Background And Purpose: Obstructive sleep apnea (OSA) frequently occurs in Parkinson Disease (PD), probably caused by upper airway dysfunctions or shared pathogenetic mechanisms. OSA may precede PD diagnosis or worsen throughout its course, but its relationship with clinical features and dopaminergic medication remains unclear. This meta-analysis aimed to provide a reliable estimate of OSA prevalence in the PD population (PD-OSA) and to clarify its clinical associated factors to help clinicians in understanding the underlying pathophysiological mechanisms.
Methods: A systematic literature search was performed up to April 2023 using the PubMed, Scopus, and PsycINFO databases. Articles were included if they provided data on PD patients with and without OSA. Pooled prevalence for PD-OSA was calculated using the proportions of PD participants diagnosed with OSA. Demographic and clinical features associated with PD-OSA were explored by comparing PD patients with and without OSA.
Results: Seventeen studies were included in the meta-analysis. Pooled OSA prevalence was 45% of a total sample of 1448 PD patients and was associated with older age, male sex, higher body mass index (BMI), more severe motor disturbances and periodic limb movements, reduced risk of rapid eye movement sleep behavior disorder, intake of dopamine agonists, and worse excessive daytime sleepiness. No relationship emerged with cognitive functioning and neuropsychiatric manifestations.
Conclusions: OSA affects nearly half of PD patients as a secondary outcome of predisposing factors such as older age and higher BMI in addition to PD-related motor impairment. Future studies should focus on determining the impact of both clinical features and dopaminergic medication on the development of PD-OSA.
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http://dx.doi.org/10.1111/ene.16109 | DOI Listing |
Medicine (Baltimore)
January 2025
Department of Otolaryngology, Hangzhou Red Cross Hospital (Zhejiang Hospital of Integrated Traditional Chinese and Western Medicine), Hangzhou, Zhejiang, China.
T-helper 17 (Th17) cells significantly influence the onset and advancement of malignancies. This study endeavor focused on delineating molecular classifications and developing a prognostic signature grounded in Th17 cell differentiation-related genes (TCDRGs) using machine learning algorithms in head and neck squamous cell carcinoma (HNSCC). A consensus clustering approach was applied to The Cancer Genome Atlas-HNSCC cohort based on TCDRGs, followed by an examination of differential gene expression using the limma package.
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January 2025
Departments of1Neurosurgery.
Objective: Craniopharyngiomas are rare, benign brain tumors that are primarily treated with surgery. Although the extended endoscopic endonasal approach (EEEA) has evolved as a more reliable surgical alternative and yields better visual outcomes than traditional craniotomy, postoperative visual deterioration remains one of the most common complications, and relevant risk factors are still poorly defined. Hence, identifying risk factors and developing a predictive model for postoperative visual deterioration is indeed necessary.
View Article and Find Full Text PDFBlood
January 2025
Division of Immunology and Allergy, Children's Hospital of Philadelphia; Department of Pediatrics, Perelman School of Medicine; Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States.
Leukopoiesis is lethally arrested in mice lacking the master transcriptional regulator PU.1. Depending on the animal model, subtotal PU.
View Article and Find Full Text PDFJCO Clin Cancer Inform
January 2025
Machine Learning Department, H. Lee Moffit Cancer Center and Research Institute, Tampa, FL.
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January 2025
INSERM, IMRBU955, Univ Paris Est Créteil, Créteil, France.
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