Continuous glucose monitors have already demonstrated that real-time biochemical data can transform disease management — but cardiometabolic disease is far too complex to be captured by a single molecule. A sweeping narrative review in Frontiers in Bioengineering and Biotechnology now maps what it would take to extend that monitoring paradigm to a full constellation of physiologically relevant signals, and the implications for how clinicians and individuals track heart-metabolic health could be substantial.
The review frames cardiometabolic disease as a multi-pathway disorder requiring simultaneous surveillance of metabolic substrates, hormonal signals, and immune mediators. The authors propose tracking lactate, ketones, uric acid, and electrolytes alongside glucose as metabolic markers; cortisol and catecholamines as stress-axis readouts; and cytokines alongside acute-phase proteins and selected cardiac biomarkers as inflammatory and cardiac stress signals. Two technical frameworks are evaluated in parallel: biomarker biology (which analytes matter most and why) and device architecture (sweat patches, microneedle-based interstitial fluid sensors, and fully implantable platforms). The central argument is that the regulatory and clinical pathway carved out by continuous glucose monitoring provides a replicable blueprint for this expansion.
This is an ambitious but largely aspirational roadmap. Most of the analytes discussed — particularly cortisol, cytokines, and cardiac markers — present formidable engineering challenges: low physiological concentrations, matrix interference in sweat or interstitial fluid, signal drift, and uncertain correlation between peripheral fluid levels and circulating plasma values. The field's track record outside of glucose remains thin; few multi-analyte wearables have cleared regulatory scrutiny or demonstrated clinical utility in prospective trials. That said, convergent advances in affinity-based electrochemical sensing, flexible electronics, and microfluidics are genuinely accelerating the timeline. As a narrative review rather than a systematic analysis or meta-analysis, this work synthesizes existing evidence without quantitative pooling, and its conclusions carry the limitations inherent to that design. Still, as a structured intellectual framework for where the field must go, it adds real value for researchers, clinicians, and health-technology developers navigating this rapidly evolving space.