
1st STUDENT SCIENTIFIC CONFERENCE OF THE BRAZILIAN ASSOCIATION FOR RESEARCH AND POSTGRADUATE IN PHYSIOTHERAPY (ABRAPG-FT)
More infoThe multifactorial nature of falls in Parkinson's disease (PD) is well described. Clinical aspects (e.g., fear of falling and disease severity) and gait deficits (e.g., difficulties with dual task walking and freezing of gait episodes) are among identified risk factors of falling. However, optimal assessment for the identification of fallers remains unclear.
ObjectivesTo identify clinical and objective gait measures that best discriminate fallers from non-fallers in PD, with suggestions of optimal cutoff scores.
MethodsCross-sectional study composed by 127 individuals with mild to moderate PD classified as fallers (≥2 falls) or non-fallers based on previous 12 months falls. Clinical measures (demographic, motor, cognitive and patient-reported outcomes) were assessed with standard scales/tests. For measuring gait parameters, participants were asked to walk, at a self-selected pace, back and forth on a straight 9-m walkway for 2 minutes in single and dual-task (i.e., forward digit span) conditions, while instrumented with eight, synchronized inertial sensors at the sternum, lumbar spine, bilaterally on the wrists, shins, and feet. We extracted 24 clinical measurements and 39 objective variables from those instruments. Receiver operating characteristic (ROC) curve analysis identified measures (separately and in combination) that best discriminate fallers from non-fallers; we calculated the area under the curve (AUC) and identified optimal cutoff scores (i.e., point closest-to-(0,1) corner).
ResultsThirty-one participants (24.4%) were classified as fallers and 96 (75.6%) as non-fallers. Fallers had more severe motor symptoms and more advanced disease stage than non-fallers. Single gait and clinical measures that best classified fallers were foot strike angle (AUC=0.728; cutoff=14.07°) and the Falls Efficacy Scale International (FES-I; AUC=0.716, cutoff=25.5), respectively. Combinations of clinical+gait measures had higher AUCs than combinations of clinical-only or gait-only measures. The best performing combination included FES-I score, New Freezing of Gait Questionnaire score, foot strike angle and trunk transverse range of motion (AUC=0.85).
ConclusionThe combinations of clinical and gait measures have higher discriminative ability in classifying fallers from non-fallers among people with PD than combinations of clinical-only and gait-only measures.
ImplicationsThe falls consequences represent great independence and autonomy loss for patients and high costs to health-care services. In this context, it is necessary to devote attention to falls management in PD, including the identification of PD-specific markers for risk of falling. Therefore, the use of wearable inertial sensors is useful and can enhance the traditional fall risk assessment in PD.
Conflict of interest: The authors declare no conflict of interest.
Acknowledgment: To participants of Research and Neurofunctional Physiotherapy Group (GPFIN) e for support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - (CAPES).
Ethics committee approval: London-Bloomsbury NHS Research Ethics Committee (and Health Research Authority; 20/LO/1036, 05/10/2020) and the Institutional Review Board of the Oregon Health & Science University (#9903).