Acute Heart Failure, Diagnosis
Conditions
Keywords
Artificial Intelligence
Brief summary
Acute heart failure is a life-threatening condition where the heart is suddenly unable to pump blood around the body. It can be challenging to diagnose because the symptoms often mimic other conditions. Previous studies have showed that delays in making the correct diagnosis result in worse outcomes. We therefore developed a decision-support tool called CoDE-HF that uses a computer algorithm to combine levels of a blood test called NT-proBNP with patient factors to calculate the probability of acute heart failure for an individual. In this project, we wish to evaluate the performance of CoDE-HF in approximately 2,000 patients attending the Emergency Department with suspected acute heart failure. We will store surplus material from their blood tests to measure NT-proBNP and link information from their electronic health records with other routinely collected medical information in regional and national databases in order to evaluate this algorithm.
Interventions
DIAGNOSTIC_TESTCoDE-HF decision support tool
We will assess the diagnostic performance of the CoDE-HF decision support tool
Sponsors
University of Edinburgh
NHS Lothian
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Patients presenting to the Emergency Department with acute breathlessness
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Adjudicated diagnosis of acute heart failure | At index presentation |
Secondary
| Measure | Time frame |
|---|---|
| Subsequent hospitalisation with heart failure | 3 months |
| All-cause death | 3 months |
Countries
United Kingdom
Outcome results
None listed