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Life sciences · Journal article
The Egyptian Journal of Internal Medicine · September 9, 2026
A consensus or society position rather than new primary data.
This is a narrative review of continuous biosensing technologies—including CGM, CKM, wearable sweat sensors, microneedle devices, and implantable biosensors—for real-time metabolic monitoring in obesity, type 2 diabetes, and diabetic kidney disease. The review distinguishes clinically established platforms (CGM) from early translational technologies and identifies key barriers to implementation: CKD-specific validation, clinically actionable thresholds, regulatory approval, interoperability, reimbursement, and equitable access.
Journal article. Patients with obesity, type 2 diabetes mellitus, and diabetic kidney disease (DKD) at risk for chronic kidney disease and kidney failure.
HbA1c becomes progressively less reliable in advanced CKD due to anaemia, altered erythrocyte turnover, iron therapy, erythropoiesis-stimulating treatment, transfusion, and related factors distorting its relationship with mean glucose Continuous biosensor platforms enable real-time monitoring of glucose, ketones, and other metabolic and kidney-relevant biomarkers, creating opportunities for precision diabetes and kidney care Established and emerging platforms discussed include continuous glucose monitoring (CGM), continuous ketone monitoring (CKM), wearable sweat biosensors, microneedle-based devices, and implantable biosensors
No original efficacy or safety data provided; no comparative effectiveness metrics reported No quantified evidence on clinical outcomes (e.g., reduction in hypoglycaemic episodes, kidney disease progression, mortality) reported
Clinicians should be aware that traditional markers (HbA1c, creatinine, albuminuria) provide only intermittent assessment and that HbA1c is unreliable in advanced CKD. Continuous biosensing offers promise for real-time metabolic monitoring and precision care, but widespread clinical adoption requires validation specific to CKD populations, clear actionable thresholds, regulatory clearance, and solutions to interoperability and reimbursement challenges.
A narrative review synthesizing established and emerging biosensor technologies for diabetes and kidney disease monitoring, offering expert perspective on clinical applications and implementation barriers rather than reporting original research evidence.
Clinicians should be aware that traditional markers (HbA1c, creatinine, albuminuria) provide only intermittent assessment and that HbA1c is unreliable in advanced CKD. Continuous biosensing offers promise for real-time metabolic monitoring and precision care, but widespread clinical adoption requires validation specific to CKD populations, clear actionable thresholds, regulatory clearance, and solutions to interoperability and reimbursement challenges.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
What is missing. This record has no reported figures. That is a gap in the analysis, not a judgement about the study.
Abstract Diabetic kidney disease (DKD), a major complication of obesity and type 2 diabetes mellitus, is a leading cause of chronic kidney disease and kidney failure worldwide. Optimal management requires timely assessment of glycaemic status, metabolic instability, and cardiorenal risk; however, traditional monitoring tools such as glycated haemoglobin (HbA1c), serum creatinine, and albuminuria provide only intermittent assessments, while HbA1c becomes progressively less reliable in advanced CKD because anaemia, altered erythrocyte turnover, iron therapy, erythropoiesis-stimulating treatment, transfusion, and related factors can distort its relationship with mean glucose. Recent advances in biosensor technologies enable continuous, real-time monitoring of glucose, ketones, and other metabolic and kidney-relevant biomarkers, creating new opportunities for precision diabetes and kidney care. In this Review, we discuss established and emerging platforms, including continuous glucose monitoring (CGM), continuous ketone monitoring (CKM), wearable sweat biosensors, microneedle-based devices, and implantable biosensors. We distinguish clinically established applications from early translational technologies and highlight their potential roles in hypoglycaemia detection, metabolic safety during sodium-glucose cotransporter 2 inhibitor therapy, and individualized treatment. Integration with digital health and artificial intelligence may further support dynamic risk assessment, although CKD-specific validation, clinically actionable thresholds, regulatory approval, interoperability, reimbursement, and equitable implementation remain important barriers.
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