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Correlation Analysis of Persistence and Recurrence of Stroke in Young Patients Based on Big Data in Healthcare

Wei Duan, Xiaojun Fu, Ping Yuan

    Alternative Therapies in Health and Medicine
    |March 18, 2023
    PubMed

    Insights

    Big data analysis reveals key factors influencing stroke recurrence in young adults. Understanding these elements, including blood pressure and diabetes, is crucial for effective stroke treatment and prevention strategies.

    Area of Science:

    • Neurology
    • Healthcare Big Data Analytics
    • Public Health

    Background:

    • Stroke remains a significant health concern, particularly its recurrence in young patients.
    • Big data in healthcare offers novel approaches to analyze complex health patterns.
    • Understanding stroke recurrence factors is vital for improving patient outcomes.

    Purpose of the Study:

    • To analyze the correlation between stroke persistence and recurrence in young patients using big data.
    • To identify key clinical and lifestyle factors associated with stroke recurrence.
    • To apply the Apriori parallelization algorithm based on compression matrix (PBCM) for data analysis.

    Main Methods:

    • Randomized division of patients into two groups for comparative analysis.
    • Application of the PBCM algorithm within a big data healthcare framework.
    • Analysis of factors including fasting blood glucose (FBG), HbA1c, blood pressure (BP), blood lipids, alcohol consumption, and smoking.

    Main Results:

    • Multiple factors significantly correlate with stroke recurrence (P < .05).
    • Identified factors include NIHSS score, FBG, HbA1c, TG, HDL, BMI, hospital stay duration, gender, high BP, diabetes, heart disease, and smoking.
    • These factors impact brain health and stroke recurrence rates.

    Conclusions:

    • Stroke recurrence in young patients is influenced by a combination of clinical and lifestyle factors.
    • The findings underscore the need for increased attention to stroke recurrence in patient treatment.
    • Big data analytics provides a powerful tool for uncovering complex relationships in healthcare data.

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