Sotirios A Parashos1, Bastiaan R Bloem1, Nina M Browner1, Nir Giladi1, Tanya Gurevich1, Jeffrey M Hausdorff1, Ying He1, Kelly E Lyons1, Zoltan Mari1, John C Morgan1, Bart Post1, Peter N Schmidt1, Catherine L Wielinski1. 1. Struthers Parkinson's Center (SAP, CLW), HealthPartners, Golden Valley, MN; Parkinson Center Nijmegen (BRB, BP), Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Department of Neurology, the Netherlands; Department of Neurology (NMB), University of North Carolina at Chapel Hill; Neurological Institute (NG, TG, JMH), Tel Aviv Sourasky Medical Center, Sackler School of Medicine, and Sagol School of Neuroscience, Tel-Aviv University, Israel; Department of Mathematics (YH), Clarkson University, Potsdam, NY; University of Kansas Medical Center Parkinson's Disease Center (KEL), Kansas City; Department of Neurology (ZM), Johns Hopkins University, Baltimore, MD, currently at Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV; Movement Disorders Program (JCM), NPF Center of Excellence, Department of Neurology, Medical College of Georgia, Augusta University; Parkinson's Foundation (PNS), Miami, FL; and Department of Biostatistics (SSW), University of Florida, Gainesville.
Abstract
BACKGROUND: We undertook this study to identify patients with Parkinson disease (PD) with no or rare falls who may progress to frequent falling by their next annual follow-up visit. METHODS: We analyzed data in the National Parkinson Foundation Quality Improvement Initiative database to identify factors predicting which patients with PD with no or rare falls at the baseline visit will report at least monthly falls at the annual follow-up visit. Multivariable models were constructed using logistic regression. Variables were introduced in 4 blocks: in the 1st block, variables present at or before the baseline visit were entered; in the 2nd, baseline visit assessments; in the 3rd, interventions implemented during baseline visit; and, in the 4th block, changes in comorbidities, living situation, and treatment between visits. RESULTS: Of 3,795 eligible participants, 3,276 (86.3%) reported no or rare falls at baseline visit, and of them, 382 (11.7%) reported at least monthly falls at follow-up visit. Predictors included female sex, <90% diagnostic certainty, motor fluctuations, levodopa treatment, antidepressant treatment, prior deep brain stimulation (DBS), worse quality of life, Hoehn & Yahr stage 2 or 3, worse semantic fluency, and, between visits, addition of amantadine, referral to occupational therapy, social services, or DBS, new diagnoses of cancer or osteoarthritis, and increased emergency visits. CONCLUSIONS: This large-scale analysis identified several predictors of progression to falling in PD. Such identifiers may help target patient subgroups for falls prevention intervention. Some factors are modifiable, offering opportunities for developing such interventions.
BACKGROUND: We undertook this study to identify patients with Parkinson disease (PD) with no or rare falls who may progress to frequent falling by their next annual follow-up visit. METHODS: We analyzed data in the National Parkinson Foundation Quality Improvement Initiative database to identify factors predicting which patients with PD with no or rare falls at the baseline visit will report at least monthly falls at the annual follow-up visit. Multivariable models were constructed using logistic regression. Variables were introduced in 4 blocks: in the 1st block, variables present at or before the baseline visit were entered; in the 2nd, baseline visit assessments; in the 3rd, interventions implemented during baseline visit; and, in the 4th block, changes in comorbidities, living situation, and treatment between visits. RESULTS: Of 3,795 eligible participants, 3,276 (86.3%) reported no or rare falls at baseline visit, and of them, 382 (11.7%) reported at least monthly falls at follow-up visit. Predictors included female sex, <90% diagnostic certainty, motor fluctuations, levodopa treatment, antidepressant treatment, prior deep brain stimulation (DBS), worse quality of life, Hoehn & Yahr stage 2 or 3, worse semantic fluency, and, between visits, addition of amantadine, referral to occupational therapy, social services, or DBS, new diagnoses of cancer or osteoarthritis, and increased emergency visits. CONCLUSIONS: This large-scale analysis identified several predictors of progression to falling in PD. Such identifiers may help target patient subgroups for falls prevention intervention. Some factors are modifiable, offering opportunities for developing such interventions.
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