Objective: To externally validate two predictive tools to identify people with Parkinson’s disease (PD) at risk of recurrent falls.
Background: Two fall prediction tools were developed with moderate-to-high accuracy to identify people with PD at low, moderate or high risk of recurrent falls in the next 12 months.1 The 3-predictor tool includes history of ≥ 2 falls in the past year, motor fluctuations and UPDRS activities of daily living (ADL) >12 points (AUC = 0.84; 95% CI 0.78–0.90), and the 5-predictor tool includes these three predictors plus levodopa equivalent dose (LED) >700 mg/day and Berg balance scale ≤ 49 points (AUC = 0.86; 95% CI 0.81–0.92). However, both tools need to be externally validated.
Method: Participants with PD (n=156) were enrolled in this study and followed-up for 12 months. Demographic and clinical data including history of ≥ 2 falls in the past year, PD symptoms and medications taken, including LED, were recorded. Participants were assessed by the UPDRS ADL and Berg balance scale (BBS). Multivariate logistic regression analyses were performed and the accuracy of both the 3-predictor tool and the 5-predictor tool was determined based on the area under the receiver-operating characteristic curve (AUC).
Results: 46 (29.5%) participants reported ≥ 2 falls during the 12-month follow up. Multivariate models showed that only a history of ≥ 2 falls in the past year and motor fluctuations were independent predictors of recurrent falls in both tools. The 3-predictor tool had an AUC=0.71; 95% CI 0.63-0.79 (≥ 2 falls in the past year: OR=5.23, 95% CI 2.33-11.73; motor fluctuations: OR=2.88, 95% CI 1.29-6.46 and UPDRS ADL >12 points: OR=0.98, 95% CI 0.44-2.18). The 5-predictor tool had an AUC=0.69; 95% CI 0.60-0.77 (≥ 2 falls in the past year: OR=5.68, 95% CI 2.48-12.98; motor fluctuations: OR=2.38, 95% CI 1.02-5.55; UPDRS ADL >12points: OR=0.88, 95% CI 0.36-2.16; LED >700 mg/day: OR=1.84, 95% CI 0.76-4.43; and BBS ≤ 49 points: OR=0.82, 95% CI 0.33-1.99).
Conclusion: Both predictive tools showed acceptable accuracy to identify people with PD at risk of falling recurrently within the next year in this external validation study. Since both tools presented similar AUC, the use of the 3-predictor tool may be considered in clinical practice.
References: [1] Almeida LRS, Valenca GT, Negreiros NN, Pinto EB, & Oliveira-Filho J. (2017) Predictors of Recurrent Falls in People with Parkinson’s Disease and Proposal for a Predictive Tool. Journal of Parkinson’s Disease, 7(2), 313–324.
To cite this abstract in AMA style:
H. Cavalcanti, I. Rosa, M. Piemonte, A. Costa, G. Valença, J. Oliveira-Filho, L. Almeida. EXTERNAL VALIDATION OF TWO PREDICTIVE TOOLS TO IDENTIFY PEOPLE WITH PARKINSON’S DISEASE AT RISK OF RECURRENT FALLS [abstract]. Mov Disord. 2021; 36 (suppl 1). https://www.mdsabstracts.org/abstract/external-validation-of-two-predictive-tools-to-identify-people-with-parkinsons-disease-at-risk-of-recurrent-falls/. Accessed November 21, 2024.« Back to MDS Virtual Congress 2021
MDS Abstracts - https://www.mdsabstracts.org/abstract/external-validation-of-two-predictive-tools-to-identify-people-with-parkinsons-disease-at-risk-of-recurrent-falls/