ArticleFrontiers in aging neuroscience2022
Development of stroke predictive model in community-dwelling population: A longitudinal cohort study in Southeast China.
Article in Frontiers in aging neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Development of a conceptual model of intertemporal decision-making ability for young and middle-aged stroke patients within physical activity: a qualitative study.Frontiers in psychology · 2026Article
- The most efficient machine learning algorithms in stroke prediction: A systematic review.Health science reports · 2024Review
- The association of changes in the Chinese visceral adiposity index and cardiometabolic diseases: a cohort study.Diabetology & metabolic syndrome · 2024Article
- Gender differences in risk factors for ischemic stroke: a longitudinal cohort study in East China.BMC neurology · 2024Article
- SRPNet: stroke risk prediction based on two-level feature selection and deep fusion network.Frontiers in physiology · 2024Article
- External Validation and Recalibration of a Mortality Prediction Model for Patients with Ischaemic Stroke.Journal of clinical medicine · 2023Article
- Association between Chinese visceral adiposity index and risk of stroke incidence in middle-aged and elderly Chinese population: evidence from a large national cohort study.Journal of translational medicine · 2023Article
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6 authors.
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Abstract
Background: Stroke has been the leading cause of death and disability in the world. Early recognition and treatment of stroke could effectively limit brain damage and vastly improve outcomes. This study aims to develop a highly accurate prediction model of stroke with a list of lifestyle behaviors and clinical characteristics to distinguish high-risk groups in the community-dwelling population. Methods: Participants in this longitudinal cohort study came from the community-dwelling population in Suzhou between November 2018 and June 2019. A total of 4,503 residents participated in the study, while stroke happened to 22 participants in the 2-year follow-up period. Baseline information of each participant was acquired and enrolled in this study. Results: A highly accurate prediction model of stroke was constructed by age, gender, exercise, meat and vegetarian diet, BMI, waist circumference, systolic blood pressure, Chinese visceral adiposity index, and waist-height ratio. Two additional prediction models for overweight and non-overweight individuals were formulated based on crucial risk factors, respectively. The stroke risk prediction models for community-dwelling and overweight populations had accuracies of 0.79 and 0.82, severally. Gender and exercise were significant predictors (χ Conclusion: The predictive models could predict 2-year stroke with high accuracy. The models provided an effective tool for identifying high-risk groups and supplied guidance for improving prevention and treatment strategies in community-dwelling population.
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