Early autonomic dysfunction may vary across metabolic risk states in individuals without overt diabetes. An exploratory pilot study published in Frontiers in Endocrinology examined whether continuous glucose monitoring (CGM)-derived glycemic metrics or broader metabolic risk better reflect early neural impairment.

The analysis included 41 participants categorized as controls (Finnish Diabetes Risk Score [FINDRISC] <12; n=12), increased risk of prediabetes (HbA1c <5.7% with FINDRISC ≥12; n=14), and prediabetes (HbA1c 5.70–6.49%; n=15). Associations between metabolic status, CGM-derived metrics, and autonomic function indices, including root mean square of successive differences (RMSSD), percentage of adjacent NN intervals differing by >50 ms (pNN50), and expiration-to-inspiration (E/I) ratio, were assessed using regression models. Cardiac autonomic neuropathy (CAN) was evaluated using logistic regression.

CAN was identified in 16 participants (39%). Age showed a borderline relationship with CAN (odds ratio [OR] 1.06 per year; p=0.059), which attenuated after adjustment for metabolic status. Increased prediabetes risk (OR ~8.4) and prediabetes (OR ~7.0) were examined in relation to CAN independent of age, although confidence intervals were wide. Among CGM-derived measures, only mean interstitial glucose differed across metabolic groups, while no glycemic marker showed a relationship with CAN.

These findings indicate that autonomic dysfunction in early metabolic states may align more closely with metabolic risk status rather than short-term glycemic variability.