AI-Driven Model Impact on Patient Engagement in Medically Assisted Reproduction
NCT ID: NCT07087171
Last Updated: 2025-07-30
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
774 participants
OBSERVATIONAL
2025-06-11
2026-08-31
Brief Summary
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Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized healthcare, offering innovative solutions for personalized patient care. In IVF, AI-ML models hold the potential to enhance patient engagement by delivering tailored communication, reminders, and educational support, but also improved prognostication by providing personalized and accurate predictions of treatment outcomes. These capabilities enable patients to make more informed decisions and enhance their adherence to treatment protocols.This protocol outlines a prospective evaluation of an AI-ML model, specifically the Univfy PreIVF report, developed to improve patient engagement in IVF care. Recently, a retrospective, multicenter study reported improved IVF utilization rates among patients counselled using the Univfy PreIVF Report. The current study will prospectively assess the model's effectiveness in addressing individual patient needs and creating a supportive treatment environment. Specifically, this study will measure adherence to providers' recommendation of treatment protocols. By analyzing the impact of these interventions, this research aims to provide robust evidence for the integration of AI-ML technologies in reproductive medicine, paving the way for broader implementation and improved patient outcomes.
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Detailed Description
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Conditions
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Study Design
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COHORT
OTHER
Study Groups
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Conventional counselling group
A retrospective cohort of patients who underwent their new patient visit with one of the doctors participating in the study between December 2024 and June 2025 will be analyzed.
No interventions assigned to this group
AI-based counselling group
A prospective cohort of patients undergoing their NPV with one of the doctors participating in the study will receive an artificial intelligence-machine learning report with their accurate personalized probabilities of having a live birth rate together with a medical explanation by their physician
Artificial intelligence-Machine learning report with accurate personalized probabilities of having a live birth rate
Patients included in the prospective arm will receive the Univfy® PreIVF Report with their accurate personalized probabilities of having a live birth rate (Univfy®) together with a medical explanation by their physician
Interventions
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Artificial intelligence-Machine learning report with accurate personalized probabilities of having a live birth rate
Patients included in the prospective arm will receive the Univfy® PreIVF Report with their accurate personalized probabilities of having a live birth rate (Univfy®) together with a medical explanation by their physician
Eligibility Criteria
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Inclusion Criteria
* Patients willing to undergo Medically Assisted Reproduction (heterosexual couples, same-sex female couples and single females undergoing artificial insemination, IVF/ICSI or oocyte donation treatments)
Exclusion Criteria
* Patients who are not candidates for IVF/ICSI
* Patients who are menopausal or peri-menopausal
* Patients undergoing Fertility Preservation
* Same-sex couples who will undergo reception of oocytes from partner.
* Patients who decline to be counselled about their probability of having a live birth from IVF/ICSI treatment
18 Years
45 Years
ALL
No
Sponsors
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Univfy Inc.
INDUSTRY
Instituto Valenciano de Infertilidade de Lisboa
NETWORK
Responsible Party
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Locations
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IVI-RMA Lisboa
Lisbon, , Portugal
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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2412-LIS-233-AN
Identifier Type: -
Identifier Source: org_study_id
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