ArticleJournal of atherosclerosis and thrombosis2022
Predictors of Stroke Outcome Extracted from Multivariate Linear Discriminant Analysis or Neural Network Analysis.
Article in Journal of atherosclerosis and thrombosis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning prediction of motor function in chronic stroke patients: a systematic review and meta-analysis.Frontiers in neurology · 2023Pooled it
- Interictal epileptiform activity in the acute stroke phase: an independent predictor of poor outcome.European stroke journal · 2026Article
- Development and validation of a dynamic nomogram for high care dependency during the hospital-family transition periods in older stroke patients.BMC geriatrics · 2024Article
- Construction and validation of machine learning algorithm for predicting depression among home-quarantined individuals during the large-scale COVID-19 outbreak: based on Adaboost model.BMC psychology · 2024Article
- Impact of alkaline phosphatase on clinical outcomes in patients with ischemic stroke: a nationwide registry analysis.Frontiers in neurology · 2024Article
- Alkaline phosphatase and mortality in stroke patients: a systematic review.Annals of translational medicine · 2023Review
- Distinct WBC Trajectories are Associated with the Risks of Incident CVD and All-Cause Mortality.Journal of atherosclerosis and thrombosis · 2023Article
- Review
- Increased Serum Alkaline Phosphatase and Functional Outcome in Patients with Acute Ischemic Stroke Presenting a Low Ankle-Brachial Index.Journal of atherosclerosis and thrombosis · 2022Article
- Baseline Objective Malnutritional Indices as Immune-Nutritional Predictors of Long-Term Recurrence in Patients with Acute Ischemic Stroke.Nutrients · 2022Article
- Nutritional, Anthropometric and Sociodemographic Factors Affecting Fatty Acids Profile of Pregnant Women's Serum at Labour-Chemometric Studies.Nutrients · 2021Article
- Machine learning model for unfavorable outcome prediction in neurosurgical patients: the potential role of liver function markers.Frontiers in neurologyArticle
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimThe prediction of functional outcome is essential in the management of acute ischemic stroke patients. We aimed to explore the various prognostic factors with multivariate linear discriminant analysis or neural network analysis and evaluate the associations between candidate factors, baseline characteristics, and outcome.
methodsAcute ischemic stroke patients (n=1,916) with premorbid modified Rankin Scale (mRS) scores of 0-2 were analyzed. The prediction models with multivariate linear discriminant analysis (quantification theory type II) and neural network analysis (log-linearized Gaussian mixture network) were used to predict poor functional outcome (mRS 3-6 at 3 months) with various prognostic factors added to age, sex, and initial neurological severity at admission.
resultsBoth models revealed that several nutritional statuses and serum alkaline phosphatase (ALP) levels at admission improved the predictive ability. Of the 1,484 patients without missing data, 560 patients (37.7%) had poor outcomes. The patients with poor outcomes had higher ALP levels than those without (294.3±259.5 vs. 246.3±92.5 U/l, P＜0.001). Multivariable logistic analyses revealed that higher ALP levels (1-SD increase) were independently associated with poor stroke outcomes after adjusting for several confounding factors, including the neurological severity, malnutrition status, and inflammation (odds ratio 1.21, 95% confidence interval 1.02-1.49). Several nutritional indicators extracted from prediction models were also associated with poor outcome.
conclusionBoth the multivariate linear discriminant and neural network analyses identified the same indicators, such as nutritional status and serum ALP levels. These indicators were independently associated with functional stroke outcome.
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