Daily Treatment Monitoring for Patients Receiving Home-Based Peritoneal Dialysis and Prediction of Heart Failure...

Area of Science:

• Nephrology
• Cardiology
• Digital Health
• Medical Informatics

Background:

• Peritoneal dialysis (PD) is a key renal replacement therapy for end-stage renal disease.
• Heart failure is a frequent complication in PD patients, particularly those on home-based continuous ambulatory PD, due to challenges in fluid management.
• Lack of continuous professional monitoring in home PD settings increases risks for adverse events like heart failure.

Purpose of the Study:

• To develop innovative mobile health (mHealth) tools for enhanced home-based continuous ambulatory peritoneal dialysis (CAPD) management.
• To create a predictive model for heart failure using daily monitoring data from the mHealth system.
• To improve the quality, safety, and personalization of home PD treatments.

Main Methods:

• A 4-layer mHealth system was built using a robust technology stack (Spring Boot, Vue, WeChat Mini Program).
• Patients utilized the mHealth tool for daily PD monitoring from January 2017 to April 2023.
• Logistic regression models analyzed real-time data for heart failure prediction, with performance evaluated using sensitivity, specificity, and Youden index.

Main Results:

• Developed 'Futou Bao' WeChat Mini Program for patients and a data management platform for clinicians.
• Collected data from 6635 PD patients, with a 0.71% incidence of heart failure.
• An optimal prediction model incorporating sex, age, and diastolic blood pressure achieved 89% accuracy, 0.75 sensitivity, 0.91 specificity, and a 0.66 Youden index (AUC=0.879).

Conclusions:

• Introduced a novel paradigm for home-based PD management with daily monitoring and early heart failure risk warnings.
• The mHealth system significantly enhances the efficiency, security, and personalized care in PD.
• This approach offers substantial value in mitigating heart failure risks for PD patients.