Kidney Week

Abstract: FR-PO340

Supporting Self-Management of Kidney Health in Diabetic Patients via a Novel Digital Health Intervention: Protocol for a Prospective Interventional Study

Session Information

• Diabetic Kidney Disease: Clinical Modeling, Diagnosis, Education, and More
  October 25, 2024 | Location: Exhibit Hall, Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Diabetic Kidney Disease

• 702 Diabetic Kidney Disease: Clinical

Authors

• Wu, Jingyi, Advanced Institute of Information Technology, Peking University, Hangzhou, Zhejiang, China

Jingyi Wu, MS

• Pan, Hong'an, Advanced Institute of Information Technology, Peking University, Hangzhou, Zhejiang, China

Hong'an Pan, MS

• Li, Qing, Advanced Institute of Information Technology, Peking University, Hangzhou, Zhejiang, China

Qing Li

• Wang, Jinwei, Renal Division, Department of Medicine, Peking University First Hospital; Peking University Institute of Nephrology, Beijing, China

Jinwei Wang, PhD

• Li, Pengfei, Advanced Institute of Information Technology, Peking University, Hangzhou, China

Pengfei Li, PhD

• Zhang, Luxia, National Institute of Health Data Science, Peking University, Beijing, China

Luxia Zhang, MD, MPH

Background

Diabetes has become the leading cause of chronic kidney disease in China. Preventing and managing diabetic kidney disease (DKD) is crucial for diabetics, but it often goes undetected due to a lack of early symptoms and low awareness. Urine albumin-to-creatinine ratio (UACR) is an effective early indicator of kidney damage, and we have developed a digital intervention, the UACR home-testing kit (UTK), for self-monitoring of kidney health based on computer-vision algorithms. UTK has been validated to be highly accurate and sensitive in albuminuria screening, and can be a promising new strategy for cost-effective management of kidney health. We proposed a prospective interventional study to evaluate the efficacy of the UTK-based digital intervention in diabetics.

Methods

This study has been conducted since August, 2023 and will recruit over 2,000 diabetics from Yinzhou district, Ningbo city in China for the intervention group. The sample size is calculated based on the assumed odds ratio of 1.3 for the treatment rate of DKD for a matched case-control design. The intervention group will receive a routine UACR home-monitoring using UTK for one year at a recommended frequency by KDIGO, and will complete baseline and final questionnaires and estimated glomerular filtration rate (eGFR) examinations. The control group will be extracted from all 90,940 adult diabetics recorded in Yinzhou Regional Health Information System with repeated eGFR measurements during the study period. The primary outcome is the treatment rate of DKD, and the secondary outcome is DKD progression measured as the incidence rate of a 10% eGFR decline after one-year follow up.

Results

The study is ongoing and has enrolled 4,554 eligible diabetic patients (mean age 68.5±9.2 years, 42.4% males) for the intervention group, with a median follow-up duration of 5.8 (4.0-7.1) months. The baseline eGFR was 86.2±23.1 mL/min per 1.73m², and among 445 participants with eGFR < 60 mL/min per 1.73m², only 17 (3.8%) of them have received treatment of DKD.

Conclusion

This study will provide quantitative evidence for promising benefits of this user-friendly and cost-effective digital intervention for diabetics self-managing kidney health, which could potentially alleviate the heavy burden on healthcare systems for kidney disease in China.

Funding

• Government Support – Non-U.S.