Autonomic symptoms affect most patients with Parkinson's disease (PD) and often have a profound impact on their prognosis. Symptoms include orthostatic hypotension, gastroparesis, constipation, excessive sweating, and sexual dysfunction, however, these symptoms are frequently unrecognised by clinicians and remain untreated. The mechanism of autonomic dysfunction is attributed to the involvement of the central and peripheral postganglionic nervous system. It is now well established some autonomic symptoms have a diagnostic value because they appear early in the course of PD and may precede the onset of motor symptoms. Early recognition of autonomic symptoms is essential because it will help to expand our knowledge of the nature the neurodegenera- tive process. It is important that physicians both recognize and treat theses complications in an effort to improve quality of life.
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Arterial compliance (AC) is an important cardiovascular parameter characterizing mechanical properties of arteries. AC is significantly influenced by arterial wall structure and vasomotion, and it markedly influences cardiac load. A new method, based on a two-element Windkessel model, has been recently proposed for estimating AC as the ratio of the time constant T of the diastolic blood pressure decay and peripheral vascular resistance derived from clinically available stroke volume measurements and selected peripheral blood pressure parameters which are less prone to peripheral distortions.
View Article and Find Full Text PDFTurk J Pediatr
December 2024
Department of Pediatric Neurology, Faculty of Medicine, İnönü University, Malatya, Türkiye.
Background: This study aimed to investigate the risk factors associated with the severity of the disease, the need for mechanical ventilation (MV) and poor prognosis in the early stages of Guillain-Barré Syndrome (GBS).
Methods: Data of children who met GBS diagnostic criteria were evaluated retrospectively. The sample was divided into three binary subgroups according to severe GBS (Hughes Functional Grading Scale [HFGS] ≥ 4 at admission), mechanical ventilation (MV) requirement, and poor prognosis (inability to walk independently, HFGS ≥ 3 after six months).
BMJ Open
December 2024
Dr D Y Patil Vidyapeeth, Dr D Y Patil Medical College Hospital and Research Centre, Pune, Maharashtra, India.
Introduction: Parkinson's disease is a neurodegenerative disorder that presents with motor symptoms such as tremors, slowness and gait difficulties, in addition to various non-motor symptoms such as anxiety, depression and autonomic and sleep disturbances. Pranayama (yogic breathing practices) has been studied as a part of yoga interventions in Parkinson's disease. Previous systematic reviews and meta-analyses have not detailed the pranayama practices used in clinical studies, and there is no clarity on the pranayama practices that would be most beneficial for Parkinson's disease.
View Article and Find Full Text PDFNeurology
February 2025
From the Autonomic Medicine Section, Clinical Neurosciences Program, Division of Intramural Research, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD.
Background And Objectives: Lewy body diseases (LBDs) such as Parkinson disease (PD) feature increased deposition of α-synuclein (α-syn) in cutaneous sympathetic noradrenergic nerves. The pathophysiologic significance of sympathetic intraneuronal α-syn is unclear. We reviewed data about immunoreactive α-syn, tyrosine hydroxylase (TH, a marker of catecholaminergic fibers), and the sympathetic neurotransmitter norepinephrine (NE) in skin biopsies from control participants and patients with PD, the related LBD pure autonomic failure (PAF), the non-LBD synucleinopathy multiple system atrophy (MSA), or neurologic postacute sequelae of severe acute respiratory syndrome coronavirus 2 (neuro-PASC).
View Article and Find Full Text PDFKorean J Neurotrauma
December 2024
Department of Neurosurgery, Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Korea.
Spinal cord injury (SCI) frequently results in persistent motor, sensory, or autonomic dysfunction, and the outcomes are largely determined by the location and severity of the injury. Despite significant technological progress, the intricate nature of the spinal cord anatomy and the difficulties associated with neuroregeneration make full recovery from SCI uncommon. This review explores the potential of artificial intelligence (AI), with a particular focus on machine learning, to enhance patient outcomes in SCI management.
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