Literature DB >> 29102438

Prediction of Falls in Subjects Suffering From Parkinson Disease, Multiple Sclerosis, and Stroke.

Ettore Beghi1, Elisa Gervasoni2, Elisabetta Pupillo1, Elisa Bianchi1, Angelo Montesano2, Irene Aprile3, Michela Agostini4, Marco Rovaris2, Davide Cattaneo5.   

Abstract

OBJECTIVE: To compare the risk of falls and fall predictors in patients with Parkinson disease (PD), multiple sclerosis (MS), and stroke using the same study design.
DESIGN: Multicenter prospective cohort study.
SETTING: Institutions for physical therapy and rehabilitation. PARTICIPANTS: Patients (N=299) with PD (n=94), MS (n=111), and stroke (n=94) seen for rehabilitation.
INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Functional scales were applied to investigate balance, disability, daily performance, self-confidence with balance, and social integration. Patients were followed for 6 months. Telephone interviews were organized at 2, 4, and 6 months to record falls and fall-related injuries. Incidence ratios, Kaplan-Meier survival curves, and Cox proportional hazards models were used.
RESULTS: Of the 299 patients enrolled, 259 had complete follow-up. One hundred and twenty-two patients (47.1%) fell at least once; 82 (31.7%) were recurrent fallers and 44 (17.0%) suffered injuries; and 16%, 32%, and 40% fell at 2, 4, and 6 months. Risk of falls was associated with disease type (PD, MS, and stroke in decreasing order) and confidence with balance (Activities-specific Balance Confidence [ABC] scale). Recurrent fallers were 7%, 15%, and 24% at 2, 4, and 6 months. The risk of recurrent falls was associated with disease type, high educational level, and ABC score. Injured fallers were 3%, 8%, and 12% at 2, 4, and 6 months. The only predictor of falls with injuries was disease type (PD).
CONCLUSIONS: PD, MS, and stroke carry a high risk of falls. Other predictors include perceived balance confidence and high educational level.
Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Falls; Multiple sclerosis; Parkinson disease; Rehabilitation; Risk factors; Stroke

Mesh:

Year:  2018        PMID: 29102438     DOI: 10.1016/j.apmr.2017.10.009

Source DB:  PubMed          Journal:  Arch Phys Med Rehabil        ISSN: 0003-9993            Impact factor:   3.966


  9 in total

1.  Protocol for the development of a core outcome set for evaluating mixed-diagnosis falls prevention interventions for people with Multiple Sclerosis, Parkinson's Disease and stroke.

Authors:  Nicola O'Malley; Susan Coote; Amanda M Clifford
Journal:  HRB Open Res       Date:  2022-05-06

2.  Beam Walking to Assess Dynamic Balance in Health and Disease: A Protocol for the "BEAM" Multicenter Observational Study.

Authors:  Tibor Hortobágyi; Azusa Uematsu; Lianne Sanders; Reinhold Kliegl; József Tollár; Renato Moraes; Urs Granacher
Journal:  Gerontology       Date:  2018-10-18       Impact factor: 5.140

3.  Design and Evaluation of User-Centered Exergames for Patients With Multiple Sclerosis: Multilevel Usability and Feasibility Studies.

Authors:  Alexandra Schättin; Stephan Häfliger; Alain Meyer; Barbara Früh; Sonja Böckler; Yannic Hungerbühler; Eling D de Bruin; Sebastian Frese; Regula Steinlin Egli; Ulrich Götz; René Bauer; Anna Lisa Martin-Niedecken
Journal:  JMIR Serious Games       Date:  2021-05-07       Impact factor: 4.143

4.  Educational and Exercise Intervention to Prevent Falls and Improve Participation in Subjects With Neurological Conditions: The NEUROFALL Randomized Controlled Trial.

Authors:  Davide Cattaneo; Elisa Gervasoni; Elisabetta Pupillo; Elisa Bianchi; Irene Aprile; Isabella Imbimbo; Rita Russo; Arianna Cruciani; Andrea Turolla; Johanna Jonsdottir; Michela Agostini; Ettore Beghi
Journal:  Front Neurol       Date:  2019-09-13       Impact factor: 4.003

5.  Effectiveness of non-pharmacological falls prevention interventions for people with Multiple Sclerosis, Parkinson's Disease and stroke: protocol for an umbrella review.

Authors:  Nicola O'Malley; Amanda M Clifford; Laura Comber; Susan Coote
Journal:  HRB Open Res       Date:  2020-12-01

Review 6.  Effectiveness of interventions to prevent falls for people with multiple sclerosis, Parkinson's disease and stroke: an umbrella review.

Authors:  Nicola O'Malley; Amanda M Clifford; Mairéad Conneely; Bláthín Casey; Susan Coote
Journal:  BMC Neurol       Date:  2021-09-29       Impact factor: 2.474

7.  Efficacy of Robot-Assisted Gait Training Combined with Robotic Balance Training in Subacute Stroke Patients: A Randomized Clinical Trial.

Authors:  Irene Aprile; Carmela Conte; Arianna Cruciani; Cristiano Pecchioli; Letizia Castelli; Sabina Insalaco; Marco Germanotta; Chiara Iacovelli
Journal:  J Clin Med       Date:  2022-08-31       Impact factor: 4.964

8.  Efficacy of a multiple-component and multifactorial personalized fall prevention program in a mixed population of community-dwelling older adults with stroke, Parkinson's Disease, or frailty compared to usual care: The PRE.C.I.S.A. randomized controlled trial.

Authors:  Fabio La Porta; Giada Lullini; Serena Caselli; Franco Valzania; Chiara Mussi; Claudio Tedeschi; Giulio Pioli; Massimo Bondavalli; Marco Bertolotti; Federico Banchelli; Roberto D'Amico; Roberto Vicini; Silvia Puglisi; Pierina Viviana Clerici; Lorenzo Chiari
Journal:  Front Neurol       Date:  2022-09-01       Impact factor: 4.086

9.  Deep Neural Networks for Human's Fall-risk Prediction using Force-Plate Time Series Signal.

Authors:  M Savadkoohi; T Oladunni; L A Thompson
Journal:  Expert Syst Appl       Date:  2021-05-26       Impact factor: 8.665

  9 in total

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