Should we use both clinical and mobility measures to identify fallers in Parkinson's disease?

Although much is known about the multifactorial nature of falls in Parkinson's disease (PD), optimal classification of fallers remains unclear. To identify clinical (demographic, motor, cognitive and patient-reported) and objective mobility (balance and gait) measures that best discriminate fal...

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Vydané v:	Parkinsonism & related disorders Ročník 106; s. 105235
Hlavní autori:	Vitorio, Rodrigo, Mancini, Martina, Carlson-Kuhta, Patricia, Horak, Fay B., Shah, Vrutangkumar V.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Elsevier Ltd 01.01.2023
Predmet:	Balance Fall Gait Gait Disorders, Neurologic - diagnosis Gait Disorders, Neurologic - etiology Humans Parkinson Disease - complications Parkinson Disease - psychology Parkinson's disease Postural Balance Walking Fall Parkinson's disease Gait Balance
ISSN:	1353-8020, 1873-5126, 1873-5126
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Shrnutí:	Although much is known about the multifactorial nature of falls in Parkinson's disease (PD), optimal classification of fallers remains unclear. To identify clinical (demographic, motor, cognitive and patient-reported) and objective mobility (balance and gait) measures that best discriminate fallers from non-fallers in PD. People with mild-to-moderate idiopathic PD were classified as fallers (at least one fall; n = 54) or non-fallers (n = 90) based on previous six months falls. Clinical characteristics included demographic, motor and cognitive status and patient-reported outcomes. Mobility (balance and gait) characteristics were derived from body-worn, inertial sensors while performing walking and standing tasks. To investigate the combinations of (up to four) measures that best discriminate fallers from non-fallers in each scenario (i.e., clinical-only, mobility-only and combined clinical + mobility models), we applied logistic regression employing a ‘best subsets selection strategy’ with a 5-fold cross validation, and calculated the area under the curve (AUC). The highest AUCs for the clinical-only, mobility-only and clinical + mobility models were 0.89, 0.88, and 0.94, respectively. The most consistently selected measures in the top-10 ranked models were freezing of gait status (8x), the root mean square of anterior-posterior trunk acceleration while standing on a foam with eyes open (5x), gait double support duration (4x) and the postural instability and gait disorders score from the MDS UPDRS (4x). Findings highlight the importance of considering multiple aspects of clinical as well as objective balance and gait characteristics for the classification of fallers and non-fallers in PD. •Three models were explored to investigate which balance and gait measures that best discriminate PD fallers from non-fallers.•Logistic regression was used with a ‘best subsets selection strategy’ and 5-fold cross validation to test the model performance.•The highest AUCs for the clinical-only, mobility-only and clinical + mobility models were 0.89, 0.88, and 0.94, respectively.•Findings highlight the importance of considering both clinica and objective balance/gait measures for the classification of fallers in PD.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1353-8020 1873-5126 1873-5126
DOI:	10.1016/j.parkreldis.2022.105235