Heart FailurePRECISE AINCT06478901
Precision of AI-Based Cardiac Ultrasound for LVEF in the Elderly
An observational study of Heart Failure and Heart Failure Systolic, run by Hôpital Broca APHP at 1 site in France.
Trial summary
Heart failure (HF) is common in older adults, especially those over 65. It is a leading cause of hospitalization and has high mortality rates. Diagnosing HF in elderly patients can be challenging due to atypical symptoms and multiple other health issues. Read more about this study
- Who is it for?
- Ages 75 years and older
- Conditions the study is for
- Heart Failure, Heart Failure Systolic, Elderly
- What is being tested?
- Echocardiography
- Type of treatment
- Medical device
- How many people
- 129 participants
- Where
- 1 siteFrance
- Study dates
- 14 Jan 2023to 20 Feb 2024
- How long will I take part?
- 129 Days
- 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 75 years and older
- All sexes
- No healthy volunteers
- Older adult
Study population: 75 years or more and a clinical presentation of acute heart failure
Who may be able to join
- At least 75 years and a clinical presentation of acute heart failure consistent with the criteria of the European Society of Cardiology guidelines
Who cannot join
- unstable patient
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Precision and RElevance of CardIac ultraSound Using Artificial Intelligence for Left Ventricle Ejection Fraction Assessment in the Elderly. ( PRECISE AI)
Heart failure (HF) is common in older adults, especially those over 65. It is a leading cause of hospitalization and has high mortality rates. Diagnosing HF in elderly patients can be challenging due to atypical symptoms and multiple other health issues. Echocardiography, an ultrasound of the heart, is crucial for accurate diagnosis and treatment planning.
One problem in geriatric care is the difficulty of accessing echocardiography due to high demand and limited specialized doctors. Recent advancements show that AI-assisted portable ultrasound devices can reliably measure heart function, producing results comparable to traditional methods.
Read more
This study aims to evaluate the accuracy and relevance of AI-assisted echocardiography (AutoEF-AI) in elderly patients. It also assesses whether geriatricians, even without specialized training, can capture quality images for AI analysis.
In simple terms, this study investigates if portable ultrasound devices with AI can provide precise heart function diagnostics, making it easier for older adults with heart failure to get the care they need, even without specialists.
Read the detailed description
Heart failure (HF) is a major chronic illness, particularly common in older adults. With advances in healthcare and an aging population, HF is increasingly affecting people over 65 years old. In fact, 80% of HF patients are over 65. HF is associated with high mortality rates and is the leading cause of hospitalization after age 80, and even after age 65 in some countries like France.
In older adults, HF symptoms are often atypical due to multiple other health conditions, increased frailty, and associated geriatric syndromes, making diagnosis difficult. In this context, echocardiography (an ultrasound of the heart) is essential for accurately diagnosing HF.
Evaluating the left ventricular ejection fraction (LVEF) through echocardiography is a fundamental step in diagnosing HF and deciding on treatment strategies. This evaluation helps refine the HF diagnosis, propose appropriate treatments, and monitor changes in heart function over time.
One major challenge in geriatric units and nursing homes (EHPADs) is the difficulty in accessing echocardiography due to growing demand and a limited number of specialized doctors.
Recent studies have shown that automated LVEF measurements assisted by artificial intelligence (AI) using portable ultrasound devices are reliable and produce results comparable to traditional methods. This AI-assisted automatic LVEF calculation (AutoEF-AI) could be a major advantage in geriatric departments, providing a credible alternative to conventional echocardiography for evaluating LVEF in HF patients.
The main goal of this study was to evaluate the relevance and accuracy of AutoEF-AI echocardiography in elderly patients. The secondary goal was to assess whether geriatricians without specialized training in echocardiography could capture images of sufficient quality to be analyzed by automatic LVEF algorithms with acceptable accuracy.
In simple terms, this study aims to determine if using portable ultrasound devices, assisted by artificial intelligence, can provide diagnostics as precise as traditional methods. This could make evaluating heart function more accessible and effective for older adults with heart failure, even when specialists are not available.
- Being tested
- Echocardiography
- Keywords
- Elderly, Left ventricular ejection fraction, Artificial intelligence, Echocardiography
- Medical subject headings
- Heart Failure, Heart Failure, Systolic
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
EchocardiographyDevice
Echocardiography assited by Artificial intelligence
What is being measured
The primary outcome is the main question the study is designed to answer.
evaluate the relevance and accuracy of echocardiography assisted by Artificial intelligence in elderly patients
The correlation between LVEF measurements from standard echocardiography and AutoEF-AI echocardiography was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman analysis. Weighted Kappa coefficient was calculated to determine agreement between measurements in classifying patients into different categories based on LVEF
Measured: From enrollment to the end 48 hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Jun 2024
- Study start14 Jan 2023
- Primary completion2 Feb 2024
- Study completion20 Feb 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- 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
- Cohort
- Time perspective
- Prospective
- Enrolment
- 129 participants (actual)
- Target duration
- 129 Days
Sponsor and investigators
- Lead sponsor
- Hôpital Broca APHP
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06478901
- Sponsor's protocol ID
- PRECIS-AI-2024-01
- Acronym
- PRECISE AI
- Status last verified
- Jun 2024
- First submitted
- 10 Jun 2024
- Last updated
- 27 Jun 2024
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes
Publications
Chaudhry SI, Wang Y, Gill TM, Krumholz HM. Geriatric conditions and subsequent mortality in older patients with heart failure. J Am Coll Cardiol. 2010 Jan 26;55(4):309-16. doi: 10.1016/j.jacc.2009.07.066.
PubMed 20117435
Study at a glance
From the registry record, last updated by the sponsor on 27 Jun 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Precision and RElevance of CardIac ultraSound Using Artificial Intelligence for Left Ventricle Ejection Fraction Assessment in the Elderly. ( PRECISE AI)
- ClinicalTrials.gov ID
- NCT06478901
- Acronym / sponsor ID
- PRECISE AI / PRECIS-AI-2024-01
- Keywords
- Elderly, Left ventricular ejection fraction, Artificial intelligence, Echocardiography
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 129 participants (actual)
- Lead sponsor
- Hôpital Broca APHPUniversity, hospital or other
- Study start
- 14 Jan 2023 (actual)
- Primary completion
- 2 Feb 2024 (actual)
- Study completion
- 20 Feb 2024 (actual)
- First posted
- 27 Jun 2024 (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.
Heart failure (HF) is common in older adults, especially those over 65. It is a leading cause of hospitalization and has high mortality rates. Diagnosing HF in elderly patients can be challenging due to atypical symptoms and multiple other health issues. Echocardiography, an ultrasound of the heart, is crucial for accurate diagnosis and treatment planning.
One problem in geriatric care is the difficulty of accessing echocardiography due to high demand and limited specialized doctors. Recent advancements show that AI-assisted portable ultrasound devices can reliably measure heart function, producing results comparable to traditional methods.
This study aims to evaluate the accuracy and relevance of AI-assisted echocardiography (AutoEF-AI) in elderly patients. It also assesses whether geriatricians, even without specialized training, can capture quality images for AI analysis.
In simple terms, this study investigates if portable ultrasound devices with AI can provide precise heart function diagnostics, making it easier for older adults with heart failure to get the care they need, even without specialists.
Detailed description
Heart failure (HF) is a major chronic illness, particularly common in older adults. With advances in healthcare and an aging population, HF is increasingly affecting people over 65 years old. In fact, 80% of HF patients are over 65. HF is associated with high mortality rates and is the leading cause of hospitalization after age 80, and even after age 65 in some countries like France.
In older adults, HF symptoms are often atypical due to multiple other health conditions, increased frailty, and associated geriatric syndromes, making diagnosis difficult. In this context, echocardiography (an ultrasound of the heart) is essential for accurately diagnosing HF.
Evaluating the left ventricular ejection fraction (LVEF) through echocardiography is a fundamental step in diagnosing HF and deciding on treatment strategies. This evaluation helps refine the HF diagnosis, propose appropriate treatments, and monitor changes in heart function over time.
One major challenge in geriatric units and nursing homes (EHPADs) is the difficulty in accessing echocardiography due to growing demand and a limited number of specialized doctors.
Recent studies have shown that automated LVEF measurements assisted by artificial intelligence (AI) using portable ultrasound devices are reliable and produce results comparable to traditional methods. This AI-assisted automatic LVEF calculation (AutoEF-AI) could be a major advantage in geriatric departments, providing a credible alternative to conventional echocardiography for evaluating LVEF in HF patients.
The main goal of this study was to evaluate the relevance and accuracy of AutoEF-AI echocardiography in elderly patients. The secondary goal was to assess whether geriatricians without specialized training in echocardiography could capture images of sufficient quality to be analyzed by automatic LVEF algorithms with acceptable accuracy.
In simple terms, this study aims to determine if using portable ultrasound devices, assisted by artificial intelligence, can provide diagnostics as precise as traditional methods. This could make evaluating heart function more accessible and effective for older adults with heart failure, even when specialists are not available.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 129 Days
Who may qualify
- Ages
- 75 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Older adult
- Study population
- 75 years or more and a clinical presentation of acute heart failure
Key inclusion criteria (1 listed)
- At least 75 years and a clinical presentation of acute heart failure consistent with the criteria of the European Society of Cardiology guidelines
Key exclusion criteria (1 listed)
- unstable patient
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| EchocardiographyEchocardiography assited by Artificial intelligence | Device | – |
Primary outcome
evaluate the relevance and accuracy of echocardiography assisted by Artificial intelligence in elderly patients
Time frame: From enrollment to the end 48 hours
The correlation between LVEF measurements from standard echocardiography and AutoEF-AI echocardiography was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman analysis. Weighted Kappa coefficient was calculated to determine agreement between measurements in classifying patients into different categories based on LVEF
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 27 Jun 2024.
- Results publication: PubMed 20117435Chaudhry SI, Wang Y, Gill TM, Krumholz HM. Geriatric conditions and subsequent mortality in older patients with heart failure. J Am Coll Cardiol. 2010 Jan 26;55(4):309-16. doi: 10.1016/j.jacc.2009.07.066.
- Individual participant dataSharing planned: Yes
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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 Heart Failure Systolic, run by Hôpital Broca APHP at 1 site in France.
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 1 inclusion and 1 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 27 Jun 2024. 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 France. 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?
evaluate the relevance and accuracy of echocardiography assisted by Artificial intelligence in elderly patients (time frame: From enrollment to the end 48 hours). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06478901, which also lists 1 linked publication.
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 27 Jun 2024.