Assessment of the intermuscular coherence for the early detection of diabetic peripheral neuropathy: a cross-sectional study

• Early-stage DPN showed increased coherence values compared to controls. • Advanced DPN stages exhibited reduced coherence values compared to controls. • The dorsiflexor muscle pair (10–50 Hz PDC) distinguishes all DPN stages significantly. • Synergistic muscles presented significant coherences in comparison to non-synergistic. Diabetes mellitus (DM) is a global epidemic marked by chronic hyperglycaemia due to insulin insufficiency or resistance. Diabetic peripheral neuropathy (DPN) is a common complication of diabetes, affecting up to 50 % of patients. It typically presents as a distal, symmetric, length-dependent neuropathy. Early detection of DPN is crucial to mitigate its impact on quality of life and healthcare costs. While current diagnostic methods like nerve conduction studies have limitations, surface electromyography (sEMG) shows promise for its non-invasive, real-time neuromuscular assessments. This study explores the potential of sEMG, particularly through intermuscular coherence, to serve as a sensitive biomarker for early DPN detection. Two coherence parameters, partial coherence (PC) and partial directed coherence (PDC), based on the Multivariate Autoregressive (MVAR) models have been analysed in three population groups: 33 healthy volunteers (CT), 10 diabetic patients with a low risk of DPN (LW), and 17 moderate/high-risk patients (MH). In early-stage DPN, synergistic muscle pairs showed increased PC and PDC values compared to controls, likely due to neuronal hyperexcitability and compensatory mechanisms within the nervous system. In contrast, advanced DPN stages exhibited reduced coherence, reflecting nerve fiber loss and central nervous system (CNS) impairment, possibly exacerbated by structural CNS changes like spinal cord atrophy, affecting neural plasticity and adaptation. Our study found that the dorsiflexor muscle pair, especially in the bandwidth 10–50 Hz of the PDC parameter, effectively discriminated between DPN stages, distinguishing all three groups with statistical significance. This suggests its potential as an early detection biomarker for DPN and for monitoring disease progression.