Fall-related functional impairments in patients with neurological gait disorder
Falls are common in patients with neurological disorders and are a primary cause of injuries. Nonetheless, fall-associated gait characteristics are poorly understood in these patients. Objective, quantitative gait analysis is an important tool to identify the principal fall-related motor characteris...
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Published in | Scientific reports Vol. 10; no. 1; p. 21120 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
03.12.2020
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
ISSN | 2045-2322 2045-2322 |
DOI | 10.1038/s41598-020-77973-4 |
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Abstract | Falls are common in patients with neurological disorders and are a primary cause of injuries. Nonetheless, fall-associated gait characteristics are poorly understood in these patients. Objective, quantitative gait analysis is an important tool to identify the principal fall-related motor characteristics and to advance fall prevention in patients with neurological disorders. Fall incidence was assessed in 60 subjects with different neurological disorders. Patients underwent a comprehensive set of functional assessments including instrumented gait analysis, computerized postural assessments and clinical walking tests. Determinants of falls were assessed by binary logistic regression analysis and receiver operator characteristics (ROC). The best single determinant of fallers was a step length reduction at slow walking speed reaching an accuracy of 67.2% (ROC AUC: 0.669; p = 0.027). The combination of 4 spatio-temporal gait parameters including step length and parameters of variability and asymmetry were able to classify fallers and non-fallers with an accuracy of 81.0% (ROC AUC: 0.882; p < 0.001). These findings suggest significant differences in specific spatio-temporal gait parameters between fallers and non-fallers among neurological patients. Fall-related impairments were mainly identified for spatio-temporal gait characteristics, suggesting that instrumented, objective gait analysis is an important tool to estimate patients' fall risk. Our results highlight pivotal fall-related walking deficits that might be targeted by future rehabilitative interventions that aim at attenuating falls. |
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AbstractList | Falls are common in patients with neurological disorders and are a primary cause of injuries. Nonetheless, fall-associated gait characteristics are poorly understood in these patients. Objective, quantitative gait analysis is an important tool to identify the principal fall-related motor characteristics and to advance fall prevention in patients with neurological disorders. Fall incidence was assessed in 60 subjects with different neurological disorders. Patients underwent a comprehensive set of functional assessments including instrumented gait analysis, computerized postural assessments and clinical walking tests. Determinants of falls were assessed by binary logistic regression analysis and receiver operator characteristics (ROC). The best single determinant of fallers was a step length reduction at slow walking speed reaching an accuracy of 67.2% (ROC AUC: 0.669; p = 0.027). The combination of 4 spatio-temporal gait parameters including step length and parameters of variability and asymmetry were able to classify fallers and non-fallers with an accuracy of 81.0% (ROC AUC: 0.882; p < 0.001). These findings suggest significant differences in specific spatio-temporal gait parameters between fallers and non-fallers among neurological patients. Fall-related impairments were mainly identified for spatio-temporal gait characteristics, suggesting that instrumented, objective gait analysis is an important tool to estimate patients' fall risk. Our results highlight pivotal fall-related walking deficits that might be targeted by future rehabilitative interventions that aim at attenuating falls. Falls are common in patients with neurological disorders and are a primary cause of injuries. Nonetheless, fall-associated gait characteristics are poorly understood in these patients. Objective, quantitative gait analysis is an important tool to identify the principal fall-related motor characteristics and to advance fall prevention in patients with neurological disorders. Fall incidence was assessed in 60 subjects with different neurological disorders. Patients underwent a comprehensive set of functional assessments including instrumented gait analysis, computerized postural assessments and clinical walking tests. Determinants of falls were assessed by binary logistic regression analysis and receiver operator characteristics (ROC). The best single determinant of fallers was a step length reduction at slow walking speed reaching an accuracy of 67.2% (ROC AUC: 0.669; p = 0.027). The combination of 4 spatio-temporal gait parameters including step length and parameters of variability and asymmetry were able to classify fallers and non-fallers with an accuracy of 81.0% (ROC AUC: 0.882; p < 0.001). These findings suggest significant differences in specific spatio-temporal gait parameters between fallers and non-fallers among neurological patients. Fall-related impairments were mainly identified for spatio-temporal gait characteristics, suggesting that instrumented, objective gait analysis is an important tool to estimate patients' fall risk. Our results highlight pivotal fall-related walking deficits that might be targeted by future rehabilitative interventions that aim at attenuating falls.Falls are common in patients with neurological disorders and are a primary cause of injuries. Nonetheless, fall-associated gait characteristics are poorly understood in these patients. Objective, quantitative gait analysis is an important tool to identify the principal fall-related motor characteristics and to advance fall prevention in patients with neurological disorders. Fall incidence was assessed in 60 subjects with different neurological disorders. Patients underwent a comprehensive set of functional assessments including instrumented gait analysis, computerized postural assessments and clinical walking tests. Determinants of falls were assessed by binary logistic regression analysis and receiver operator characteristics (ROC). The best single determinant of fallers was a step length reduction at slow walking speed reaching an accuracy of 67.2% (ROC AUC: 0.669; p = 0.027). The combination of 4 spatio-temporal gait parameters including step length and parameters of variability and asymmetry were able to classify fallers and non-fallers with an accuracy of 81.0% (ROC AUC: 0.882; p < 0.001). These findings suggest significant differences in specific spatio-temporal gait parameters between fallers and non-fallers among neurological patients. Fall-related impairments were mainly identified for spatio-temporal gait characteristics, suggesting that instrumented, objective gait analysis is an important tool to estimate patients' fall risk. Our results highlight pivotal fall-related walking deficits that might be targeted by future rehabilitative interventions that aim at attenuating falls. |
ArticleNumber | 21120 |
Author | Filli, Linard Hostettler, Pascal Widmer, Lucas Petersen, Jens Alexander Ehrhardt, Angela Straumann, Dominik Reuter, Katja |
Author_xml | – sequence: 1 givenname: Angela surname: Ehrhardt fullname: Ehrhardt, Angela email: Angela.ehrhardt@usz.ch organization: Department of Neurology, University Hospital and University of Zurich – sequence: 2 givenname: Pascal surname: Hostettler fullname: Hostettler, Pascal organization: Department of Neurology, University Hospital and University of Zurich – sequence: 3 givenname: Lucas surname: Widmer fullname: Widmer, Lucas organization: Department of Neurology, University Hospital and University of Zurich – sequence: 4 givenname: Katja surname: Reuter fullname: Reuter, Katja organization: Department of Neurology, University Hospital and University of Zurich – sequence: 5 givenname: Jens Alexander surname: Petersen fullname: Petersen, Jens Alexander organization: Department of Neurology, University Hospital and University of Zurich – sequence: 6 givenname: Dominik surname: Straumann fullname: Straumann, Dominik organization: Department of Neurology, University Hospital and University of Zurich – sequence: 7 givenname: Linard surname: Filli fullname: Filli, Linard organization: Department of Neurology, University Hospital and University of Zurich, Spinal Cord Injury Center, Balgrist University Hospital, Swiss Center for Clinical Movement Analysis (SCMA) |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33273488$$D View this record in MEDLINE/PubMed |
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Snippet | Falls are common in patients with neurological disorders and are a primary cause of injuries. Nonetheless, fall-associated gait characteristics are poorly... |
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SubjectTerms | 631/378 631/378/2632 692/617/375 Accidental Falls Central Nervous System Diseases - pathology Central Nervous System Diseases - physiopathology Falls Female Gait Gait Disorders, Neurologic - physiopathology Humanities and Social Sciences Humans Inflammation - pathology Male Middle Aged Motor task performance multidisciplinary Neurological diseases Neurological disorders Postural Balance Regression analysis ROC Curve Science Science (multidisciplinary) |
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Title | Fall-related functional impairments in patients with neurological gait disorder |
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