Prospective Validation of the CoDE-HF Algorithm for the Diagnosis of Acute Heart Failure

NCT05518396 | Active Not Recruiting

• 3 other identifiers: DL-2021-003MRC/CIC8/79RE/18/5/34216
• Study Type: observational
• Target: 3,808
• Locations: 1 country
• Sites: 1

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.

Conditions

Acute Heart Failure; Diagnosis

Keywords

Artificial Intelligence

Outcome Measures

Primary Outcomes (1)

• Adjudicated diagnosis of acute heart failure

  At index presentation

Secondary Outcomes (2)

• Subsequent hospitalisation with heart failure

  3 months

• All-cause death

  3 months

Interventions

CoDE-HF decision support tool DIAGNOSTIC_TEST

We will assess the diagnostic performance of the CoDE-HF decision support tool

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

All consecutive patients presenting to the Emergency Department with acute breathlessness will be included in this study

You may qualify if:

• Patients presenting to the Emergency Department with acute breathlessness

Sponsors & Collaborators

• University of Edinburgh: lead
• NHS Lothian: collaborator

Study Sites (1)

Centre for Cardiovascular Science, University of Edinburgh

Edinburgh, EH16 4SB, United Kingdom

Location

Related Publications (1)

• Lee KK, Doudesis D, Anwar M, Astengo F, Chenevier-Gobeaux C, Claessens YE, Wussler D, Kozhuharov N, Strebel I, Sabti Z, deFilippi C, Seliger S, Moe G, Fernando C, Bayes-Genis A, van Kimmenade RRJ, Pinto Y, Gaggin HK, Wiemer JC, Mockel M, Rutten JHW, van den Meiracker AH, Gargani L, Pugliese NR, Pemberton C, Ibrahim I, Gegenhuber A, Mueller T, Neumaier M, Behnes M, Akin I, Bombelli M, Grassi G, Nazerian P, Albano G, Bahrmann P, Newby DE, Japp AG, Tsanas A, Shah ASV, Richards AM, McMurray JJV, Mueller C, Januzzi JL, Mills NL; CoDE-HF investigators. Development and validation of a decision support tool for the diagnosis of acute heart failure: systematic review, meta-analysis, and modelling study. BMJ. 2022 Jun 13;377:e068424. doi: 10.1136/bmj-2021-068424.

  PMID: 35697365 BACKGROUND

MeSH Terms

Conditions

Disease

Condition Hierarchy (Ancestors)

Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 24, 2022
• First Posted: August 26, 2022
• Study Start: April 25, 2021
• Primary Completion: June 1, 2024
• Study Completion (Estimated): June 30, 2028
• Last Updated: February 3, 2026

Record last verified: 2026-01

Locations

GB (1)