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Título:
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Predictive model for falling in Parkinson disease patients
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Autores:
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Custodio, Nilton ;
Lira, David ;
Herrera-Perez, Eder ;
Montesinos, Rosa ;
Castro-Suarez, Sheila ;
Cuenca-Alfaro, Jose ;
Cortijo, Patricia
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Tipo de documento:
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texto impreso
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Editorial:
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Elsevier, 2019-02-06T14:45:12Z
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Nota general:
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info:eu-repo/semantics/restrictedAccess
https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
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Idiomas:
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Inglés
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Palabras clave:
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Editados por otras instituciones
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Artículos
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Artículos en revistas indizadas
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Resumen:
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Background/aims: Falls are a common complication of advancing Parkinson's disease (PD). Although numerous risk factors are known, reliable predictors of future falls are still lacking. The aim of this study was to develop a multivariate model to predict falling in PD patients. Methods: Prospective cohort with forty-nine PD patients. The area under the receiver-operating characteristic curve (AUC) was calculated to evaluate predictive performance of the purposed multivariate model. Results: The median of PD duration and UPDRS-III score in the cohort was 6 years and 24 points, respectively. Falls occurred in 18 PD patients (30%). Predictive factors for falling identified by univariate analysis were age, PD duration, physical activity, and scores of UPDRS motor, FOG, ACE, IFS, PFAQ and GDS (p-value
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En línea:
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http://doi.org/10.1016/j.ensci.2016.11.003
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