How cervical ultrasound settings affect AI prediction of preterm birth

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This prospective observational study examines an existing AI model that predicts spontaneous preterm birth to see if its performance varies with how cervical ultrasound images are acquired. Pregnant women in the second trimester undergoing routine scans with a transvaginal cervical assessment are enrolled. The study analyzes imaging settings and their impact on the AI model’s predictive accuracy using pregnancy outcomes. It focuses on real-world clinical practice to understand AI reliability across imaging variations.

Why it matters

Who can join: the full rules

Inclusion Criteria:

* Pregnant women aged ≥18 years
* Attending routine second-trimester scan (and scheduled transvaginal cervical assessment per local protocol/workflow)

Exclusion Criteria:

* Absence of transvaginal cervical assessment at the second-trimester scan
* Missing follow-up data on pregnancy outcome (gestational age at delivery)
* Inadequate image quality or missing required cervical ultrasound image

Where it's running

• Rigshospitalet, Copenhagen Univeristy Hospital
  Copenhagen, Denmark Recruiting

Study contacts

• Study coordinator: Emilie Pi F Sejer, MD
• Email: emilie.pi.fogtmann.sejer.01@regionh.dk
• Phone: 0045 28890690

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

• Predicting Adverse Pregnancy Outcomes in Uganda through Partnerships and Innovation

  This study tests whether everyday health data, ultrasound, and blood samples from first-time pregnant women in Uganda can help predict problems like preeclampsia, fetal growth restriction, and preterm birth.

  Recruiting at 2 sites Makerere University · Kampala and 1 other locations · NCT07844876

• Cervical stiffness test to help predict preterm birth in at-risk pregnant women

  A simple cervical stiffness test using the Pregnolia device is being studied to see if it can better identify women with threatened preterm labor who are likely to give birth soon.

  Recruiting Pregnolia AG · Prague · NCT07840235

• Prenatal education to reduce environmental exposures during pregnancy

  Aimed at pregnant people, this program tests whether a classroom-style education can help reduce exposure to harmful pollutants from seafood and nearby pollution sources.

  Recruiting at 2 sites The University of Texas Medical Branch, Galveston · Galveston, Texas and 1 other locations · NCT07758114

• How doctors and nurses decide about bed rest in pregnancy

  This study tests a plan to stop routinely restricting activity or bed rest during pregnancy to see if providers accept it, find it appropriate, and change how often they recommend it for women at risk of preterm birth.

  Recruiting at 2 sites University of Pennsylvania · Philadelphia, Pennsylvania and 1 other locations · NCT07698483

• Does AI-based cephalometric tracing match digital manual tracing for orthodontic measurements?

  This study tests whether AI-powered cephalometric analysis can produce measurements similar to traditional digital tracing in 100 patient radiographs.

  Recruiting University of Pavia · Pavia, Italy · NCT07664488

• Heart score calculator test using GPT-4o and Claude in chest pain patients

  This study tests whether two large language models can calculate HEART scores from patient notes and predict 30-day adverse heart events in adults with chest pain in the emergency department.

  Recruiting Marmara University Pendik Training and Research Hospital · Istanbul, Istanbul · NCT07626060

How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.