Objective: Due to the aging population, the incidence of stroke is steadily increasing. In patients with stroke outcomes, sensory, motor and cognitive problems limit the performance of activities of daily living. The development of new technologies in rehabilitation is improving the quality and efficiency of functional recovery. Hunova robotic platform (Movendo Technology, srl, Genoa, Italy) is a robotic device for functional assessment and rehabilitation of balance. The purpose of this study is to evaluate the effects of rehabilitation with Hunova on cognitive function and balance in older adults with stroke.
Patients And Methods: This is a randomized, controlled, single-blind study. Twenty-four older adults with stroke outcomes were randomized into the Hunova group (HuG), which performed a specific rehabilitation program for balance using Hunova for 12 sessions in addition to conventional rehabilitation, and the control group (CoG), which performed only conventional rehabilitation. All patients underwent a clinical cognitive, balance, quality of life and fatigue assessment, and an instrumental balance assessment with Hunova at the beginning and end of treatment.
Results: Statistical analysis showed significant improvements in most clinical scales in both groups. Comparing the groups, HuG showed greater improvements in executive functions, speed of information processing, attention and discrimination of multiple stimuli, static and dynamic balance and autonomy in daily activities, standing postural sway, and trunk control in static and dynamic conditions.
Conclusions: Data analysis showed that elderly with stroke who underwent balance technology treatment with Hunova in combination with conventional treatment had a greater improvement in cognitive functions, balance and reduced risk of falling.
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http://dx.doi.org/10.26355/eurrev_202309_33580 | DOI Listing |
Background: The authors aimed to explore the association of fatty acids with periodontitis and its severity and to assess causality using Mendelian randomization (MR) analyses.
Methods: Data for participants with complete data were extracted from the 2009-2014 National Health and Nutrition Examination Survey. Weighted logistic regression was used to explore the relationship between dietary fatty acids and periodontitis and its severity.
Dis Esophagus
January 2025
Department of Digestive and Oncological Surgery, Claude Huriez Hospital, Chu Lille, Lille, France.
Background: Malnutrition is common with esophagogastric cancers and is associated with negative outcomes. We aimed to evaluate if immunonutrition during neoadjuvant treatment improves patient's health-related quality of life (HRQOL) and reduces postoperative morbidity and toxicities during neoadjuvant treatment.
Methods: A multicenter double-blind randomized controlled trial (RCT) was undertaken.
BMC Public Health
January 2025
Amsterdam UMC location Vrije Universiteit Amsterdam, Public and Occupational Health, De Boelelaan 1117, Amsterdam, the Netherlands.
Background: Developing interventions along with the population of interest using systems thinking is a promising method to address the underlying system dynamics of overweight. The purpose of this study is twofold: to gain insight into the perspectives of adolescents regarding: (1) the system dynamics of energy balance-related behaviours (EBRBs) (physical activity, screen use, sleep behaviour and dietary behaviour); and (2) underlying mechanisms and overarching drivers of unhealthy EBRBs.
Methods: We conducted Participatory Action Research (PAR) to map the system dynamics of EBRBs together with adolescents aged 10-14 years old living in a lower socioeconomic, ethnically diverse neighbourhood in Amsterdam East, the Netherlands.
Sci Rep
January 2025
Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monitor real-time changes in cerebral hemodynamics. In this study, thirty-six healthy adults were measured by single channel fNIRS to explore differences between two age groups using machine learning (ML). The subjects, measured during functional magnetic resonance imaging (fMRI) at Oulu University Hospital, were divided into young (age ≤ 32) and elderly (age ≥ 57) groups.
View Article and Find Full Text PDFProstate Cancer Prostatic Dis
January 2025
Department of Urology, Chang Gung Memorial Hospital at Linkou, Taoyuan, 333, Taiwan.
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