Heart FailureNCT03905226
Development of a Predictive Algorithm for the Risk of Rehospitalization of Patients With Heart Failure
An observational study of Heart Failure, run by Fondation Hôpital Saint-Joseph at 1 site in France.
Trial summary
Heart failure is a chronic disease whose prevalence, due to the aging of the population, is increasing. In France, the prevalence of this pathology is 2.3% (it reaches 10% in the over 75 years) and affects nearly a million patients. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Heart Failure
- How many people
- 1,486 participants
- Where
- 1 siteFrance
- Study dates
- 12 Jan 2019to 31 Dec 2019
- 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: Patients with heart failure hospitalized in the cardiology department ath GHPSJ between january 2015 to december 2018
Who may be able to join
- Patients older than 18 years
- Patients with heart failure hospitalized in the cardiology department ath GHPSJ between january 2015 to december 2018
Who cannot join
- Patient opposing the use of his data for this research
- Patient under tutorship or curatorship
- Patient deprived of liberty
Trial locations and contacts
1 site in 1 country.
About this study
Heart failure is a chronic disease whose prevalence, due to the aging of the population, is increasing. In France, the prevalence of this pathology is 2.3% (it reaches 10% in the over 75 years) and affects nearly a million patients.
The rehospitalization of patients with heart failure affects 25% of patients within 1-3 months of hospital discharge, and 66% at 1 year while 75% of hospitalizations are preventable. These readmissions result in decreased quality of life and increased mortality; from an economic point of view, hospitalization accounts for 70% of expenses related to the management of heart failure. Avoiding rehospitalization is therefore a major public health issue. The current predictive scores remain perfectible, even though risk factors for readmission have already been the subject of numerous studies. The identification of patients at risk of rehospitalization is still an issue, especially for patients with preserved left ventricular ejection fraction. Targeting patients requiring appropriate care remains an issue.
The rise of innovative statistical techniques around Big Data in health opens new perspectives for the scientific exploitation of data available in electronic medical records, for example in the field of prediction. This study aims to explore the risk of rehospitalization in heart failure patients by analyzing routine data collected in medical records and by mobilizing artificial intelligence algorithms. A review of the literature confirms the innovative nature of such an approach: the majority of the studies identified implemented a prospective collection of data; only 20% of the studies mobilized the medical file; no French study used the new machine learning algorithms.
- Conditions
- Heart Failure
- Medical subject headings
- Heart Failure
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 |
|---|---|---|
| Heart Failure | Patients whom initiated a hospital pathway for heart failure management within the Paris Saint Joseph Hospital Group (GHPSJ) between January 1, 2015 and December 31, 2018. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of readmissions
Comparison of the number of readmissions predicted to the number actually observed with calculation of the sensitivity and specificity of the model at the validation phase.
Measured: month 1
Number of readmissions
Comparison of the number of readmissions predicted to the number actually observed with calculation of the sensitivity and specificity of the model at the validation phase.
Measured: Month 6
Number of readmissions
Comparison of the number of readmissions predicted to the number actually observed with calculation of the sensitivity and specificity of the model at the validation phase.
Measured: Year 1
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Apr 2019
- Study start12 Jan 2019
- Primary completion31 Dec 2019
- Study completion31 Dec 2019
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
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 1,486 participants (actual)
Sponsor and investigators
- Lead sponsor
- Fondation Hôpital Saint-Joseph
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Philippe ABASSADE, MD, Principal investigator, Fondation Hôpital Saint-Joseph
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03905226
- Sponsor's protocol ID
- PREDIC
- Status last verified
- Apr 2023
- First submitted
- 4 Apr 2019
- Last updated
- 27 Apr 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 27 Apr 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of a Predictive Algorithm for the Risk of Rehospitalization of Patients With Heart Failure
- ClinicalTrials.gov ID
- NCT03905226
- Acronym / sponsor ID
- PREDIC
- Conditions
- Heart Failure
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,486 participants (actual)
- Lead sponsor
- Fondation Hôpital Saint-JosephUniversity, hospital or other
- Study start
- 12 Jan 2019 (actual)
- Primary completion
- 31 Dec 2019 (actual)
- Study completion
- 31 Dec 2019 (actual)
- First posted
- 5 Apr 2019 (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 is a chronic disease whose prevalence, due to the aging of the population, is increasing. In France, the prevalence of this pathology is 2.3% (it reaches 10% in the over 75 years) and affects nearly a million patients.
The rehospitalization of patients with heart failure affects 25% of patients within 1-3 months of hospital discharge, and 66% at 1 year while 75% of hospitalizations are preventable. These readmissions result in decreased quality of life and increased mortality; from an economic point of view, hospitalization accounts for 70% of expenses related to the management of heart failure. Avoiding rehospitalization is therefore a major public health issue. The current predictive scores remain perfectible, even though risk factors for readmission have already been the subject of numerous studies. The identification of patients at risk of rehospitalization is still an issue, especially for patients with preserved left ventricular ejection fraction. Targeting patients requiring appropriate care remains an issue.
The rise of innovative statistical techniques around Big Data in health opens new perspectives for the scientific exploitation of data available in electronic medical records, for example in the field of prediction. This study aims to explore the risk of rehospitalization in heart failure patients by analyzing routine data collected in medical records and by mobilizing artificial intelligence algorithms. A review of the literature confirms the innovative nature of such an approach: the majority of the studies identified implemented a prospective collection of data; only 20% of the studies mobilized the medical file; no French study used the new machine learning algorithms.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Heart Failure | – | –Patients whom initiated a hospital pathway for heart failure management within the Paris Saint Joseph Hospital Group (GHPSJ) between January 1, 2015 and December 31, 2018. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with heart failure hospitalized in the cardiology department ath GHPSJ between january 2015 to december 2018
Key inclusion criteria (2 listed)
- Patients older than 18 years
- Patients with heart failure hospitalized in the cardiology department ath GHPSJ between january 2015 to december 2018
Key exclusion criteria (3 listed)
- Patient opposing the use of his data for this research
- Patient under tutorship or curatorship
- Patient deprived of liberty
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
Number of readmissions
Time frame: month 1
Comparison of the number of readmissions predicted to the number actually observed with calculation of the sensitivity and specificity of the model at the validation phase.
Number of readmissions
Time frame: Month 6
Comparison of the number of readmissions predicted to the number actually observed with calculation of the sensitivity and specificity of the model at the validation phase.
Number of readmissions
Time frame: Year 1
Comparison of the number of readmissions predicted to the number actually observed with calculation of the sensitivity and specificity of the model at the validation phase.
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 Apr 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.
Philippe ABASSADE, MD principal investigator
Fondation Hôpital Saint-Joseph
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, run by Fondation Hôpital Saint-Joseph 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 2 inclusion and 3 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 Apr 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 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?
Number of readmissions (time frame: month 1). The study lists 3 primary outcomes in all. 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 27 Apr 2023.