Heart FailureNCT06070506
Heart Failure With Improved Ejection Fraction and Deep Learning
An observational study of Heart Failure and Diagnosis, run by Yihui Kong at 1 site in China.
Trial summary
The aim of this study was to design a deep learning-based trained model to assist in HFimpEF diagnosis. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Heart Failure, Diagnosis
- How many people
- 422 participants
- Where
- 1 siteChina
- Study dates
- 1 Mar 2022to 20 May 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The participants in the study are HF patients hospitalized in the Department of Cardiology of the First Affiliated Hospital of Harbin Medical University who had no less than two echocardiograms at baseline and during the follow-up period, between January 2014 to December 2022.
Who may be able to join
- Age >18 years.
- The diagnostic criteria of HF follows the 2018 Chinese Guidelines for the Diagnosis and Treatment of Heart Failure, having symptoms of dyspnea, fatigue or decreased activity tolerance, having signs of fluid retention (such as pulmonary congestion and peripheral edema), having echocardiogram abnormalities in cardiac structure and/or function, showing elevated natriuretic peptide levels (BNP>35 ng/L or/and N-terminal pro-BNP >125 ng/L).
- Have reviewing echocardiography after discharge.
Who cannot join
- Patients with hypertrophic, restrictive, or invasive cardiomyopathy and congenital or rheumatic heart disease.
- Patients with heart transplantation during follow-up.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Deep Learning-Based Prediction Model of Heart Failure With Improved Ejection Fraction
The aim of this study was to design a deep learning-based trained model to assist in HFimpEF diagnosis.
- Conditions
- Heart Failure, Diagnosis
- Keywords
- Heart failure, Left ventricular ejection fraction, Heart failure with improved ejection fraction, Deep learning
- Medical subject headings
- Heart Failure, Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| HFrEF group | Heart failure patients with LVEF persistently ≤40%. | |
| HFimpEF group | Heart failure patients with previous LVEF ≤40% and a follow-up LVEF of more than 40%. |
What is being measured
The primary outcome is the main question the study is designed to answer.
change of left ventricular ejection fraction
left ventricular ejection fraction value in millimeters
Measured: 3 months
Secondary outcomes (2)
change of clinical predictor of EF improvement
weight in kilograms, height in meters(weight and height will be combined to report BMI in kg/m^2)
Measured: 3 months
the independent clinical predictor of HFimpEF
prealbumin in mg/L
Measured: 3 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Oct 2023
- Study start1 Mar 2022
- Primary completion31 Dec 2022
- Study completion20 May 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Heart FailureStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Retrospective
- Enrolment
- 422 participants (actual)
Sponsor and investigators
- Lead sponsor
- Yihui Kong
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Yihui Kong, First Affiliated Hospital of Harbin Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06070506
- Sponsor's protocol ID
- 2020020668
- Status last verified
- Oct 2023
- First submitted
- 30 Aug 2023
- Last updated
- 11 Oct 2023
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 11 Oct 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Deep Learning-Based Prediction Model of Heart Failure With Improved Ejection Fraction
- ClinicalTrials.gov ID
- NCT06070506
- Acronym / sponsor ID
- 2020020668
- Conditions
- Heart Failure, Diagnosis
- Keywords
- Heart failure, Left ventricular ejection fraction, Heart failure with improved ejection fraction, Deep learning
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 422 participants (actual)
- Lead sponsor
- Yihui KongUniversity, hospital or other
- Study start
- 1 Mar 2022 (actual)
- Primary completion
- 31 Dec 2022 (actual)
- Study completion
- 20 May 2023 (actual)
- First posted
- 6 Oct 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The aim of this study was to design a deep learning-based trained model to assist in HFimpEF diagnosis.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| HFrEF group | – | –Heart failure patients with LVEF persistently ≤40%. |
| HFimpEF group | – | –Heart failure patients with previous LVEF ≤40% and a follow-up LVEF of more than 40%. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The participants in the study are HF patients hospitalized in the Department of Cardiology of the First Affiliated Hospital of Harbin Medical University who had no less than two echocardiograms at baseline and during the follow-up period, between January 2014 to December 2022.
Key inclusion criteria (3 listed)
- Age >18 years.
- The diagnostic criteria of HF follows the 2018 Chinese Guidelines for the Diagnosis and Treatment of Heart Failure, having symptoms of dyspnea, fatigue or decreased activity tolerance, having signs of fluid retention (such as pulmonary congestion and peripheral edema), having echocardiogram abnormalities in cardiac structure and/or function, showing elevated natriuretic peptide levels (BNP>35 ng/L or/and N-terminal pro-BNP >125 ng/L).
- Have reviewing echocardiography after discharge.
Key exclusion criteria (2 listed)
- Patients with hypertrophic, restrictive, or invasive cardiomyopathy and congenital or rheumatic heart disease.
- Patients with heart transplantation during follow-up.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
change of left ventricular ejection fraction
Time frame: 3 months
left ventricular ejection fraction value in millimeters
2 secondary outcomes
change of clinical predictor of EF improvement
Time frame: 3 months
the independent clinical predictor of HFimpEF
Time frame: 3 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 11 Oct 2023.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Heart Failure and Diagnosis, run by Yihui Kong at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 11 Oct 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
change of left ventricular ejection fraction (time frame: 3 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 11 Oct 2023.