NCT05381376

Multicentre Prospective Clinical Database for the Construction of Predictive Models on Risk of Intrauterine Adhesion

Status unknown Last updated 31 October 2022

What this trial tests

trial testing Hysteroscopy in Database for Intrauterine Adhesion in 2,200 participants. Status unknown.

Timeline

20 January 2018

Primary endpoint
20 December 2023

20 April 2024

Quick facts

Lead sponsor	Hua Duan
Status	Status unknown
Study type	OBSERVATIONAL
Enrollment	2,200
Start date	20 January 2018
Primary completion	20 December 2023
Estimated completion	20 April 2024
Sites	2 locations across China

Drugs / interventions tested

• Hysteroscopy
• Ultrasonography

Conditions studied

• Database for Intrauterine Adhesion — all drugs for Database for Intrauterine Adhesion →
• Risk Factors for Intrauterine Adhesion — all drugs for Risk Factors for Intrauterine Adhesion →
• Risk Stratification and Prognostic Assessment — all drugs for Risk Stratification and Prognostic Assessment →
• Intrauterine Adhesion — all drugs for Intrauterine Adhesion →

Sponsor

Hua Duan — full company profile →

Who can join

Adults 20 to 45, female only, with Database for Intrauterine Adhesion or Risk Factors for Intrauterine Adhesion. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

1\. To establish a follow-up database for uterine adhesions and a library of biological specimens for Intrauterine Adhesion. 2. using epidemiological surveys and biological analyses to screen risk factors for the development and prognosis of Intrauterine Adhesion. 3. Predictive models based on clinical and biochemical indicators, specimen testing and hysteroscopic images are also combined with statistical analysis and machine learning algorithms to enable patients' risk stratification and prognostic assessment.

Publications & conference data

4 peer-reviewed publications reference this trial (live from Europe PMC):

1. An XGBoost predictive model of ongoing pregnancy in patients following hysteroscopic adhesiolysis.
   Li Y, Duan H, Wang S. · · 2023 · cited 9× · PMID 37037757 · DOI 10.1016/j.rbmo.2023.01.019
2. Artificial intelligence-driven prognostic system for conception prediction and management in intrauterine adhesions following hysteroscopic adhesiolysis: a diagnostic study using hysteroscopic images.
   Li B, Chen H, Duan H. · · 2024 · cited 6× · PMID 38638324 · DOI 10.3389/fbioe.2024.1327207
3. Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study.
   Li B, Chen H, Duan H. · · 2025 · cited 1× · PMID 40098308 · DOI 10.1080/07853890.2025.2478473
4. A XGBoost predictive model of reproductive outcomes in patients following hysteroscopic adhesiolysis
   Li Y, Duan H, Wang S. · · 2023 · DOI 10.21203/rs.3.rs-2388576/v1