Daphne J Geerse1, Melvyn Roerdink2, Johan Marinus3, Jacobus J van Hilten3. 1. Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands; Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, the Netherlands. Electronic address: D.Geerse@lumc.nl. 2. Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, the Netherlands. 3. Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands.
Abstract
BACKGROUND: Most falls occur during walking and are due to trips, slips or misplaced steps, which suggests a reduced walking adaptability. The objective of this study was to evaluate the potential merit of a walking-adaptability assessment for identifying prospective fallers and risk factors for future falls in a cohort of stroke patients, Parkinson's disease patients, and controls (n = 30 for each group). RESEARCH QUESTION: Does an assessment of walking-adaptability improve the identification of fallers compared to generic fall-risk factors alone? METHODS: This study comprised an evaluation of subject characteristics, clinical gait and balance tests, a quantitative gait assessment and a walking-adaptability assessment with the Interactive Walkway. Subjects' falls were registered prospectively with falls calendars during a 6-month follow-up period. Generic and walking-related fall-risk factors were compared between prospective fallers and non-fallers. Binary logistic regression and Chi-square Automatic Interaction Detector analyses were performed to identify fallers and predictor variables for future falls. RESULTS: In addition to fall history, obstacle-avoidance success rate and normalized walking speed during goal-directed stepping correctly classified prospective fallers and were predictors of future falls. Compared to the use of generic fall-risk factors only, the inclusion of walking-related fall-risk factors improved the identification of prospective fallers. SIGNIFICANCE: If cross-validated in future studies with larger samples, these fall-risk factors may serve as quick entry tests for falls prevention programs. In addition, the identification of these walking-related fall-risk factors may help in developing falls prevention strategies.
BACKGROUND: Most falls occur during walking and are due to trips, slips or misplaced steps, which suggests a reduced walking adaptability. The objective of this study was to evaluate the potential merit of a walking-adaptability assessment for identifying prospective fallers and risk factors for future falls in a cohort of strokepatients, Parkinson's diseasepatients, and controls (n = 30 for each group). RESEARCH QUESTION: Does an assessment of walking-adaptability improve the identification of fallers compared to generic fall-risk factors alone? METHODS: This study comprised an evaluation of subject characteristics, clinical gait and balance tests, a quantitative gait assessment and a walking-adaptability assessment with the Interactive Walkway. Subjects' falls were registered prospectively with falls calendars during a 6-month follow-up period. Generic and walking-related fall-risk factors were compared between prospective fallers and non-fallers. Binary logistic regression and Chi-square Automatic Interaction Detector analyses were performed to identify fallers and predictor variables for future falls. RESULTS: In addition to fall history, obstacle-avoidance success rate and normalized walking speed during goal-directed stepping correctly classified prospective fallers and were predictors of future falls. Compared to the use of generic fall-risk factors only, the inclusion of walking-related fall-risk factors improved the identification of prospective fallers. SIGNIFICANCE: If cross-validated in future studies with larger samples, these fall-risk factors may serve as quick entry tests for falls prevention programs. In addition, the identification of these walking-related fall-risk factors may help in developing falls prevention strategies.
Authors: Jacek Wilczyński; Magdalena Ścipniak; Kacper Ścipniak; Kamil Margiel; Igor Wilczyński; Rafał Zieliński; Piotr Sobolewski Journal: Biomed Res Int Date: 2021-09-28 Impact factor: 3.411
Authors: Marissa H G Gerards; Kenneth Meijer; Kiros Karamanidis; Lotte Grevendonk; Joris Hoeks; Antoine F Lenssen; Christopher McCrum Journal: Front Sports Act Living Date: 2021-05-19