Trials / Withdrawn
WithdrawnNCT07493798
Serum Potassium Prediction Using Machine Learning and Single-lead ECG
- Status
- Withdrawn
- Phase
- —
- Study type
- Observational
- Enrollment
- 0 (actual)
- Sponsor
- Brigham and Women's Hospital · Academic / Other
- Sex
- All
- Age
- 18 Years
- Healthy volunteers
- Not accepted
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
- Infection
- Heart Failure
- Chronic Obstructive Pulmonary Disease
- Asthma
- Gout Flare
- Chronic Kidney Diseases
- Hypertensive Urgency
- Atrial Fibrillation Rapid
- Anticoagulants; Increased
Interventions
| Type | Name | Description |
|---|---|---|
| OTHER | Potassium estimation algorithm | Apply a machine learning algorithm to estimate a patient's potassium. |
Timeline
- Start date
- 2021-03-20
- Primary completion
- 2021-08-01
- Completion
- 2021-12-01
- First posted
- 2026-03-25
- Last updated
- 2026-03-25
Locations
2 sites across 1 country: United States
Source: ClinicalTrials.gov record NCT07493798. Inclusion in this directory is not an endorsement.