Roman Schniepp1,2, Anna Huppert3, Julian Decker3,4, Fabian Schenkel3, Cornelia Schlick3, Atal Rasoul3, Marianne Dieterich5,3, Thomas Brandt3, Klaus Jahn3,4, Max Wuehr3. 1. Department of Neurology, Ludwig-Maximilians University of Munich, Marchioninistrasse 15, 81377, Munich, Germany. roman.schniepp@med.uni-muenchen.de. 2. German Center for Vertigo and Balance Disorders, Ludwig-Maximilians University of Munich, Munich, Germany. roman.schniepp@med.uni-muenchen.de. 3. German Center for Vertigo and Balance Disorders, Ludwig-Maximilians University of Munich, Munich, Germany. 4. Schön Klinik, Bad Aibling, Germany. 5. Department of Neurology, Ludwig-Maximilians University of Munich, Marchioninistrasse 15, 81377, Munich, Germany.
Abstract
OBJECTIVE: To evaluate the predictive validity of multimodal clinical assessment outcomes and quantitative measures of in- and off-laboratory mobility for fall-risk estimation in patients with different forms of neurological gait disorders. METHODS: The occurrence, severity, and consequences of falls were prospectively assessed for 6 months in 333 patients with early stage gait disorders due to vestibular, cerebellar, hypokinetic, vascular, functional, or other neurological diseases and 63 healthy controls. At inclusion, participants completed a comprehensive multimodal clinical and functional fall-risk assessment, an in-laboratory gait examination, and an inertial-sensor-based daily mobility monitoring for 14 days. Multivariate logistic regression analyses were performed to identify explanatory characteristics for predicting the (1) the fall status (non-faller vs. faller), (2) the fall frequency (occasional vs. frequent falls), and (3) the fall severity (benign vs. injurious fall) of patients. RESULTS: 40% of patients experienced one or frequent falls and 21% severe fall-related injuries during prospective fall assessment. Fall status and frequency could be reliably predicted (accuracy of 78 and 91%, respectively) primarily based on patients' retrospective fall status. Instrumented-based gait and mobility measures further improved prediction and provided independent, unique information for predicting the severity of fall-related consequences. INTERPRETATION: Falls- and fall-related injuries are a relevant health problem already in early stage neurological gait disorders. Multivariate regression analysis encourages a stepwise approach for fall assessment in these patients: fall history taking readily informs the clinician about patients' general fall risk. In patients at risk of falling, instrument-based measures of gait and mobility provide critical information on the likelihood of severe fall-related injuries.
OBJECTIVE: To evaluate the predictive validity of multimodal clinical assessment outcomes and quantitative measures of in- and off-laboratory mobility for fall-risk estimation in patients with different forms of neurological gait disorders. METHODS: The occurrence, severity, and consequences of falls were prospectively assessed for 6 months in 333 patients with early stage gait disorders due to vestibular, cerebellar, hypokinetic, vascular, functional, or other neurological diseases and 63 healthy controls. At inclusion, participants completed a comprehensive multimodal clinical and functional fall-risk assessment, an in-laboratory gait examination, and an inertial-sensor-based daily mobility monitoring for 14 days. Multivariate logistic regression analyses were performed to identify explanatory characteristics for predicting the (1) the fall status (non-faller vs. faller), (2) the fall frequency (occasional vs. frequent falls), and (3) the fall severity (benign vs. injurious fall) of patients. RESULTS: 40% of patients experienced one or frequent falls and 21% severe fall-related injuries during prospective fall assessment. Fall status and frequency could be reliably predicted (accuracy of 78 and 91%, respectively) primarily based on patients' retrospective fall status. Instrumented-based gait and mobility measures further improved prediction and provided independent, unique information for predicting the severity of fall-related consequences. INTERPRETATION: Falls- and fall-related injuries are a relevant health problem already in early stage neurological gait disorders. Multivariate regression analysis encourages a stepwise approach for fall assessment in these patients: fall history taking readily informs the clinician about patients' general fall risk. In patients at risk of falling, instrument-based measures of gait and mobility provide critical information on the likelihood of severe fall-related injuries.
Entities:
Keywords:
Fall prediction; Fall risk; Gait analysis; Mobility assessment; Neurological gait disorder
Authors: E M R Fonteyn; T Schmitz-Hübsch; C C P Verstappen; L Baliko; B R Bloem; S Boesch; L Bunn; P Giunti; C Globas; T Klockgether; B Melegh; M Pandolfo; L Schöls; D Timmann; B P C van de Warrenburg Journal: Eur Neurol Date: 2012-11-07 Impact factor: 1.710
Authors: T S Voss; J J Elm; C L Wielinski; M J Aminoff; D Bandyopadhyay; K L Chou; L R Sudarsky; B C Tilley Journal: Parkinsonism Relat Disord Date: 2012-04-26 Impact factor: 4.891