Evaluation of the Utility of the ‘Velocity Field Diagram’ and ‘Timed-Up-and-Go Test‘ as Fall Screening Tools Among Community-Dwelling Older Adults: An Observational Study

Background: Evidence from systematic reviews demonstrated that gait variables are the most reliable predictors of future falls, yet are rarely included in fall screening tools. It explains why most tools have higher specificity than sensitivity, hence may be misleading/detrimental to care. The diagnostic utility of a gait analytical tool-velocity field diagram (VFD), and “Timed-up-and-go test (TUG)’- commonly used in Nigeria, was therefore compared to a gold standard (known fallers) to evaluate their accuracy and utility in fall screening. Method: This is an observational study of 500 older adults (280 fallers and 220 non-fallers), recruited by convenience sampling technique at a community health forum on fall prevention. The number of steps and time they spent to complete a-7metre distance was determined and used to calculate the stride length, stride frequency, and velocity, which regression lines were used to form the VFD. TUG test was simultaneously conducted to discriminate fallers from non-fallers. The cut-off points for falls: TUG times ≥13.5 seconds; and VFD’s intersection point of the stride frequency, and velocity regression lines (E1) ≥3.5velots. Receiver operating characteristic (ROC) area under the curves (AUC) was used to explore the ability of the E1≥3.5velots to discriminate between fallers and non-fallers. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the VFD and TUG were determined. Alpha was set at p<0.05. Results: The sensitivity, specificity, PPV and NPV of the VFD versus TUG is 71%, 27%, 72%, and 43%, versus 39%, 59%, 40%, and 43%, respectively. The ROC’s AUC were 0.74(95%CI:0.597,0.882, p=0.001) for the VFD. The optimal categorizations for discrimination between fallers/non-fallers were ≥3.78 versus ≤3.78 for VFD (fallers and non-fallers prevalence 60.71% versus 95.45%, respectively), with an accuracy of 0.76 unlike TUG with AUC=0.53 (95% CI:0.353, 0.700, p=0.762), and an accuracy of 0.68, and optimal characterization of ≥12.81s versus ≤12.81 (fallers and non-fallers prevalence = 92.86% versus 36.36%, respectively). Conclusion: The VFD demonstrated a fair discriminatory power and greater accuracy in identifying fallers than the TUG. Therefore, the VFD could serve as a primary tool in screening those at the risk of fall than the TUG.

Identifying falls remotely in people with multiple sclerosis

Background Falling is common in people with multiple sclerosis (MS) but tends to be under-ascertained and under-treated. Objective To evaluate fall risk in people with MS. Methods Ninety-four people with MS, able to walk > 2 min with or without an assistive device (Expanded Disability Status Scale (EDSS ≤ 6.5) were recruited. Clinic-based measures were recorded at baseline and 1 year. Patient-reported outcomes (PROs), including a fall survey and the MS Walking Scale (MSWS-12), were completed at baseline, 1.5, 3, 6, 9, and 12 months. Average daily step counts (STEPS) were recorded using a wrist-worn accelerometer. Results 50/94 participants (53.2%) reported falling at least once. Only 56% of participants who reported a fall on research questionnaires had medical-record documented falls. Fallers had greater disability [median EDSS 5.5 (IQR 4.0–6.0) versus 2.5 (IQR 1.5–4.0), p < 0.001], were more likely to have progressive MS (p = 0.003), and took fewer STEPS (mean difference − 1,979, p = 0.007) than Non-Fallers. Stepwise regression revealed MSWS-12 as a major predictor of future falls. Conclusions Falling is common in people with MS, under-reported, and under-ascertained by neurologists in clinic. Multimodal fall screening in clinic and remotely may help improve patient care by identifying those at greatest risk, allowing for timely intervention and referral to specialized physical rehabilitation.