Fall prediction in people with Parkinson's Disease: a multifactorial approach

• Grant number: 16/23695-2
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: August 01, 2017
• End date: July 31, 2018
• Field of knowledge: Health Sciences - Physical Education
• Principal Investigator: Rodrigo Vitório
• Grantee: Willian Serati Luizon
• Host Institution: Instituto de Biociências (IB). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil

Abstract

The major consequence of impairments caused by Parkinson's disease (PD) is the increased occurrence of falls. The appropriate management of this problem requires the development of clinical tools able to identify individuals with increased risk of falling. However, the existing studies on prediction of falls in PD are limited by focusing on the performance of single variables. As multiple factors are associated with fall occurrence in PD, a multifactorial approach is needed. This kind of research has potential to improve quality of life in people with PD and decrease public and private costs on health services. In this context, the aim of the current research project will be to test the effectiveness of single and combined classifiers (clinical and cognitive symptoms, functional capacity and kinematic/Kinect parameters of gait and postural control) to predict falls based on a 4-month prospective fall report in patients with PD. This project will consist in a prospective study and will use data collected between 2010 and 2015 from the database of the Posture and Gait Studies Laboratory (LEPLO, Instituto de Biociência de Rio Claro). The experimental design will include baseline assessments and a 4-month prospective follow up period for fall occurrence. The effectiveness of single and combined outcome measures to predict falls during four months will be assessed using ROC curve analyses (sensitivity, specificity and area under the curve). (AU)