Introduction And Aim: Multifocal motor neuropathy (MMN) is a rare, chronic disorder with potentially severe and progressive disability, which may affect patients' quality of life (QoL). Since there is still small number of studies that predominantly investigated QoL in patients with MMN, we sought to analyze QoL in these patients.
Materials And Methods: Our study comprised 17 patients diagnosed with MMN at the same clinic. Following scales were used: SF-36 questionnaire, INCAT disability scale, Krupp's Fatigue Severity scale, and Beck Depression Inventory.
Results: Physical domains of QoL were slightly more affected than mental ones, but with no statistical significance (64.8 ± 22.3 vs. 70.0 ± 19.5, p > 0.05). Total SF-36 score was 69.2 ± 19.9. INCAT arm disability score at testing was found to correlate with the total SF-36 score (rho = -0.603, p < 0.05). INCAT arm disability score at diagnosis (rho = -0.57, p < 0.05) and at testing (rho = -0.48, p = 0.05) correlated with physical composite score (PCS). Disease duration (rho = -0.51, p < 0.05) and INCAT arm disability score at testing (rho = -0.60, p = 0.01) were associated with mental composite score (MCS).
Conclusion: QoL in patients with MMN was reduced, especially in physical domains. Although arm disability was the most significant parameter which affected QoL of MMN patients in both physical and mental aspects, longer disease duration should not be underestimated as a psychological burden for these patients.
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http://dx.doi.org/10.1016/j.jns.2019.02.029 | DOI Listing |
Glob Health Res Policy
January 2025
Center for Public Health and Epidemic Preparedness and Response, Peking University, Haidian District, 38Th Xueyuan Road, Beijing, 100191, China.
Background: As population aging intensifies, it becomes increasingly important to elucidate the casual relationship between aging and changes in population health. Therefore, our study proposed to develop a systematic attribution framework to comprehensively evaluate the health impacts of population aging.
Methods: We used health-adjusted life expectancy (HALE) to measure quality of life and disability-adjusted life years (DALY) to quantify the burden of disease for the population of Guangzhou.
Pilot Feasibility Stud
January 2025
Department of Internal Medicine - Cardiology, Virginia Commonwealth University, West Hospital 8th Floor, North Wing, Richmond, VA, 23298, USA.
Background: To determine the feasibility, acceptability, and preliminary efficacy of a 6-month tailored non-linear progressive physical activity intervention (PAI) for lymphoma patients undergoing chemotherapy.
Methods: Patients newly diagnosed with lymphoma (non-Hodgkin (NHL) or Hodgkin (HL)) were randomized into the PAI or healthy living intervention (HLI) control (2:1). Feasibility was assessed by examining accrual, adherence, and retention rates.
Inj Epidemiol
January 2025
Injury Prevention Research Center, University of Iowa, 145 N Riverside Dr., Iowa City, IA, 52242, USA.
Background: Motor vehicle crashes are the second leading cause of injury death among adults aged 65 and older in the U.S., second only to falls.
View Article and Find Full Text PDFBMC Med Genomics
January 2025
Department of Otolaryngology, First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, WuHua District, Kunming City, Yunnan Province, China.
Hearing loss is a prevalent condition with a significant impact on individuals' quality of life. However, comprehensive studies investigating the differential gene expression and regulatory mechanisms associated with hearing loss are lacking, particularly in the context of diverse patient samples. In this study, we integrated data from 10 patients across different regions, age groups, and genders, with their data retrieved from a public transcriptome database, to explore the molecular basis of hearing loss.
View Article and Find Full Text PDFJ Transl Med
January 2025
School of Information and Communication Engineering, Dalian University of Technology, No. 2 Linggong Road, 116024, Dalian, China.
Background: Parkinson's Disease (PD) is a neurodegenerative disorder, and eye movement abnormalities are a significant symptom of its diagnosis. In this paper, we developed a multi-task driven by eye movement in a virtual reality (VR) environment to elicit PD-specific eye movement abnormalities. The abnormal features were subsequently modeled by using the proposed deep learning algorithm to achieve an auxiliary diagnosis of PD.
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