Kidney Week

Abstract: FR-PO0529

Noninvasive Metabolic-Autonomic Phenotyping Using Skin Autofluorescence and Fractal Heart Rate Dynamics for Risk Stratification in Diabetic Kidney Disease

Session Information

• CKM: Clinical - Trials, Epidemiology, and Biomarkers
  October 23, 2026 | Location: Exhibit Hall A, Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Cardiovascular-Kidney-Metabolic Health

• 602 Cardiovascular-Kidney-Metabolic Health: Clinical

Authors

• Tran, Hien Ngoc, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Viet Nam

Hien Ngoc Tran, MD

• Le, Nhan Trong, Hong Bang International University, Ho Chi Minh City, Viet Nam

Nhan Trong Le, MD, MSc

• Le, Tuan Quoc, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Viet Nam

Tuan Quoc Le

Background

Diabetic kidney disease (DKD) remains the leading cause of chronic kidney disease worldwide. Standard markers such as albuminuria and eGFR incompletely capture the pathophysiological complexity underlying renal decline. Skin autofluorescence (SAF), a non-invasive measure of tissue advanced glycation end-product accumulation, and detrended fluctuation analysis short-term exponent (DFA-α1), a fractal index of cardiac autonomic regulation, have each been linked to adverse renal outcomes. However, their combined phenotypic value for identifying high-risk DKD subgroups has not been evaluated.

Methods

In this cross-sectional study, 104 adults with type 2 diabetes underwent non-invasive assessment of SAF (AGE Reader) and short-term heart rate variability (Polar H10; Kubios HRV Premium). A composite nonlinear HRV score was derived from DFA-α1, approximate entropy, and sample entropy using principal component analysis. Participants were classified into four phenotypes by median split of SAF and HRV score: Low SAF–High HRV (reference), Low SAF–Low HRV, High SAF–High HRV, and High SAF–Low HRV. Renal impairment was defined as eGFR <60 mL/min/1.73 m² (CKD-EPI creatinine–cystatin C). Logistic regression examined associations between phenotypes and reduced eGFR, adjusted for age and sex.

Results

The High SAF–Low HRV phenotype exhibited markedly elevated odds of reduced eGFR compared with the reference group (unadjusted OR 4.30, 95% CI 1.17–15.85, p=0.028). After adjustment for age and sex, the association remained substantial (OR 3.34, 95% CI 0.80–13.90), with confidence interval attenuation attributable to modest sample size. No consistent associations were observed for other phenotypes. Sensitivity analyses using creatinine-based eGFR yielded concordant findings.

Conclusion

A joint metabolic–autonomic phenotyping approach using SAF and nonlinear HRV identifies a distinct high-risk subgroup among adults with T2DM characterized by elevated odds of reduced eGFR. These findings highlight the potential of integrating non-invasive metabolic and autonomic indices for early renal risk stratification in DKD. Validation in larger, prospective cohorts is warranted.