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AI and Guideline-based algorithms for optimization of heart failure treatment

AI and Guideline-based algorithms for optimization of heart failure treatment - AGILE-HF

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
DRKS
Registry ID
DRKS00031920
Enrollment
125
Registered
2023-05-30
Start date
2023-05-04
Completion date
Unknown
Last updated
2025-04-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

I50

Interventions

Group 1: All patients will receive the standard of care of at least 3 to 6 monthly scheduled cardiology visits. Follow-up clinic visits will take place at the scheduled uptitration visits (V1+n). This

Sponsors

Maastricht University Medical Centre
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: • Adults (=18 years) with a diagnosis of chronic HF according to ESC 2021 guidelines (HFrEF = LVEF <41%, HFmrEF = LVEF 41-49%), based on echocardiographic or magnetic resonance imaging (MRI) findings within the last year and considered stable before. • Patients with HF in the state of medication uptitration, defined as = 2 of medication classes recommended by ESC 2021 HF guideline or 3 with =50% of the maximum recommended dosage. • Ability and willingness to give written informed consent and to comply with the requirements of the study.

Exclusion criteria

Exclusion criteria: • Patients with HFpEF (LVEF >50%). • Uncontrolled or serious disease, or any medical or surgical condition, that may either interfere with participation in the clinical study, and/or put the subject at significant risk (according to investigator's judgment) if he/she participates in the clinical study. • An underlying known disease, or surgical, physical, or medical condition that, in the opinion of the investigator might interfere with interpretation of the clinical study results. • Treatment with other investigational products or devices within 30 days or five half-lives of the screening visit, whichever is longer. • Planned use of other investigational products or devices during the course of the study. • Any condition that according to the investigator could interfere with the conduct of the study, such as but not limited to: a. Subjects who are unable to communicate or to cooperate with the investigator. b. Unable to understand the protocol requirements, instructions and study-related restrictions, the nature, scope, and possible consequences of the study. c. Unlikely to comply with the protocol requirements, instructions, and study-related restrictions (e.g., uncooperative attitude, inability to return for follow-up visits (as parts of standard care), and improbability of completing the study). d. Have any medical or surgical condition, which in the opinion of the investigator would put the subject at increased risk from participating in the study e. Persons directly involved in the conduct of the study.

Design outcomes

Primary

MeasureTime frame
% of guideline-based medical therapy (GBMT) decisions by the algorithm [DoctorME-GB (v1.1)], which are in agreement with those made by the treating HCP.

Secondary

MeasureTime frame
• % of AI-based treatment decisions [DoctorME-AI] that are in agreement with those made by the treating HCP. • % of safe and effective decision supports by the guideline based algorithm [DoctorME-GB (v1.1)], where an increase in number of GBMT classes at any visit would have been advised compared to decisions made by treating HCP. • % of safe increases in GBMT dosage where the guideline based algorithm [DoctorME-GB (v1.1)] would have advised to do so based on currently prescribed GBMT classes at study visit.

Countries

Germany, Ireland, Netherlands, United Kingdom

Contacts

Public ContactMarlo Verket, MSPH

Universitätsklinikum der RWTH Aachen

mverket@ukaachen.de+49 241 80 38067

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026