SAFETYLIT WEEKLY UPDATE

We compile citations and summaries of about 400 new articles every week.
RSS Feed

HELP: Tutorials | FAQ
CONTACT US: Contact info

Search Results

Journal Article

Citation

Almeida LRS, Heller G, Allen NE, Canning CG, Sherrington C, Valença GT, Oliveira-Filho J, Paul SS. Aging Clin. Exp. Res. 2019; ePub(ePub): ePub.

Affiliation

Discipline of Physiotherapy, Faculty of Health Sciences, The University of Sydney, Sydney, NSW, Australia.

Copyright

(Copyright © 2019, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s40520-019-01281-9

PMID

31347101

Abstract

BACKGROUND: Previous investigations of falls predictors in people with Parkinson's disease (PD) have used various statistical methods and categorization of falls outcomes. The impact of methodological differences on falls predictors has not been investigated.

OBJECTIVES: To describe similarities and differences in predictors modelled for fall rates [negative binomial (NB), Poisson Inverse Gaussian (PIG) and quantile regression] and previously-reported predictors of time to second fall (Cox regression), i.e. past falls, motor fluctuations, disability, levodopa dose and balance impairment. To investigate whether predictors from quantile regression vary across subsets of fallers based on fall frequency.

METHODS: Participants with PD (n = 229) were followed-up for 12 months. NB and PIG regression were used to determine predictors of fall rates, with the best fitting model reported. Quantile regression was used to determine predictors at higher (62nd, 70th, 80th) percentiles of the falls distribution. Univariate and multivariate analyses were performed.

RESULTS: Predictors of fall rates were the same in NB and PIG multivariate models, with the PIG model fitting our data better. Past falls, disability and levodopa dose were associated with fall rates from PIG and quantile regression. Freezing of gait was associated with fall rates from PIG regression. Disease severity predicted less (70th percentile, approximately 2-4) and more (80th percentile, approximately ≥ 5) frequent falls, and anteroposterior stability also predicted less frequent falls (p < 0.05), from quantile regression.

CONCLUSIONS: Not all predictors of time to second fall were predictors of fall rates. Quantile regression revealed some divergent predictors depending on the percentile of fall frequency examined.


Language: en

Keywords

Falls; Parkinson’s disease; Prediction; Risk factors; Statistical models

NEW SEARCH


All SafetyLit records are available for automatic download to Zotero & Mendeley
Print