Contemporary Nursing

Objective To investigate the application value of an artificial intelligence (AI)-assisted decision support system in volume management and dry weight assessment for patients undergoing hemodialysis. Methods A total of 18 patients receiving maintenance hemodialysis in our hospital from June 2024 to December 2025 were prospectively enrolled and randomly assigned to an observation group (AI-assisted decision support system plus conventional management, n=9) and a control group (conventional management alone, n=9). All patients received continuous treatment for six months. The two groups were compared in terms of dry weight assessment accuracy, volume management-related indicators, laboratory parameters, and adverse events. Results The observation group had a higher rate of accurate dry weight assessment and a lower rate of inter-dialytic weight gain compared with the control group (P<0.05). After treatment, the observation group showed higher levels of hemoglobin and serum calcium, lower levels of serum phosphorus, serum creatinine, blood urea nitrogen, and intact parathyroid hormone, and a higher Kt/V value compared with the control group (all P<0.05). The incidence of intradialytic hypotension and muscle cramps was lower in the observation group than in the control group (P<0.05). Conclusion The AI-assisted decision support system can improve the accuracy of dry weight assessment, optimize volume management, enhance relevant laboratory parameters, and reduce the risk of adverse events in hemodialysis patients.

Artificial intelligence; Hemodialysis; Volume management; Dry weight assessment; Decision support system