Behavioral biomarkers of fall risks in older people with Parkinson's disease: a multicenter study

• Grant number: 23/14143-0
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Effective date (Start): August 01, 2024
• Effective date (End): July 31, 2026
• Field of knowledge: Health Sciences - Physical Education
• Principal Investigator: José Angelo Barela
• Grantee: Diego Orcioli da Silva
• Host Institution: Instituto de Biociências (IB). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil

Abstract

Determining the factors that can predict falls is one of the greatest scientific challenges. Although previous studies have made efforts to identify tools to predict falls in older people with Parkinson's disease (PD), these studies have focused only on the final outcome (e.g., gait and balance performance), without understanding the factors involved in the execution of the task, such as sensory deficits, that could lead to falls. This study advances knowledge towards understanding declines in sensory information in older people with PD and how this information can be used as biomarkers of falls risk. Therefore, the aims of the present study are: (i) to analyze and compare sensory information between fallers and non-fallers with PD and (ii) to identify sensory variables that can predict falls in this population. This research project will be multicentric, being carried out predominantly at the Institute of Biosciences, at the São Paulo State University (UNESP) Campus Rio Claro, but also involving the School of Sciences, at UNESP Campus Bauru, and the Institute of Physical Activity and Sport Sciences, at the Cruzeiro do Sul University, and with this, it is expected to recruit 100 older people with PD. Participants will perform a battery of sensory (primary outcome) and motor (secondary outcome) assessments. After the assessments, participants will be prospectively monitored every month during 12 months, to record falls. They will be classified as fallers and non-fallers. The results of this study will make it possible to identify predictors of falls and, consequently, develop more specific intervention strategies for the problems caused by PD, minimizing the occurrence of falls.