Blockchain-Powered kidney app aims to cut hospital visits for dialysis patients
NCT ID NCT05240573
First seen Apr 10, 2026 · Last updated Jun 23, 2026 · Updated 11 times
Summary
This trial tested a smartphone app called Strong Kidney Initiative (SKI) that uses blockchain and AI to help people on dialysis better manage their health. The app shows real-time kidney data, gives care tips, and predicts health risks. Researchers compared it to a standard dialysis app in 181 patients to see if it could reduce emergency room visits and hospital stays. The study was terminated early, so the full results are not available.
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This is a summary of
the original study
.
Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
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Contacts and locations
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Locations
-
China Medical University Hospital
Taichung, Taiwan, 404, Taiwan
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
Active substance
SKI App (digital health intervention)
What this could lead to
If it works, this could show that a smartphone app with AI and blockchain helps dialysis patients avoid emergency visits and hospital stays.
What could go wrong
The trial was terminated early, so results are limited. The app relies on patients having a mobile device and being comfortable using it, which may not apply to everyone.
Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.