip systems, and personalized diagnosis and treatment platforms. By integrating interdisciplinary technologies, this field will promote the upgrading of CVD management from conventional detection to precise simulation-guided personalized treatment, ultimately providing new strategies for reducing the global burden of CVDs.