ArticleJournal of clinical neurology (Seoul, Korea)2020
Heart-Rate-Based Machine-Learning Algorithms for Screening Orthostatic Hypotension.
Article in Journal of clinical neurology (Seoul, Korea), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Use of Valsalva Maneuver to Detect Late-Onset Delayed Orthostatic Hypotension.Hypertension (Dallas, Tex. : 1979) · 2023Trial
- Artificial Intelligence That Changes Clinical Neurology Practice: Translating Algorithms Into Actionable Care.Journal of clinical neurology (Seoul, Korea) · 2026Review
- Predicting vasovagal syncope during head-up tilt test: three machine learning approaches.Frontiers in neuroinformatics · 2026Article
- Heart rate variability and its association with symptoms of orthostatic hypotension in spinal cord injury.The journal of spinal cord medicine · 2025Article
- Digital Healthcare in Future Medicine: From Research to Clinical Practice in Neurology.Journal of clinical neurology (Seoul, Korea) · 2025Article
- Scale for Ocular Motor Disorders in Ataxia (SODA) in Patients with Multiple System Atrophy.Cerebellum (London, England) · 2024Article
- Sympathetic dysfunction as an early indicator of autonomic involvement in Parkinson's disease.Clinical autonomic research : official journal of the Clinical Autonomic Research Society · 2024Article
- Augmented ocular vestibular-evoked myogenic potentials in postural orthostatic tachycardia syndrome.Clinical autonomic research : official journal of the Clinical Autonomic Research Society · 2023Article
- The Intersection of Technology and Humanity: Exploring the Ethics and Potential of Artificial Intelligence in Medicine.Journal of clinical neurology (Seoul, Korea) · 2023Article
- Clinical application of functional near-infrared spectroscopy for burn assessment.Frontiers in bioengineering and biotechnology · 2023Article
- Utricular dysfunction in patients with orthostatic hypotension.Clinical autonomic research : official journal of the Clinical Autonomic Research Society · 2022Article
- Differentiating amnestic from non-amnestic mild cognitive impairment subtypes using graph theoretical measures of electroencephalography.Scientific reports · 2022Article
- Frontal lobe hemodynamics detected by functional near-infrared spectroscopy during head-up tilt table tests in patients with electrical burns.Frontiers in human neuroscience · 2022Article
- Regional Gray Matter Volume Changes in Parkinson's Disease with Orthostatic Hypotension.Brain sciences · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
background and purposeMany elderly patients are unable to actively stand up by themselves and have contraindications to performing the head-up tilt test (HUTT). We aimed to develop screening algorithms for diagnosing orthostatic hypotension (OH) before performing the HUTT.
methodsThis study recruited 663 patients with orthostatic intolerance (78 with and 585 without OH, as confirmed by the HUTT) and compared their clinical characteristics. Univariate and multivariate analyses were performed to investigate potential predictors of an OH diagnosis. Machine-learning algorithms were applied to determine whether the accuracy of OH prediction could be used for screening OH without performing the HUTT.
resultsDifferences between expiration and inspiration (E-I differences), expiration:inspiration ratios (E:I ratios), and Valsalva ratios were smaller in patients with OH than in those without OH. The univariate analysis showed that increased age and baseline systolic blood pressure (BP) as well as decreased E-I difference, E:I ratio, and Valsalva ratio were correlated with OH. In the multivariate analysis, increased baseline systolic BP and decreased Valsalva ratio were found to be independent predictors of OH. Using those variables as input features, the classification accuracies of the support vector machine,
conclusionsWe have identified clinical parameters that are strongly associated with OH. Machine-learning analysis using those parameters was highly accurate in differentiating OH from non-OH patients. These parameters could be useful screening factors for OH in patients who are unable to perform the HUTT.
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