Serum Potassium Prediction Using Machine Learning and Single-lead ECG

Withdrawn before enrolling

Conditions studied: Infection, Heart Failure, Chronic Obstructive Pulmonary Disease, Asthma, Gout Flare, Chronic Kidney Diseases, Hypertensive Urgency, Atrial Fibrillation Rapid, Anticoagulants; Increased

In brief

This is a retrospective study drawing on data from the Brigham and Women's Hospital Home Hospital Program's Database. Sociodemographic and clinical data from a training cohort were used to train a machine learning algorithm to predict blood potassium throughout a patient's admission. This algorithm was then validated in a validation cohort.

Key facts

Study ID
NCT07493798
Run by
Brigham and Women's Hospital
People needed
0
Starts
2021-03-20
Expected to finish
2021-12-01
Last updated by the study team
2026-03-25

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

Where it is running

Full record on ClinicalTrials.gov

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