MedTrace Logo

Serum Potassium Prediction Using Machine Learning and Single-lead ECG

NCT07493798 · Status: WITHDRAWN · Type: OBSERVATIONAL

Last updated 2026-03-25

No results posted yet for this study

Summary

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.

Conditions

Interventions

OTHER

Potassium estimation algorithm

Apply a machine learning algorithm to estimate a patient's potassium.

Sponsors & Collaborators

  • Biofourmis Inc.

    collaborator INDUSTRY

  • Brigham and Women's Hospital

    lead OTHER

Principal Investigators

  • David Levine, MD MPH MA · Associate Physician

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-03-20
Primary Completion
2021-08-01
Completion
2021-12-01

Countries

  • United States

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07493798 on ClinicalTrials.gov