Predicting Readmissions Using Omics, Biostatistical Evaluate and Artificial Intelligence

Recruiting now

Conditions studied: Heart Failure

In brief

This study is a prospective registry that aims to predict readmissions in patients with heart failure, using -omics, machine learning, patient reported outcomes, clinical data and other high-dimensional data sources.

Key facts

Study ID

NCT05028686

Run by

Institute for Clinical Evaluative Sciences

People needed

500

Starts

2019-02-01

Expected to finish

2029-09-30

Last updated by the study team

2021-09-02

Who can join

Age: 18 and older, up to 105. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Any patient aged 18 years or older admitted to hospital or seen in the emergency department with heart failure defined clinically
• The diagnosis will be guided by the Framingham criteria for HF and/or BNP. A BNP >400 will be defined as definite heart failure and BNP 100-400 classified as possible heart failure.
• Provides informed consent

You may not qualify if…

• Patients who cannot communicate due to dementia or severe cognitive deficits
• non-Ontario residents
• nursing home residents
• those who are not discharged home but are discharged to a skilled nursing facility (long-term care or chronic institution)
• those who are unable to communicate who do not have a proxy (e.g. spouse or close family member) to facilitate communication with the patient.

Where it is running

• University Health Network — Toronto, Ontario, Canada (enrolling)

Full record on ClinicalTrials.gov

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