AI-Powered ECG could spot dangerous potassium shifts without blood draws
NCT ID NCT07493798
First seen Apr 09, 2026 · Last updated Jun 23, 2026 · Updated 12 times
Summary
This study planned to use a machine learning algorithm to estimate blood potassium levels from a single-lead ECG in hospitalized patients. It was designed as a retrospective analysis of existing data from a home hospital program. However, the study was withdrawn before enrolling any participants, so no results or conclusions are available.
Disclaimer
Read more
Show less
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.
Get updates
Get notified about this study
Sign up to get updates when this study changes or when new studies for HEART FAILURE are added.
Genom att skicka in godkänner du våra Användarvillkor
Contacts and locations
Show contact details
Enter your email to view the contact information for this study.
Genom att skicka in godkänner du våra Användarvillkor
Locations
-
Brigham and Women's Faulkner Hospital
Boston, Massachusetts, 02130, United States
-
Brigham and Women's Hospital
Boston, Massachusetts, 02115, United States
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.