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External validation of a 3-step falls prediction model in mild Parkinson’s disease

Lindholm, Beata LU ; Nilsson, Maria H. LU ; Hansson, Oskar LU and Hagell, Peter LU (2016) In Journal of Neurology 263(12). p.2462-2469
Abstract

The 3-step falls prediction model (3-step model) that include history of falls, history of freezing of gait and comfortable gait speed <1.1 m/s was suggested as a clinical fall prediction tool in Parkinson’s disease (PD). We aimed to externally validate this model as well as to explore the value of additional predictors in 138 individuals with relatively mild PD. We found the discriminative ability of the 3-step model in identifying fallers to be comparable to previously studies [area under curve (AUC), 0.74; 95 % CI 0.65–0.84] and to be better than that of single predictors (AUC, 0.61–0.69). Extended analyses generated a new model for prediction of falls and near falls (AUC, 0.82; 95 % CI 0.75–0.89) including history of near falls,... (More)

The 3-step falls prediction model (3-step model) that include history of falls, history of freezing of gait and comfortable gait speed <1.1 m/s was suggested as a clinical fall prediction tool in Parkinson’s disease (PD). We aimed to externally validate this model as well as to explore the value of additional predictors in 138 individuals with relatively mild PD. We found the discriminative ability of the 3-step model in identifying fallers to be comparable to previously studies [area under curve (AUC), 0.74; 95 % CI 0.65–0.84] and to be better than that of single predictors (AUC, 0.61–0.69). Extended analyses generated a new model for prediction of falls and near falls (AUC, 0.82; 95 % CI 0.75–0.89) including history of near falls, retropulsion according to the Nutt Retropulsion test (NRT) and tandem gait (TG). This study confirms the value of the 3-step model as a clinical falls prediction tool in relatively mild PD and illustrates that it outperforms the use of single predictors. However, to improve future outcomes, further studies are needed to firmly establish a scoring system and risk categories based on this model. The influence of methodological aspects of data collection also needs to be scrutinized. A new model for prediction of falls and near falls, including history of near falls, TG and retropulsion (NRT) may be considered as an alternative to the 3-step model, but needs to be tested in additional samples before being recommended. Taken together, our observations provide important additions to the evidence base for clinical fall prediction in PD.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Balance, Falls, Gait, Near falls, Parkinon disease, Prediction
in
Journal of Neurology
volume
263
issue
12
pages
2462 - 2469
publisher
Steinkopff
external identifiers
  • scopus:84988360811
  • wos:000388625500015
ISSN
0340-5354
DOI
10.1007/s00415-016-8287-9
language
English
LU publication?
yes
id
1fadab63-60f6-480d-9e73-3293032071c1
date added to LUP
2016-11-03 08:38:21
date last changed
2017-09-18 11:29:03
@article{1fadab63-60f6-480d-9e73-3293032071c1,
  abstract     = {<p>The 3-step falls prediction model (3-step model) that include history of falls, history of freezing of gait and comfortable gait speed &lt;1.1 m/s was suggested as a clinical fall prediction tool in Parkinson’s disease (PD). We aimed to externally validate this model as well as to explore the value of additional predictors in 138 individuals with relatively mild PD. We found the discriminative ability of the 3-step model in identifying fallers to be comparable to previously studies [area under curve (AUC), 0.74; 95 % CI 0.65–0.84] and to be better than that of single predictors (AUC, 0.61–0.69). Extended analyses generated a new model for prediction of falls and near falls (AUC, 0.82; 95 % CI 0.75–0.89) including history of near falls, retropulsion according to the Nutt Retropulsion test (NRT) and tandem gait (TG). This study confirms the value of the 3-step model as a clinical falls prediction tool in relatively mild PD and illustrates that it outperforms the use of single predictors. However, to improve future outcomes, further studies are needed to firmly establish a scoring system and risk categories based on this model. The influence of methodological aspects of data collection also needs to be scrutinized. A new model for prediction of falls and near falls, including history of near falls, TG and retropulsion (NRT) may be considered as an alternative to the 3-step model, but needs to be tested in additional samples before being recommended. Taken together, our observations provide important additions to the evidence base for clinical fall prediction in PD.</p>},
  author       = {Lindholm, Beata and Nilsson, Maria H. and Hansson, Oskar and Hagell, Peter},
  issn         = {0340-5354},
  keyword      = {Balance,Falls,Gait,Near falls,Parkinon disease,Prediction},
  language     = {eng},
  number       = {12},
  pages        = {2462--2469},
  publisher    = {Steinkopff},
  series       = {Journal of Neurology},
  title        = {External validation of a 3-step falls prediction model in mild Parkinson’s disease},
  url          = {http://dx.doi.org/10.1007/s00415-016-8287-9},
  volume       = {263},
  year         = {2016},
}