Objectives: To investigate whether machine learning (ML)-based center of pressure (COP) analysis for gait assessment, when used in conjunction with clinical information, offers additive benefits in predicting functional outcomes in patients with acute ischemic stroke.
Design: A prospective, single-center cohort study.
Setting: A tertiary hospital setting.
Participants: A total of 185 patients with acute ischemic stroke, capable of walking 10 m with or without a gait aid by day 7 postadmission. From these patients, 10,804 pairs of consecutive footfalls were included for analysis.
Interventions: Not applicable.
Main Outcome Measures: The dependent variable was a 3-month poor functional outcome, defined as modified Rankin scale score ≥2. For independent variables, 65 clinical variables including demographics, anthropometrics, comorbidities, laboratory data, questionnaires, and drug history were included. Gait function was evaluated using a pressure-sensitive mat. Time-series COP data were parameterized into spatial and temporal variables and analyzed with logistic regression and 2 ML models (light gradient-boosting machine and multilayer perceptron [MLP]). We derived GAIT-AI output scores from the best-performing model analyzed COP data and constructed multivariable logistic regression models using clinical variables and the GAIT scores.
Results: Among the included patients, 70 (37.8%) experienced unfavorable outcomes. The MLP model demonstrated the highest predictive performance with an area under the receiver operating characteristic curve (AUROC) of 0.799. Multivariable logistic regression identified age, initial National Institutes of Health Stroke Scale, and initial Fall Efficacy Scale-International as associated factors with unfavorable outcomes. The combined multivariable logistic regression incorporating COP-derived output scores improved the AUROC to 0.812.
Conclusions: Gait function, assessed through COP analysis, serves as a significant predictor of functional outcome in patients with acute ischemic stroke. ML-based COP analysis, when combined with clinical data, enhances the prediction of poor functional outcomes.
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http://dx.doi.org/10.1016/j.apmr.2024.08.006 | DOI Listing |
BMC Med
December 2024
National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 167, Beilishi Rd, Beijing, 100037, Xicheng District, China.
Background: Low-density lipoprotein cholesterol (LDL-C) is a well-recognized risk factor for cardiovascular diseases. However, several clinical studies demonstrated an inverse association between LDL-C and mortality risk in patients with acute myocardial infarction (AMI), known as the lipid paradox. This study aims to investigate the potential impact of inflammation on the association between LDL-C levels and mortality risks.
View Article and Find Full Text PDFCardiol Ther
December 2024
Internal Medicine Medical Affairs, Pfizer Japan Inc, 3-22-7 Yoyogi, Shibuya-Ku, Tokyo, 151-8589, Japan.
Introduction: Very elderly patients with nonvalvular atrial fibrillation (NVAF) are at high risk for both ischemic and hemorrhagic events. This study aimed to understand the characteristics and real-world treatment of very elderly patients with NVAF in Japan.
Methods: We conducted a retrospective analysis of electronic health records and claims data from acute care hospitals for very elderly patients with NVAF with medical records available on or after their 80th birthday.
Am J Cardiol
December 2024
Jinan Hospital, 63-1 Lishan Road, Jinan City 250013.
Individual cerebral small vessel disease (SVD) markers independently predict poor prognosis following stroke. However, the impact of a single SVD, especially cumulative SVD burden on outcomes in acute ischemic stroke (AIS) after intravenous thrombolysis remains unclear. This work evaluated the occurrence of small vessel disease (SVD) in AIS patients who were treated with intravenous thrombolytic therapy by using multimodal MRI imaging.
View Article and Find Full Text PDFClin Neuroradiol
December 2024
Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary and Foothills Medical Centre, Calgary, AB, Canada.
Background & Purpose: Non-stenotic (< 50%) carotid plaques are increasingly recognized as a potential mechanism for ischemic stroke. We assessed the prevalence of such plaques in patients with low-risk neurologic events and evidence of DWI (Diffusion Weighted Imaging)-positive ischemia.
Methods: This is a post-hoc exploratory analysis from the DOUBT study, a prospective, observational, multicenter study of patients with low-risk transient or persistent minor focal neurological symptoms.
Neurotherapeutics
December 2024
Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States; Neurocritical Care Division, Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, MD, United States; Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States; Department of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States. Electronic address:
Brain ischemia is a major cause of neurological dysfunction and mortality worldwide. It occurs not only acutely, such as in acute ischemic stroke (AIS), but also in chronic conditions like cerebral small vessel disease (cSVD). Any other conditions resulting in brain hypoperfusion can also lead to ischemia.
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