Abstract: Objective  To explore the symptom clusters and their sentinel symptoms in patients undergoing maintenance hemodialysis, providing a reference for the early detection and identification of symptoms, the simplification of symptom cluster management, and the precise management of symptom clusters. Method  The convenience sampling method was adopted to select maintenance hemodialysis patients from the Blood Purification Center of the People's Hospital of Ningxia Hui Autonomous Region. Symptom clusters were extracted by using principal component analysis combined with the orthogonal rotation method of maximum variance. The Apriori algorithm was employed to determine the sentinel symptoms. Result  During dialysis, five symptom clusters were extracted from the patients: the uremic symptom cluster, the emotional symptom cluster, the electrolyte disorder symptom cluster, the gastrointestinal discomfort symptom cluster, and the sleep disorder symptom cluster. Their Cronbach's α coefficients were 0.853, 0.923, 0.850, 0.797, and 0.898, respectively. The results of Apriori correlation analysis and determination showed that skin dryness, anxiety, difficulty in keeping the legs still, constipation, and difficulty in falling asleep were the sentinel symptoms of the above-mentioned symptom clusters in sequence. Conclusion During the dialysis period, maintenance hemodialysis patients experience a variety of symptoms, and each symptom cluster contains sentinel symptoms. In light of this, it is recommended that medical staff in the future consider sentinel symptoms as the starting point for the assessment and management of symptom clusters. Subsequently, corresponding intervention measures can be implemented to enhance the efficiency of symptom management, improve the compliance of MHD patients, thereby reducing patients' disease burden and enhancing their quality of life.

Key words: Maintenance hemodialysis, Symptom cluster, Sentinel symptom, Nursing