Abstract:Objective To explore the demographic and sociological characteristics of patients with knee osteoarthritis (KOA) based on data mining.Methods Data were extracted from the Osteoarthritis Initiative (OAI) database,and data were integrated and screened.The study included a total of 4796 patients,comprising of 1 992 males and 2 804 females.The age ranged from 45 years to 79 years with an average age of (61.2±9.2) years.Among the patients,1 390 had symptomatic knee osteoarthritis (KOA),3 284 had asymptomatic KOA,and 122 patients served as the control group.Indicators included diagnosis,gender,age,occupation,education,annual income,marriage,and health insurance status.The data were analysed using the “arsenal” library in R computer language. Results The differences in the distribution of the three groups were not statistically significant in terms of gender (P=0.383),statistically significant in terms of age (P<0.001),statistically significant in terms of occupation (P<0.001),statistically significant in terms of education (P<0.001),statistically significant differences in the distribution of annual income level (P<0.001),statistically significant differences in the distribution of health insurance (P<0.001) and statistically significant differences in the distribution of marriage (P<0.001).The demographic and sociological characteristics of patients with symptomatic KOA included:(1)older mean age,(2)higher rates of nonemployment,(3)lower educational attainment,(4)lower annual income levels,(5)higher rates of nonmarital status,(6)lower rates of having health insurance.Conclusion Patients with symptomatic KOA often have specific demographic and sociological characteristics.Diagnosis and treatment according to their demographic and social characteristics may be more beneficial to the prevention and treatment of KOA in China.
刘娜,王丙刚,魏海强,田鑫铎. 基于大样本数据探究膝骨关节炎患者人口社会学特征[J]. 实用骨科杂志, 2023, 29(4): 330-.
Liu Na,Wang Binggang,Wei Haiqiang,Tian Xinduo. Exploring the Sociodemographic Characteristics of Patients with Knee Osteoarthritis Based on a Large Sample Data Mining Approach. sygkzz, 2023, 29(4): 330-.
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