ArticleJournal of neurology2021
Fall prediction in neurological gait disorders: differential contributions from clinical assessment, gait analysis, and daily-life mobility monitoring.
Article in Journal of neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 4 of them syntheses that pooled it.
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Who cites it
26 citing papers in PubMed, 4 syntheses or guidelines pooled it, 61 citations in OpenAlex.
- Interpretable and explainable artificial intelligence for wearable sensor-based fall risk assessment in older adults: a systematic review with considerations for prosthetics and orthotics.Frontiers in computational neuroscience · 2026Pooled it
- Performance of digital technologies in assessing fall risks among older adults with cognitive impairment: a systematic review.GeroScience · 2024Pooled it
- Pooled it
- Accidental Falls in Patients with Hyperkinetic Movement Disorders: A Systematic Review.Tremor and other hyperkinetic movements (New York, N.Y.) · 2022Pooled it
- Transcranial alternating current stimulation for treating spinocerebellar ataxia type 3: A randomized controlled trial.Cell reports. Medicine · 2025Trial
- Edge AI-Based Gait-Phase Detection for Closed-Loop Neuromodulation in SCI Mice.Sensors (Basel, Switzerland) · 2026Article
- Assessment of Fall Risk in Neurological Disorders and Technology: Relationship Between Silver Index and Gait Analysis.Sensors (Basel, Switzerland) · 2026Article
- Cross-sectional stratification of fall-related vulnerability in Parkinson's disease through multimodal fusion of speech, gait, facial expression, and upper-limb movement.Frontiers in digital health · 2026Article
- Development of an Artificial Intelligence-Based System for Predicting Fall Risk in Neurological Patients.Sovremennye tekhnologii v meditsine · 2026Article
- Analytical and clinical validation of step counting method in people living with amyotrophic lateral sclerosis.Scientific reports · 2025Article
- Wearable devices in neurological disorders: a narrative review of status quo and perspectives.Annals of translational medicine · 2025Review
- The Effects of Hyperkyphosis on Gait Parameters in Older Adults: A Systematic Review.Health science reports · 2025Review
- Biomarkers in Spinocerebellar Ataxias.Cerebellum (London, England) · 2025Review
- Global, regional, and national burden of falls from 1990 to 2021: a comprehensive analysis with a focus on falls attributable to reduced bone mass and projections to 2045.Frontiers in public health · 2025Article
- Beyond clinical scales: an observational study on instrumental gait analysis and biomechanical patterns in patients with Parkinson's disease.Frontiers in bioengineering and biotechnology · 2025Article
- Mobile Spatiotemporal Gait Segmentation Using an Ear-Worn Motion Sensor and Deep Learning.Sensors (Basel, Switzerland) · 2024Article
- Association between gait video information and general cardiovascular diseases: a prospective cross-sectional study.European heart journal. Digital health · 2024Article
- Human Activity Recognition in a Free-Living Environment Using an Ear-Worn Motion Sensor.Sensors (Basel, Switzerland) · 2024Article
- Accuracy validation of a wearable IMU-based gait analysis in healthy female.BMC sports science, medicine & rehabilitation · 2024Article
- Assessing balance in people with bilateral vestibulopathy using the Mini-Balance Evaluation Systems Test (Mini-BESTest): feasibility and comparison with healthy control data.Journal of neurology · 2023Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveTo evaluate the predictive validity of multimodal clinical assessment outcomes and quantitative measures of in- and off-laboratory mobility for fall-risk estimation in patients with different forms of neurological gait disorders.
methodsThe occurrence, severity, and consequences of falls were prospectively assessed for 6 months in 333 patients with early stage gait disorders due to vestibular, cerebellar, hypokinetic, vascular, functional, or other neurological diseases and 63 healthy controls. At inclusion, participants completed a comprehensive multimodal clinical and functional fall-risk assessment, an in-laboratory gait examination, and an inertial-sensor-based daily mobility monitoring for 14 days. Multivariate logistic regression analyses were performed to identify explanatory characteristics for predicting the (1) the fall status (non-faller vs. faller), (2) the fall frequency (occasional vs. frequent falls), and (3) the fall severity (benign vs. injurious fall) of patients.
results40% of patients experienced one or frequent falls and 21% severe fall-related injuries during prospective fall assessment. Fall status and frequency could be reliably predicted (accuracy of 78 and 91%, respectively) primarily based on patients' retrospective fall status. Instrumented-based gait and mobility measures further improved prediction and provided independent, unique information for predicting the severity of fall-related consequences.
interpretationFalls- and fall-related injuries are a relevant health problem already in early stage neurological gait disorders. Multivariate regression analysis encourages a stepwise approach for fall assessment in these patients: fall history taking readily informs the clinician about patients' general fall risk. In patients at risk of falling, instrument-based measures of gait and mobility provide critical information on the likelihood of severe fall-related injuries.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.