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| ID | Type | Description | Link |
|---|---|---|---|
| No 101112022 | Other Grant/Funding Number | Innovative Health Initiative Joint Undertaking (IHI JU) | |
| No 10088702 | Other Grant/Funding Number | UK Research and Innovation (UKRI) | |
| NL 009912 | Other Identifier | Overzicht van Medisch-wetenschappelijk Onderzoek in Nederland (OMON) |
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Despite extensive modelling, it was not possible to develop a model that had sufficient accuracy and could be readily applied in a clinical trial.
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| Name | Class |
|---|---|
| University Medical Center Groningen | OTHER |
| Maastricht University | OTHER |
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The main goal of PREDICT-CVS is to demonstrate that a personalized, AI-derived biomarker-guided medication treatment algorithm that provides advice to the treating professional is superior to prevent clinical events and improve quality of life (QoL) when compared to patients receiving standard treatment of care.
Participants will be randomized into two groups
Participants will visit the outpatient clinic at 1, 2, 3 and 9 months after being randomized.
The PREDICT-CVD is a prospective, randomized controlled, open label, multinational trial, in which patients with HF will be randomized to either the control arm or the intervention arm. The control arm is the standard of care and the intervention arm is where an AI-derived biomarker-guided treatment algorithm will be applied, to assist the treating professional in treatment decision. Assessment of the primary endpoint will be at the 9 month onsite follow-up visit, further long-term outcomes will be collected via telephone visits every 6 months until the last subject has completed the 9 month onsite follow-up.
The main objective is to demonstrate that a personalized, AI-derived biomarker-guided medication treatment algorithm that provides advice to the treating HF professional is superior to prevent clinical events and improve quality of life (QoL) when compared to patients receiving standard treatment of care.
The primary outcome of the trial is a clinical benefit, defined as a hierarchical composite of death from any cause, number of heart failure events and or a greater difference in change from baseline in the Kansas City Cardiomyopathy Questionnaire Total Symptom Score at 9 months, as assessed using a win ratio.
The expected duration for patients will be between 9 and max 24 months from the moment of enrollment. From 9 months onwards patients will be contacted by phone every 6 months and information regarding (HF) events and concomitant medication will be collected.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Standard of Care | Active Comparator | Standard treatment for HF |
|
| Intervention | Experimental | AI algorithm to assist the treating HF professional in treatment decision |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ASSIST-HF AI- algorithm | Other | AI-derived biomarker-guided treatment algorithm to assist the treating HF professional in treatment decision |
|
| Measure | Description | Time Frame |
|---|---|---|
| Clinical benefit | Hierarchical composite of death from any cause, number of heart failure events and or a greater difference in change from baseline in the Kansas City Cardiomyopathy Questionnaire Total Symptom Score, as assessed using a win ratio | 9 months |
| Measure | Description | Time Frame |
|---|---|---|
| Time to death from any cause | time to the first (re)hospitalization due to disease progression | 9 months (the number of days/months from randomization to the date of death) |
| Time to first (re)-hospitalization due to heart failure |
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Inclusion Criteria:
Provide written and dated informed consent for participation prior to trial admission,
Age ≥18 years, female or male
Diagnosis of heart failure* either before discharge of a heart failure hospital admission or in the outpatient setting,
Symptomatic, defined as NYHA class II - IV,
LVEF < 50% measured in the last 12 months (using any modality), with no occurrence of HF event(s) since that measurement) and
Those not previously treated with evidence-based therapies or sub-optimally treated with GDMT defined as; • Not treated with one of the foundational four** HF medication unless absolute contraindication or documented intolerance
Definition of heart failure according to the most recent Heart Failure Guidelines of the European Society of Cardiology
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University Medical Center Groningen | Groningen | Netherlands | ||||
| Leiden University Medical Center |
not decided at this time yet
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| ID | Term |
|---|---|
| D059039 | Standard of Care |
| ID | Term |
|---|---|
| D019984 | Quality Indicators, Health Care |
| D011787 | Quality of Health Care |
| D006298 | Health Services Administration |
| D017530 | Health Care Quality, Access, and Evaluation |
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Proof of concept trial
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Clinical endpoint committee remains blinded to allocation
| Standard of Care (Investigator Choice) | Other | Standard treatment of care for HF |
|
Time to first (re)-hospitalization due to heart failure
| 9 months (the number of days/months from randomization to the date of first (re)-hospitalization due to heart failure) |
| Time to all-cause hospitalization | Time to all-cause hospitalization | 9 months (the number of days/months from randomization to the date of all cause hospitalization). |
| Time to cardiovascular (CV) mortality | Time to cardiovascular (CV) mortality | 9 months (the number of days/months from randomization to the date of CV death) |
| Change in QoL | Change in QoL according to the KCCQ-TSS (change from baseline in KCCQ-TSS score, measured in points, with higher scores indicating better health status.) | 9 months |
| Change in NT-proBNP | Change in NT-proBNP (pg/mL) | 9 months |
| Change in clinical congestion score | Change in clinical congestion score (CCS). The higher the score the worst congestion is | 9 months |
| Change in eGFR | Change in eGFR (mL/min/1.73 m²) | 9 months |
| GDMT at 9 month | Guideline directed Medical Therapy | 9 months |
| Leiden |
| Netherlands |
| Maastricht University Medical Center | Maastricht | Netherlands |
| Erasmus Medical Center | Rotterdam | Netherlands |