Ontology highlight
ABSTRACT: Background
A 3-step clinical prediction tool including falling in the previous year, freezing of gait in the past month and self-selected gait speed <1.1 m/s has shown high accuracy in predicting falls in people with Parkinson's disease (PD). The accuracy of this tool when including only self-report measures is yet to be determined.Objectives
To validate the 3-step prediction tool using only self-report measures (3-step self-reported prediction tool), and to externally validate the 3-step clinical prediction tool.Methods
The clinical tool was used with 137 individuals with PD. Participants also answered a question about self-reported gait speed, enabling scoring of the self-reported tool, and were followed-up for 6 months. An intraclass correlation coefficient (ICC2,1) was calculated to evaluate test-retest reliability of the 3-step self-reported prediction tool. Multivariate logistic regression models were used to evaluate the performance of both tools and their discriminative ability was determined using the area under the curve (AUC).Results
Forty-two participants (31%) reported ≥1 fall during follow-up. The 3-step self-reported tool had an ICC2,1 of 0.991 (95% CI 0.971-0.997; P < 0.001) and AUC = 0.68; 95% CI 0.59-0.77, while the 3-step clinical tool had an AUC = 0.69; 95% CI 0.60-0.78.Conclusions
The 3-step self-reported prediction tool showed excellent test-retest reliability and was validated with acceptable accuracy in predicting falls in the next 6 months. The 3-step clinical prediction tool was externally validated with similar accuracy. The 3-step self-reported prediction tool may be useful to identify people with PD at risk of falls in e/tele-health settings.
SUBMITTER: Almeida LRS
PROVIDER: S-EPMC8015904 | biostudies-literature | 2021 Apr
REPOSITORIES: biostudies-literature
Almeida Lorena Rosa S LRS Piemonte Maria Elisa Pimentel MEP Cavalcanti Helen M HM Canning Colleen G CG Paul Serene S SS
Movement disorders clinical practice 20210311 3
<h4>Background</h4>A 3-step clinical prediction tool including falling in the previous year, freezing of gait in the past month and self-selected gait speed <1.1 m/s has shown high accuracy in predicting falls in people with Parkinson's disease (PD). The accuracy of this tool when including only self-report measures is yet to be determined.<h4>Objectives</h4>To validate the 3-step prediction tool using only self-report measures (3-step self-reported prediction tool), and to externally validate t ...[more]