Motor dual-tasking deficits predict falls in Parkinson's disease: A prospective study.

INTRODUCTION: Falls severely affect lives of Parkinson's disease (PD) patients. Cognitive impairment including dual-tasking deficits contribute to fall risk in PD. However, types of dual-tasking deficits preceding falls in PD are still unclear. METHODS: Walking velocities during box-checking and subtracting serial 7s were assessed twice a year in 40 PD patients over 2.8 ± 1.0 years. Fourteen patients reported a fall within this period (4 excluded fallers already reported falls at baseline). Their dual-task costs (DTC; mean ± standard deviation) 4.2 ± 2.2 months before the first fall were compared with 22 patients never reporting falls. ROC analyses and logistic regressions accounting for DTC, UPDRS-III and disease duration were used for faller classification and prediction. RESULTS: Only walking/box-checking predicted fallers. Fallers showed higher DTC for walking while box-checking, p = 0.029, but not for box-checking while walking, p = 0.178 (combined motor DTC, p = 0.022), than non-fallers. Combined motor DTC classified fallers and non-fallers (area under curve: 0.75; 95% confidence interval, CI: 0.60-0.91) with 71.4% sensitivity (95%CI: 41.9%-91.6%) and 77.3% specificity (54.6%-92.2%), and significantly predicted future fallers (p = 0.023). Here, 20.4%-points higher combined motor DTC (i.e. the mean difference between fallers and non-fallers) was associated with a 2.6 (1.1-6.0) times higher odds to be a future faller. CONCLUSION: Motor dual-tasking is a potentially valuable predictor of falls in PD, suggesting that avoiding dual task situations as well as specific motor dual-task training might help to prevent falls in PD. These findings and their therapeutic relevance need to be further validated in PD patients without fall history, in early PD stages, and with various motor-motor dual-task challenges.

Insulin-Like Growth Factor 1 (IGF-1) in Parkinson's Disease: Potential as Trait-, Progression- and Prediction Marker and Confounding Factors.

INTRODUCTION: Biomarkers indicating trait, progression and prediction of pathology and symptoms in Parkinson's disease (PD) often lack specificity or reliability. Investigating biomarker variance between individuals and over time and the effect of confounding factors is essential for the evaluation of biomarkers in PD, such as insulin-like growth factor 1 (IGF-1). MATERIALS AND METHODS: IGF-1 serum levels were investigated in up to 8 biannual visits in 37 PD patients and 22 healthy controls (HC) in the longitudinal MODEP study. IGF-1 baseline levels and annual changes in IGF-1 were compared between PD patients and HC while accounting for baseline disease duration (19 early stage: ≤3.5 years; 18 moderate stage: >4 years), age, sex, body mass index (BMI) and common medical factors putatively modulating IGF-1. In addition, associations of baseline IGF-1 with annual changes of motor, cognitive and depressive symptoms and medication dose were investigated. RESULTS: PD patients in moderate (130±26 ng/mL; p = .004), but not early stages (115±19, p>.1), showed significantly increased baseline IGF-1 levels compared with HC (106±24 ng/mL; p = .017). Age had a significant negative correlation with IGF-1 levels in HC (r = -.47, p = .028) and no correlation in PD patients (r = -.06, p>.1). BMI was negatively correlated in the overall group (r = -.28, p = .034). The annual changes in IGF-1 did not differ significantly between groups and were not correlated with disease duration. Baseline IGF-1 levels were not associated with annual changes of clinical parameters. DISCUSSION: Elevated IGF-1 in serum might differentiate between patients in moderate PD stages and HC. However, the value of serum IGF-1 as a trait-, progression- and prediction marker in PD is limited as IGF-1 showed large inter- and intraindividual variability and may be modulated by several confounders.