Matti D Allen1, Daniel W Stashuk2, Kurt Kimpinski3, Timothy J Doherty4, Maddison L Hourigan5, Charles L Rice6. 1. School of Kinesiology, Faculty of Health Sciences, University of Western Ontario, London, Ontario, Canada. Electronic address: mallen9@uwo.ca. 2. Systems Design Engineering, University of Waterloo, Canada. 3. Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada. 4. School of Kinesiology, Faculty of Health Sciences, University of Western Ontario, London, Ontario, Canada; Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada; Department of Physical Medicine and Rehabilitation, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada. 5. Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada. 6. School of Kinesiology, Faculty of Health Sciences, University of Western Ontario, London, Ontario, Canada; Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada.
Abstract
OBJECTIVE: To assess the degree of neuromuscular transmission variability and motor unit (MU) remodelling in patients with diabetic polyneuropathy (DPN) using decomposition-based quantitative electromyography (DQEMG) and near fibre (NF) motor unit potential (MUP) parameters. METHODS: The tibialis anterior (TA) muscle was tested in 12 patients with DPN (65 ± 15 years) and 12 controls (63 ± 15 years). DQEMG was used to analyze electromyographic (EMG) signals collected during voluntary contractions. MUP and NF MUP parameters were analyzed. NF MUPs were obtained by high-pass filtering MUP template waveforms, which isolates contributions of fibres that are close to the needle detection surface. NF MUP parameters provided assessment of motor unit size (NF area), fibre density (NF fibre count) and contribution dispersion (NF dispersion) and neuromuscular transmission instability (NF jiggle). RESULTS: DPN patients had larger (+45% NF area), more complex (+30% NF fibre count), and less stable (+30% NF jiggle) NF MUPs (p<0.05). No significant relationships were found between NF MUP stability and denervation, or strength; however NF MUP complexity was positively related to TA denervation in the DPN group (r=0.63; p<0.05). NF MUP complexity and instability were positively related in DPN patients (r=0.46; p<0.05). CONCLUSIONS: DPN is associated with neuromuscular transmission instability and MU remodelling that can be assessed using DQEMG. SIGNIFICANCE: DQEMG-derived NF MUP parameters may be useful in identifying patients in early stages of neuromuscular dysfunction related to DPN.
OBJECTIVE: To assess the degree of neuromuscular transmission variability and motor unit (MU) remodelling in patients with diabetic polyneuropathy (DPN) using decomposition-based quantitative electromyography (DQEMG) and near fibre (NF) motor unit potential (MUP) parameters. METHODS: The tibialis anterior (TA) muscle was tested in 12 patients with DPN (65 ± 15 years) and 12 controls (63 ± 15 years). DQEMG was used to analyze electromyographic (EMG) signals collected during voluntary contractions. MUP and NF MUP parameters were analyzed. NF MUPs were obtained by high-pass filtering MUP template waveforms, which isolates contributions of fibres that are close to the needle detection surface. NF MUP parameters provided assessment of motor unit size (NF area), fibre density (NF fibre count) and contribution dispersion (NF dispersion) and neuromuscular transmission instability (NF jiggle). RESULTS: DPN patients had larger (+45% NF area), more complex (+30% NF fibre count), and less stable (+30% NF jiggle) NF MUPs (p<0.05). No significant relationships were found between NF MUP stability and denervation, or strength; however NF MUP complexity was positively related to TA denervation in the DPN group (r=0.63; p<0.05). NF MUP complexity and instability were positively related in DPN patients (r=0.46; p<0.05). CONCLUSIONS: DPN is associated with neuromuscular transmission instability and MU remodelling that can be assessed using DQEMG. SIGNIFICANCE: DQEMG-derived NF MUP parameters may be useful in identifying patients in early stages of neuromuscular dysfunction related to DPN.
Authors: Nami Han; Mohammad A Yabroudi; Kristen Stearns-Reider; Wendy Helkowski; Brian M Sicari; J Peter Rubin; Stephen F Badylak; Michael L Boninger; Fabrisia Ambrosio Journal: Phys Ther Date: 2015-11-12
Authors: Geoffrey A Power; Matti D Allen; Kevin J Gilmore; Daniel W Stashuk; Timothy J Doherty; Russell T Hepple; Tanja Taivassalo; Charles L Rice Journal: J Appl Physiol (1985) Date: 2016-03-24
Authors: Érica Q Silva; Danilo P Santos; Raquel I Beteli; Renan L Monteiro; Jane S S P Ferreira; Ronaldo H Cruvinel-Junior; Asha Donini; Jady L Verissímo; Eneida Y Suda; Isabel C N Sacco Journal: Sci Rep Date: 2021-06-11 Impact factor: 4.379