Clinical Scenario: Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy of the upper-extremity. Due to the involvement of the median nerve, long-term compression of this nerve can lead to hand dysfunction and disability that can impact work and daily life. As such, early treatment is warranted to prevent any long-term damage to the median nerve. Conservative management is utilized in those with mild to moderate CTS. Neural mobilizations can aid in the reduction of neural edema, neural mobility, and neural adhesion while improving nerve conduction. Clinical Question: Is neurodynamics effective in reducing pain and reported symptoms in those with CTS? Summary of Key Findings: Four studies were included, with 2 studies utilizing passive neural mobilizations, one study using active techniques, and one study using active neural mobilizations with splinting. All studies showed large effect size for pain, symptom severity, and physical function. Clinical Bottom Line: Neurodynamics is an effective treatment for CTS. Splinting is only effective when combined with neurodynamics. Strength of Recommendation: Level B evidence to support the use of neurodynamics for the treatment of CTS.
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http://dx.doi.org/10.1123/jsr.2021-0155 | DOI Listing |
J Clin Med
January 2025
Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum, University of Bologna, 40136 Bologna, Italy.
Low back pain (LBP) is a leading cause of disability worldwide, often driven by distinct pain mechanisms: nociceptive, neuropathic, and central sensitization. Accurate classification of these mechanisms is critical for guiding effective, targeted treatments. A scoping review was conducted following the Joanna Briggs Institute methodology and reported according to PRISMA-ScR guidelines.
View Article and Find Full Text PDFBr J Hosp Med (Lond)
December 2024
Department of Neurology, Wuhan Brain Hospital, General Hospital of Yangtze River Shipping, Wuhan, Hubei, China.
Arterial spin labelling (ASL) is a non-invasive magnetic resonance imaging (MRI) method. ASL techniques can quantitatively measure cerebral perfusion by fitting a kinetic model to the difference between labelled images (tag images) and ones which are acquired without labelling (control images). ASL functional MRI (fMRI) provides quantitative perfusion maps by using arterial water as an endogenous tracer instead of depending on vascular blood oxygenation level.
View Article and Find Full Text PDFClin EEG Neurosci
January 2025
Division of Physiology and Neuroscience, Department of Functional Sciences, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania.
Complex childhood trauma (CCT) involves prolonged exposure to severe interpersonal stressors, leading to deficits in executive functioning and self-regulation during adolescence, a critical period for neurodevelopment. While qEEG parameters, particularly alpha oscillations, have been proposed as potential biomarkers for trauma, empirical documentation in developmental samples is limited. .
View Article and Find Full Text PDFCogn Neurodyn
December 2025
Department of Electronics and Communication Engineering, R.M.K. College of Engineering and Technology, Chennai, India.
In recent years, Wireless Sensor Networks (WSN) have become vital because of their versatility in numerous applications. Nevertheless, the attain problems like inherent noise, and limited node computation capabilities, result in reduced sensor node lifespan as well as enhanced power consumption. To tackle such problems, this study develops a Modified-Distributed Arithmetic-Offset Binary Coding-based Adaptive Finite Impulse Response (MDA-OBC based AFIR) framework.
View Article and Find Full Text PDFCogn Neurodyn
December 2025
Shanghai University, Shanghai, China.
Neurodynamic observations indicate that the cerebral cortex evolved by self-organizing into functional networks, These networks, or distributed clusters of regions, display various degrees of attention maps based on input. Traditionally, the study of network self-organization relies predominantly on static data, overlooking temporal information in dynamic neuromorphic data. This paper proposes Temporal Self-Organizing (TSO) method for neuromorphic data processing using a spiking neural network.
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