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A Self‐Reported Clinical Tool Predicts Falls in People with Parkinson's Disease
Author(s) -
Almeida Lorena Rosa S.,
Piemonte Maria Elisa Pimentel,
Cavalcanti Helen M.,
Canning Colleen G.,
Paul Serene S.
Publication year - 2021
Publication title -
movement disorders clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.754
H-Index - 18
ISSN - 2330-1619
DOI - 10.1002/mdc3.13170
Subject(s) - intraclass correlation , logistic regression , reliability (semiconductor) , gait , medicine , parkinson's disease , physical medicine and rehabilitation , physical therapy , disease , psychometrics , clinical psychology , power (physics) , physics , quantum mechanics
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 (ICC 2,1 ) 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 ICC 2,1 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.