Andrea Sturchio1,2,3, Alok K Dwivedi4, Luca Marsili1, Aaron Hadley5, Gabriele Sobrero1,6, Dustin Heldman5, Simona Maule6, Leonardo Lopiano7, Cristoforo Comi8, Maurizio Versino3,9, Alberto J Espay1, Aristide Merola10. 1. Department of Neurology, Gardner Family Center for Parkinson's Disease and Movement Disorders, University of Cincinnati, Cincinnati, OH, USA. 2. University of Pavia, Pavia, Italy. 3. Neurology Unit, Varese ASST Sette Laghi, Ospedale di Circolo, Varese, Italy. 4. Division of Biostatistics and Epidemiology, Department of Molecular and Translational Medicine, Texas Tech University Health Sciences Center, El Paso, TX, USA. 5. Great Lakes NeuroTechnologies, Cleveland, OH, USA. 6. Ambulatorio per le Disautonomie e l'Ipotensione Ortostatica, AOU Città della Salute e della Scienza di Torino, Turin, Italy. 7. Department of Neuroscience "Rita Levi Montalcini", University of Torino, Turin, Italy. 8. Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy. 9. DMC, University of Insubria, Varese, Italy. 10. Department of Neurology, Wexner Medical Center, Ohio State University, Columbus, OH, USA. Aristide.Merola@osumc.edu.
Abstract
OBJECTIVE: We sought to test the hypothesis that technology could predict the risk of falls in Parkinson's disease (PD) patients with orthostatic hypotension (OH) with greater accuracy than in-clinic assessment. METHODS: Twenty-six consecutive PD patients with OH underwent clinical (including home-like assessments of activities of daily living) and kinematic evaluations of balance and gait as well as beat-to-beat blood pressure (BP) monitoring to estimate their association with the risk of falls. Fall frequency was captured by a diary collected prospectively over 6 months. When applicable, the sensitivity, specificity, and diagnostic accuracy were measured using the area under the receiver operating characteristics curve (AUC). Additional in-clinic assessments included the OH Symptom Assessment (OHSA), the OH Daily Activity Score (OHDAS), and the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). RESULTS: The prevalence of falls was 53.8% over six months. There was no association between the risk of falls and test of gait and postural stability (p ≥ 0.22) or home-like activities of daily living (p > 0.08). Conversely, kinematic data (waist sway during time-up-and-go, jerkiness, and centroidal frequency during postural sway with eyes-opened) predicted the risk of falls with high sensitivity and specificity (> 80%; AUC ≥ 0.81). There was a trend for higher risk of falls in patients with orthostatic mean arterial pressure ≤ 75 mmHg. CONCLUSIONS: Kinematic but not clinical measures predicted falls in PD patients with OH. Orthostatic mean arterial pressure ≤ 75 mmHg may represent a hemodynamic threshold below which falls become more prevalent, supporting the aggressive deployment of corrective measures.
OBJECTIVE: We sought to test the hypothesis that technology could predict the risk of falls in Parkinson's disease (PD) patients with orthostatic hypotension (OH) with greater accuracy than in-clinic assessment. METHODS: Twenty-six consecutive PD patients with OH underwent clinical (including home-like assessments of activities of daily living) and kinematic evaluations of balance and gait as well as beat-to-beat blood pressure (BP) monitoring to estimate their association with the risk of falls. Fall frequency was captured by a diary collected prospectively over 6 months. When applicable, the sensitivity, specificity, and diagnostic accuracy were measured using the area under the receiver operating characteristics curve (AUC). Additional in-clinic assessments included the OH Symptom Assessment (OHSA), the OH Daily Activity Score (OHDAS), and the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). RESULTS: The prevalence of falls was 53.8% over six months. There was no association between the risk of falls and test of gait and postural stability (p ≥ 0.22) or home-like activities of daily living (p > 0.08). Conversely, kinematic data (waist sway during time-up-and-go, jerkiness, and centroidal frequency during postural sway with eyes-opened) predicted the risk of falls with high sensitivity and specificity (> 80%; AUC ≥ 0.81). There was a trend for higher risk of falls in patients with orthostatic mean arterial pressure ≤ 75 mmHg. CONCLUSIONS: Kinematic but not clinical measures predicted falls in PD patients with OH. Orthostatic mean arterial pressure ≤ 75 mmHg may represent a hemodynamic threshold below which falls become more prevalent, supporting the aggressive deployment of corrective measures.
Authors: Christopher L Pulliam; Dustin A Heldman; Elizabeth B Brokaw; Thomas O Mera; Zoltan K Mari; Michelle A Burack Journal: IEEE Trans Biomed Eng Date: 2017-04-25 Impact factor: 4.538
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