ArticleJournal of medical Internet research2024
Long-Term Efficacy of an AI-Based Health Coaching Mobile App in Slowing the Progression of Nondialysis-Dependent Chronic Kidney Disease: Retrospective Cohort Study.
Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Nurse-Led Digital Intervention for Sodium Restriction in Chronic Kidney Disease: Mixed Methods Implementation Study.JMIR nursing · 2026Trial
- Measurement Properties of an Electronic Patient-Reported Outcome Measure for Patients with Non-Dialysis-Dependent CKD.Kidney360 · 2026Article
- Clinical Artificial Intelligence Agents in Nephrology: From Prediction to Action Through Workflow-Native Intelligence-A Roadmap for Workflow-Integrated Care.Journal of clinical medicine · 2026Review
- Expanding Kidney Care: How Nonphysician Health Workers Can Address the Global CKD Crisis.Kidney international reports · 2026Review
- Current and Future Applications of AI-Driven Predictive Modeling and a Proposed Framework for AI-Bioprognostics in Kidney Care.Risk management and healthcare policy · 2026Review
- Self-Management Intentions and Behaviors Among CKD Patients at Predialysis and Dialysis Stages: A Cross-Sectional Study Based on Protection Motivation Theory.Nursing research and practice · 2026Article
- Recent advancements in patented technologies for the diagnosis and treatment of chronic kidney disease.International urology and nephrology · 2025Review
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChronic kidney disease (CKD) is a significant public health concern. Therefore, practical strategies for slowing CKD progression and improving patient outcomes are imperative. There is limited evidence to substantiate the efficacy of mobile app-based nursing systems for decelerating CKD progression.
objectiveThis study aimed to evaluate the long-term efficacy of the KidneyOnline intelligent care system in slowing the progression of nondialysis-dependent CKD.
methodsIn this retrospective study, the KidneyOnline app was used for patients with CKD in China who were registered between January 2017 and April 2023. Patients were divided into 2 groups: an intervention group using the app's nurse-led, patient-oriented management system and a conventional care group that did not use the app. Patients' uploaded health data were processed via deep learning optical character recognition, and the artificial intelligence (AI) system provided personalized health care plans and interventions. Conversely, the conventional care group received suggestions from nephrologists during regular visits without AI. Monitoring extended for an average duration of 2.1 (SD 1.4) years. The study's objective is to assess the app's effectiveness in preserving kidney function. The primary outcome was the estimated glomerular filtration rate slope over the follow-up period, and secondary outcomes included changes in albumin-to-creatinine ratio (ACR) and mean arterial pressure.
resultsA total of 12,297 eligible patients were enrolled for the analysis. Among them, 808 patients were successfully matched using 1:1 propensity score matching, resulting in 404 (50%) patients in the KidneyOnline care system group and another 404 (50%) patients in the conventional care group. The estimated glomerular filtration rate slope in the KidneyOnline care group was significantly lower than that in the conventional care group (odds ratio -1.3, 95% CI -2.4 to -0.1 mL/min/1.73 m
conclusionsThe utilization of KidneyOnline, an AI-based, nurse-led, patient-centered care system, may be beneficial in slowing the progression of nondialysis-dependent CKD.
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