Despite therapeutic advancements, stroke remains a leading cause of death and long-term disability. The quality of current stroke prognostic models varies considerably, whereas prediction models of post-stroke disability and mortality are restricted by the sample size, the range of clinical and risk factors and the clinical applicability in general. Accurate prognostication can ease post-stroke discharge planning and help healthcare practitioners individualize aggressive treatment or palliative care, based on projected life expectancy and clinical course. In this study, we aimed to develop an explainable machine learning methodology to predict functional outcomes of stroke patients at discharge, using the Modified Rankin Scale (mRS) as a binary classification problem. We identified 35 parameters from the admission, the first 72 h, as well as the medical history of stroke patients, and used them to train the model. We divided the patients into two classes in two approaches: "Independent" vs. "Non-Independent" and "Non-Disability" vs. "Disability". Using various classifiers, we found that the best models in both approaches had an upward trend, with respect to the selected biomarkers, and achieved a maximum accuracy of 88.57% and 89.29%, respectively. The common features in both approaches included: age, hemispheric stroke localization, stroke localization based on blood supply, development of respiratory infection, National Institutes of Health Stroke Scale (NIHSS) upon admission and systolic blood pressure levels upon admission. Intubation and C-reactive protein (CRP) levels upon admission are additional features for the first approach and Erythrocyte Sedimentation Rate (ESR) levels upon admission for the second. Our results suggest that the said factors may be important predictors of functional outcomes in stroke patients.
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http://dx.doi.org/10.3390/diagnostics13030532 | DOI Listing |
J Clin Monit Comput
January 2025
Department of Anaesthesiology and Intensive Care, Bicetre hospital, Assistance Publique Hôpitaux de Paris (AP-HP), Le Kremlin Bicetre, France.
Intravenous fluid is administered during high-risk surgery to optimize stroke volume (SV). To assess ongoing need for fluids, the hemodynamic response to a fluid bolus is evaluated using a fluid challenge technique. The Acumen Assisted Fluid Management (AFM) system is a decision support tool designed to ease the application of fluid challenges and thus improve fluid administration during high-risk surgery.
View Article and Find Full Text PDFNeurol Sci
January 2025
Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psychiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21 - 00128, Roma, Italy.
Rheumatol Int
January 2025
Department of Internal Medicine, General Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University, Salzburg, Austria.
Rheumatoid arthritis (RA) is a chronic autoimmune disease marked by systemic inflammation. While RA primarily affects the joints, its systemic effects may lead to an increased cerebro- and cardiovascular risk. Atherosclerosis of the carotid arteries is a significant risk factor for cerebrovascular events and serves as a surrogate marker for cardiovascular risk.
View Article and Find Full Text PDFAnn Neurol
January 2025
Department of Neurology, Boston Medical Center and Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA.
Objective: This study assesses whether longitudinal quantitative pupillometry predicts neurological deterioration after large middle cerebral artery (MCA) stroke and determines how early changes are detectable.
Methods: This prospective, single-center observational cohort study included patients with large MCA stroke admitted to Boston Medical Center's intensive care unit (2019-2024). Associations between time-to-neurologic deterioration and quantitative pupillometry, including Neurological Pupil Index (NPi), were assessed using Cox proportional hazards models with time-dependent covariates adjusted for age, sex, and Alberta Stroke Program Early CT Score.
Appl Neuropsychol Adult
January 2025
University Department of Neurology, Sestre Milosrdnice University Hospital Center, Zagreb, Croatia.
Unlabelled: Greater empirical and scientific attention is still put on patients with left brain hemisphere (LBH) damage where language impairments are common and expected. In patients with RBH damage, language assessment is therefore rarely done in the acute phase of stroke recovery.
Purpose: To investigate language impairments in the acute phase of stroke using a Croatian standardized language battery for the first time and compare patients with RBH stroke, LBH stroke and healthy individuals.
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