Purpose: Many patients receiving maintenance hemodialysis experience one or multiple symptoms. Using a latent profile analysis to identify symptom profiles may provide insights for person-centered symptom management strategies.
Methods: This is a longitudinal study based on data from patients receiving maintenance hemodialysis at three hospitals in Shanghai, China. Of the 448 patients who completed the surveys at baseline (T1), 309 completed the 12-month follow-up survey (T2). Symptoms and quality of life were measured by the Chinese version of Kidney Disease Quality of Life 36 Short Form. The optimal classification of symptoms was identified using latent profile analysis.
Results: Five symptom profiles were identified: High (9.2%), Fatigue and Gastrointestinal (7.1%), Fatigue and Skin (10.7%), Skin (23.2%), and Low (49.8%). The high-symptom profile and the-fatigue-and-skin-symptom profile were associated with a lower level of physical functioning, a higher burden of kidney disease, and more negative effects of kidney disease than the low symptom profile at T1 and T2. Multivariate regression analysis showed that the high-symptom profile predicted a poorer physical functioning at T2, and the-fatigue-and-skin-symptom profile predicted a poorer physical functioning and higher burden of kidney disease at T2.
Conclusion: Patients receiving maintenance hemodialysis reported unique symptom experiences which could be classified into different profiles. Patients reporting an overall high level of symptoms or a high level of fatigue and skin symptoms were more likely to have a poorer quality of life.
Keywords: Hemodialysis; Latent profile analysis; Quality of life; Symptom profiles.
© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.