Correlation study of discomfort symptom clusters and self-management in patients with knee osteoarthritis: a cross-sectional study

This study aimed to explore the relationship between knee discomfort symptom clusters and self-management in old patients with knee osteoarthritis(KOA), providing a basis for clinical improvement of patient symptoms and self-management. Stratified multistage random sampling was adopted to select KOA patients in Changsha and Zhangjiajie, Hunan Province, and their discomfort symptoms and self-management were investigated using the Self-assessment of Knee Discomfort Symptoms of Middle-aged and Older People Questionnaire and the Self-Management of Knee Discomfort Questionnaire for Middle-aged and Older People. Self-management of the survey included symptom management, daily life management, emotion management, and information management. Exploratory factor analysis was used to identify symptom clusters. Pearson correlation analysis and stratified multiple linear regression analysis were used to explore the relationship between discomfort symptom clusters and self-management. 651 old patients participated in the study. Mean participant self-management entry score (2.53 ± 0.67), 74.8% of patients had low self-management. Of the 21 knee discomfort symptom weights, 12 symptoms with > 80% incidence were selected to form 3 symptom clusters: “Pain-Related Self-Perceived Symptom Cluster” “Limited joint movement symptom cluster”“ Muscle-related self-perception symptom clusters”. All symptom clusters were positively correlated with self-management in KOA patients(r = 0.129–0.382, P < 0.05). BMI, pain-related self-perceived symptom cluster, limited joint movement symptom cluster and muscle-related self-perception symptom clusters significantly associated self-management (P < 0.01). Older patients with knee osteoarthritis exhibit suboptimal self-management capabilities, which are significantly associated by BMI and specific symptom clusters (pain, movement, and muscle perception). Management strategies focusing on these symptom clusters, rather than isolated symptoms, may provide a more effective pathway to improve patient self-management and clinical outcomes. Future research should continue to explore the network distribution of discomfort symptoms and understand the micro-interactions between symptoms and symptom clusters.