Background: There is a need for simple clinical tools that can objectively assess the fall risk in people with dementia. Wearable sensors seem to have the potential for fall prediction; however, there has been limited work performed in this important area. Objective: To explore the validity of sensor-derived physical activity (PA) parameters for predicting future falls in people with dementia. To compare sensor-based fall risk assessment with conventional fall risk measures. Methods: This was a cohort study of people with confirmed dementia discharged from a geriatric rehabilitation ward. PA was quantified using 24-hour motion-sensor monitoring at the beginning of the study. PA parameters (percentage of walking, standing, sitting, and lying; duration of single walking, standing, and sitting bouts) were extracted using specific algorithms. Conventional assessment included performance-based tests (Timed Up and Go Test, Performance-Oriented Mobility Assessment, 5-chair stand) and questionnaires (cognition, ADL status, fear of falling, depression, previous faller). Outcome measures were fallers (at least one fall in the 3-month follow-up period) versus non-fallers. Results: 77 people were included in the study (age 81.8 ± 6.3; community-dwelling 88%, institutionalized 12%). Surprisingly, fallers and non-fallers did not differ on any conventional assessment (p = 0.069-0.991), except for ‘previous faller' (p = 0.006). Interestingly, several PA parameters discriminated between the groups. The ‘walking bout average duration', ‘longest walking bout duration' and ‘walking bout duration variability' were lower in fallers, compared to non-fallers (p = 0.008-0.027). The ‘standing bout average duration' was higher in fallers (p = 0.050). Two variables, ‘walking bout average duration' [odds ratio (OR) 0.79, p = 0.012] and ‘previous faller' (OR 4.44, p = 0.007) were identified as independent predictors for falls. The OR for a ‘walking bout average duration' <15 s for predicting fallers was 6.30 (p = 0.020). Combining ‘walking bout average duration' and ‘previous faller' improved fall prediction (OR 7.71, p < 0.001, sensitivity/specificity 72%/76%). Discussion: Results demonstrate that sensor-derived PA parameters are independent predictors of the fall risk and may have higher diagnostic accuracy in persons with dementia compared to conventional fall risk measures. Our findings highlight the potential of telemonitoring technology for estimating the fall risk. Results should be confirmed in a larger study and by measuring PA over a longer period of time.

– The COVID-19 pandemic has had and continues to have major impacts on planned and ongoing clinical trials. Its effects on trial data create multiple potential statistical issues. The scale of impact is unprecedented, but when viewed individually, many of the issues are well defined and feasible to address. A number of strategies and recommendations are put forward to assess and address issues related to estimands, missing data, validity and modifications of statistical analysis methods, need for additional analyses, ability to meet objectives and overall trial interpretability.

BackgroundPreventing and rehabilitating gait disorders in people with dementia during early disease stage is of high importance for staying independent and ambulating safely. However, the evidence gathered in randomized controlled trials (RCTs) on the effectiveness of exercise training for improving spatio-temporal gait parameters in people with dementia is scarce. The aim of the present study was to determine whether a specific, standardized training regimen can improve gait characteristics in people with dementia.MethodsSixty-one individuals (mean age: 81.9 years) with confirmed mild to moderate stage dementia took part in a 3-month double-blinded outpatient RCT. Subjects in the intervention group (IG) received supervised, progressive resistance and functional group training for 3 months (2 times per week for two hours) specifically developed for people with dementia. Subjects in the control group (CG) conducted a low-intensity motor placebo activity program. Gait characteristics were measured before and after the intervention period using a computerized gait analysis system (GAITRite®).ResultsAdherence to the intervention was excellent, averaging 91.9% in the IG and 94.4% in the CG. The exercise training significantly improved gait speed (P < 0.001), cadence (P = 0.002), stride length (P = 0.008), stride time (P = 0.001), and double support (P = 0.001) in the IG compared to the CG. Effect sizes were large for all gait parameters that improved significantly (Cohen’s d: 0.80-1.27). No improvements were found for step width (P = 0.999), step time variability (P = 0.425) and Walk-Ratio (P = 0.554). Interestingly, low baseline motor status, but not cognitive status, predicted positive training response (relative change in gait speed from baseline).ConclusionThe intensive, dementia-adjusted training was feasible and improved clinically meaningful gait variables in people with dementia. The exercise program may represent a model for preventing and rehabilitating gait deficits in the target group. Further research is required for improving specific gait characteristics such as gait variability in people with dementia.Trial registrationISRCTN49243245