ArticlePloS one2017
Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- Accuracy of wearable devices in predicting falls in older adults: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- Lipedema Reduction Surgery Improves Pain, Mobility, Physical Function, and Quality of Life: Case Series Report.Plastic and reconstructive surgery. Global open · 2023Article
- Clinical evaluation of fall risk in older adults who use lower-limb prostheses: A scoping review.Journal of the American Geriatrics Society · 2023Article
- Neurorehabilitation in Multiple Sclerosis-A Review of Present Approaches and Future Considerations.Journal of clinical medicine · 2022Review
- Intensive Neurorehabilitation and Gait Improvement in Progressive Multiple Sclerosis: Clinical, Kinematic and Electromyographic Analysis.Brain sciences · 2022Article
- Anticholinergic and Sedative Medications and Dynamic Gait Parameters in Older Patients.Drugs & aging · 2021Article
- Detecting Fall Risk and Frailty in Elders with Inertial Motion Sensors: A Survey of Significant Gait Parameters.Sensors (Basel, Switzerland) · 2021Review
- Diagnosing gait disorders based on angular variations of knee and ankle joints utilizing a developed wearable motion sensor.Healthcare technology letters · 2021Article
- Task matters: an investigation on the effect of different secondary tasks on dual-task gait in older adults.BMC geriatrics · 2021Article
- Objectifying clinical gait assessment: using a single-point wearable sensor to quantify the spatiotemporal gait metrics of people with lumbar spinal stenosis.Journal of spine surgery (Hong Kong) · 2021Article
- Feasibility of Sensor Technology for Balance Assessment in Home Rehabilitation Settings.Sensors (Basel, Switzerland) · 2021Article
- Gait Analysis with Wearables Can Accurately Classify Fallers from Non-Fallers: A Step toward Better Management of Neurological Disorders.Sensors (Basel, Switzerland) · 2020Article
- Classification of Neurological Patients to Identify Fallers Based on Spatial-Temporal Gait Characteristics Measured by a Wearable Device.Sensors (Basel, Switzerland) · 2020Article
- The detection of age groups by dynamic gait outcomes using machine learning approaches.Scientific reports · 2020Article
- Descriptive Evaluation and Accuracy of a Mobile App to Assess Fall Risk in Seniors: Retrospective Case-Control Study.JMIR aging · 2020Article
- Key factors for the assessment of mobility in advanced dementia: A consensus approach.Alzheimer's & dementia (New York, N. Y.) · 2019Article
- Beam Walking to Assess Dynamic Balance in Health and Disease: A Protocol for the "BEAM" Multicenter Observational Study.Gerontology · 2019Observational
- Machine learning in human movement biomechanics: Best practices, common pitfalls, and new opportunities.Journal of biomechanics · 2018Review
- Developing clinical procedures to diagnose specific motor control impairments associated with low back pain: prone hip extension (PHE), active straight leg raise (ASLR), and gait variability.The Journal of the Canadian Chiropractic Association · 2017Article
- Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment.Journal of neuroengineering and rehabilitation · 2017Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fall prediction in geriatric patients remains challenging because the increased fall risk involves multiple, interrelated factors caused by natural aging and/or pathology. Therefore, we used a multi-factorial statistical approach to model categories of modifiable fall risk factors among geriatric patients to identify fallers with highest sensitivity and specificity with a focus on gait performance. Patients (n = 61, age = 79; 41% fallers) underwent extensive screening in three categories: (1) patient characteristics (e.g., handgrip strength, medication use, osteoporosis-related factors) (2) cognitive function (global cognition, memory, executive function), and (3) gait performance (speed-related and dynamic outcomes assessed by tri-axial trunk accelerometry). Falls were registered prospectively (mean follow-up 8.6 months) and one year retrospectively. Principal Component Analysis (PCA) on 11 gait variables was performed to determine underlying gait properties. Three fall-classification models were then built using Partial Least Squares-Discriminant Analysis (PLS-DA), with separate and combined analyses of the fall risk factors. PCA identified 'pace', 'variability', and 'coordination' as key properties of gait. The best PLS-DA model produced a fall classification accuracy of AUC = 0.93. The specificity of the model using patient characteristics was 60% but reached 80% when cognitive and gait outcomes were added. The inclusion of cognition and gait dynamics in fall classification models reduced misclassification. We therefore recommend assessing geriatric patients' fall risk using a multi-factorial approach that incorporates patient characteristics, cognition, and gait dynamics.
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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.