Background: Type 2 Diabetes Mellitus (T2DM) and diabetic symmetrical polyneuropathy (DSP) impact multiple modalities of sensation including light touch, temperature, position sense and vibration perception. No study to date has examined the mechanosensitivity of peripheral nerves during limb movement in this population. The objective was to determine the unique effects T2DM and DSP have on nerve mechanosensitivity in the lower extremity.
Methods: This cross-sectional study included 43 people with T2DM. Straight leg raise neurodynamic tests were performed with ankle plantar flexion (PF/SLR) and dorsiflexion (DF/SLR). Hip flexion range of motion (ROM), lower extremity muscle activity and symptom profile, intensity and location were measured at rest, first onset of symptoms (P1) and maximally tolerated symptoms (P2).
Results: The addition of ankle dorsiflexion during SLR testing reduced the hip flexion ROM by 4.3° ± 6.5° at P1 and by 5.4° ± 4.9° at P2. Individuals in the T2DM group with signs of severe DSP (n = 9) had no difference in hip flexion ROM between PF/SLR and DF/SLR at P1 (1.4° ± 4.2°; paired t-test p = 0.34) or P2 (0.9° ± 2.5°; paired t-test p = 0.31). Movement induced muscle activity was absent during SLR with the exception of the tibialis anterior during DF/SLR testing. Increases in symptom intensity during SLR testing were similar for both PF/SLR and DF/SLR. The addition of ankle dorsiflexion induced more frequent posterior leg symptoms when taken to P2.
Conclusions: Consistent with previous recommendations in the literature, P1 is an appropriate test end point for SLR neurodynamic testing in people with T2DM. However, our findings suggest that people with T2DM and severe DSP have limited responses to SLR neurodynamic testing, and thus may be at risk for harm from nerve overstretch and the information gathered will be of limited clinical value.
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http://dx.doi.org/10.1186/1471-2377-10-75 | DOI Listing |
JAMA Netw Open
December 2024
Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis.
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Diagnostics (Basel)
December 2024
PhysiUZerapy: Health Sciences Research Group, University of Zaragoza, Calle Domingo Miral S/N, 50009 Zaragoza, Spain.
Background: When performing the Upper Limb Neurodynamic Test 1 (ULNT1), the order of joint movement can be varied to place more stress onto certain nerve segments. However, the mechanisms underlying this phenomenon are still unclear. This study aimed to analyze the differences in the stiffness of the median nerve (MN) and the brachial plexus (BP) using ultrasound shear wave elastography during three sequences of the ULNT1: standard (ULNT1-STD), distal-to-proximal (ULNT1-DIST), and proximal-to-distal (ULNT1-PROX).
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December 2024
S.I. Spasokukotsky Moscow Centre for Research and Practice in Medical Rehabilitation, Restorative and Sports Medicine, Moscow, Russia.
Unlabelled: Post-stroke cognitive impairments are widespread and significantly reduce the quality of life and rehabilitation prognosis of patients. Clinical observations show a serious variability of cognitive impairments in patients after acute cerebrovascular accident. Thus, the classification of above mentioned disorders, based on which it would be possible to determine the order of individualization of a cognitive rehabilitation program, is currently not available in literature.
View Article and Find Full Text PDFCase Rep Med
December 2024
Department of Biochemistry, JSS Medical College, JSS Academy of Higher Education and Research, Mysuru, India.
Sensors (Basel)
December 2024
School of Mathematics and Physics, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China.
Evaluating students' learning effectiveness is of great importance for gaining a deeper understanding of the learning process, accurately diagnosing learning barriers, and developing effective teaching strategies. Emotion, as a key factor influencing learning outcomes, provides a novel perspective for identifying cognitive states and emotional experiences. However, traditional evaluation methods suffer from one sidedness in feature extraction and high complexity in model construction, often making it difficult to fully explore the deep value of emotional data.
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