Nevin Manimala Statistics

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

Altern Ther Health Med. 2023 Mar 20:AT7813. Online ahead of print.


This study aims to analyze the correlation between the persistence and recurrence of stroke in young patients via big data in healthcare. It provides an in-depth introduction to the background of big data in healthcare and a detailed description of stroke symptoms, so as to better apply the Apriori parallelization algorithm based on compression matrix (PBCM) algorithm against the background of big data in healthcare to analyze it. In our study, patients were randomly divided into 2 groups. By observing the different persistent relationships in the groups, the factors affecting the patients’ fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), blood pressure (BP), blood lipids, alcohol consumption, smoking and so on were analyzed. The National Institute of Health Stroke Scale (NIHSS) score, FBG, HbA1c, triglycerides (TG), high-density lipoprotein (HDL), body mass index (BMI), length of hospital stay, gender and high BP, diabetes, heart disease, smoking and other factors affect the recurrence rate of stroke as they all affect the brain, although they are all statistically different (P < .05). The recurrence of stroke requires more attention in the treatment of stroke.


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