Machine-Learning Prediction of Pregnancy Outcomes After Assisted Reproductive Treatments

October 3, 2026 updated by: BetaPlus Center for Reproductive Medicine

Development and Validation of a Machine Learning Prognostic Model for Early Prediction of Pregnancy Outcomes Following Assisted Reproductive Treatment: A Retrospective and Prospective Cohort Study

The goal of this observational study is to develop and validate a machine-learning model to predict pregnancy outcomes in women with a positive pregnancy test following assisted reproductive treatment (ART), with the primary analysis focusing on in vitro fertilization (IVF) and frozen embryo transfer (FET). The study will also include an exploratory analysis of pregnancies following intrauterine insemination (IUI). The main questions addressed by the study are:

Can early blood levels of beta-human chorionic gonadotropin (beta-hCG) predict the likelihood of live birth in an IVF or FET cycle? Can early beta-hCG levels help identify pregnancies at increased risk of biochemical pregnancy or early pregnancy loss?

Participants will have clinical and treatment information, including beta-hCG measurements and pregnancy outcomes, collected from medical records or during prospective follow-up. No changes to participants' medical treatment will be made as part of the study.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

Infertility affects more than 15% of the global population, and ART are increasingly used to achieve pregnancy. The field continues to evolve rapidly with ongoing technological and clinical advances. Although these advances have improved ART, success rates continue to vary, contributing to significant psychological distress among patients due to uncertainty regarding outcomes.

The most intense stress typically occurs after the procedure, especially following a positive pregnancy test and before ultrasound confirmation. This period, which lasts at least 3-4 weeks, is characterized by considerable uncertainty, as neither patients nor healthcare providers have reliable tools to determine pregnancy viability, assess early development, or accurately predict pregnancy progression. An individualized assessment of the probability of live birth after a positive pregnancy test could provide clinically meaningful information during this period and potentially improve counseling and management of patient expectations.

Serum beta-hCG is one of the earliest measurable biomarkers following embryo implantation and has long been recognized as an important prognostic marker of early pregnancy outcome. Both the absolute concentration of beta-HCG and its subsequent rate of increase have been associated with pregnancy viability and live birth following embryo transfer.

Investigators plan to use a machine-learning system to collect and analyze retrospective clinical data. Beta-HCG values from this dataset were collected at very early stages of pregnancy (around aspiration days +14 and 16, and post-FET days 9 and 11).

Patients were advised to have blood drawn for beta-HCG measurement 14 days after oocyte aspiration or insemination, followed by a second measurement two days later. For FET, measurements were taken 9 days after blastocyst transfer (or the corresponding day for cleavage-stage embryos) and two days afterward. Due to scheduling constraints, such as weekends, actual measurements may have occurred one day earlier or later, or several days apart. The dataset included the exact dates of each blood draw, allowing precise calculation of the interval between measurements for analysis.

ART outcomes were primarily collected through direct patient reporting of events, including adverse pregnancy outcomes or live birth; for patients who did not report the outcomes, clinic staff conducted follow-up calls to ensure complete follow-up.

This study is an observational retrospective-prospective cohort study for development and validation of an AI (artificial intelligence) - based prognostic model predicting live birth after ART.

The retrospective phase will use existing clinical data from patients who underwent ART procedures at the BetaPlus Center between January 2017 and 31.12.2025.

The prospective phase will include consecutive patients undergoing ART after model development in both BetaPlus Center and Clinical University Hospital in Rijeka. These patients will be followed to assess pregnancy outcomes, enabling external validation of the model.

The study is observational in nature. No interventions, treatment modifications, or randomization will be performed as part of this research. Clinical management will follow standard operating procedures (SOP) independent of model predictions.

Study Type

Observational

Enrollment (Estimated)

2200

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • Croatia
      • Rijeka, Croatia
        • Recruiting
        • Clinical Hospital Center
        • Contact:
      • Zagreb, Croatia, 10000
        • Recruiting
        • BetaPlus Center for Reproductive Medicine
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 45 years (Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

Female

Sampling Method

Non-Probability Sample

Study Population

Participants will be women undergoing ART at the BetaPlus Center and, during the prospective validation phase, at the Clinical University Hospital in Rijeka, Croatia. The study population will include patients undergoing IVF/ICSI, FET, or IUI.

Description

Inclusion Criteria:

  • Women who underwent ART procedures (IUI, IVF/ICSI, or FET) using homologous oocytes.
  • Availability of at least one positive early serum beta-HCG measurement after aspiration, FET, or insemination (beta-HCG >10 mIU/mL).
  • Availability of the pregnancy outcome.
  • Availability of relevant patient characteristics and clinical variables required for predictive modeling.
  • For embryo-transfer cycles, availability of information on embryo developmental stage and number of embryos transferred where applicable.
  • For the prospective validation cohort, written informed consent.

Exclusion Criteria

  • Missing beta-HCG measurements critical for model input.
  • Missing key demographic or clinical variables required for predictive modeling.
  • Missing ART treatment protocol where required for the model.
  • Missing pregnancy outcomes.
  • Multiple pregnancy, hydatidiform mole, heterotopic pregnancy, and ectopic pregnancy will be excluded from the primary live-birth analysis but will be described separately and, where sample size permits, evaluated as secondary adverse pregnancy outcomes.
  • Non-consent for prospective participation in validation.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: COHORT
  • Time Perspectives: OTHER

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
ART pregnancies with positive beta-hCG

Patients with a positive serum beta-hCG measurement following ART, including IVF, FET, and IUI. Participants will be followed to assess pregnancy outcomes, including live birth, biochemical pregnancy, and early pregnancy loss.
Other: Machine-Learning Model for Prediction of Pregnancy Outcomes

A machine-learning prognostic model using early serum beta-hCG measurements and patient, embryo, and treatment characteristics to predict live birth and early adverse pregnancy outcomes following assisted reproductive treatment.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Live birth following ART
Time Frame: From positive pregnancy test until delivery.

Delivery of a live infant at ≥24 weeks of gestation.
From positive pregnancy test until delivery.

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Biochemical pregnancy following ART
Time Frame: From the first positive serum beta-hCG measurement until biochemical pregnancy resolution.

A pregnancy characterized by a positive serum beta-hCG test followed by bleeding or pregnancy loss without ultrasound confirmation of a clinical pregnancy.
From the first positive serum beta-hCG measurement until biochemical pregnancy resolution.
Early Pregnancy Loss following ART
Time Frame: From clinical pregnancy confirmation until 12 weeks of gestation.

Pregnancy loss occurring before 12 weeks of gestation, excluding biochemical pregnancy, ectopic pregnancy, heterotopic pregnancy, and hydatidiform mole.
From clinical pregnancy confirmation until 12 weeks of gestation.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

BetaPlus Center for Reproductive Medicine

Collaborators

Clinical Hospital Center Rijeka

Investigators

  • Principal Investigator: Romana Dmitrovic, BetaPlus Center for Reproductive Medicine

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2026

Primary Completion (Estimated)

December 31, 2026

Study Completion (Estimated)

September 30, 2027

Study Registration Dates

First Submitted

September 28, 2026

First Submitted That Met QC Criteria

September 28, 2026

First Posted (Actual)

October 2, 2026

Study Record Updates

Last Update Posted (Actual)

October 7, 2026

Last Update Submitted That Met QC Criteria

October 3, 2026

Last Verified

October 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • PK 1.1.12.0074
  • PK 1.1.12.0074 (Other Grant/Funding Number: HAMAG BICRO)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

De-identified individual participant data underlying the results of this study will be made available upon reasonable request. The shared dataset will include the clinical and treatment variables necessary to reproduce or further investigate the study findings, including relevant beta-hCG measurements, timing of measurements, ART treatment characteristics, and pregnancy outcomes.

Data will not include names, contact information, medical record numbers, or other directly identifying information.

IPD Sharing Time Frame

After publication and for 5 years thereafter

IPD Sharing Access Criteria

Data will be available to qualified researchers, subject to applicable ethical, legal, and institutional requirements

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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