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临床试验/NCT06951061
NCT06951061进行中(未招募)不适用

Reproductive Outcomes in Children Born Through Assisted Reproduction (ART): Focus on Intracytoplasmic Sperm Injection (ICSI) With Surgically Retrieved Sperm.

Karolinska Institutet1 个研究点 分布在 1 个国家目标入组 200,000 人开始时间: 2007年1月1日最近更新:

试验速览

阶段
不适用
状态
进行中(未招募)
入组人数
200,000
试验地点
1
主要终点
Biochemical pregnancy rate

研究概览

简要总结

This research project explores how the source of sperm affects outcomes in assisted reproductive technologies (ART), focusing on children conceived through intracytoplasmic sperm injection (ICSI) with surgically retrieved sperm (SRS). Outcomes will be compared to those from ICSI with ejaculated sperm and conventional IVF. Using national registry data from all IVF and ICSI treatments in Sweden between 2007 and 2023 (Q-IVF), the study applies artificial intelligence (AI) and machine learning (ML) to identify factors influencing success rates. The aim is to improve prediction models and support more personalized fertility treatments. Special emphasis is placed on understanding the potential risks and long-term health outcomes for children conceived using SRS, which may be associated with higher rates of genetic abnormalities. The results may help optimize care strategies for infertile couples.

详细描述

This research project aims to improve our understanding of how different sources of sperm affect outcomes in assisted reproductive technologies (ART). The focus is on children conceived through intracytoplasmic sperm injection (ICSI) using surgically retrieved sperm (SRS), compared to ICSI with ejaculated sperm and conventional in vitro fertilization (IVF).

The study has three main goals:

  1. To compare reproductive outcomes following ICSI with SRS, ICSI with ejaculated sperm, and conventional IVF.
  2. To investigate whether artificial intelligence (AI) and machine learning (ML) algorithms can predict cumulative reproductive outcomes, including results from both fresh and frozen embryo transfer cycles.
  3. To evaluate how AI/ML-based models perform in comparison to traditional statistical methods in terms of accuracy and predictive value.

Method: National Population-Based Registry Study: This includes all IVF and ICSI treatments performed in Sweden from January 1, 2007, to December 31, 2023, using data from the Swedish National Quality Registry for Assisted Reproduction (Q-IVF). AI will be used to analyze large datasets, detect patterns, and help identify key factors-such as sperm source, number of retrieved oocytes, and patient characteristics-that may influence treatment success. This approach could lead to personalized treatment plans and better predictions of successful pregnancy outcomes.

Special attention is given to outcomes in children born after ICSI with surgically retrieved sperm, as these sperm may be less mature and carry a higher risk of genetic abnormalities. The findings are expected to provide valuable insights into the reproductive and long-term health outcomes of these treatments, ultimately helping to improve care and treatment strategies for infertile couples.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Retrospective

入排标准

年龄范围
18 Years 至 45 Years(Adult)
性别
All
接受健康志愿者

入选标准

  • All IVF treatments performed in Sweden during the study period.
  • IVF treatments will be identified from the National register Q-IVF.

排除标准

  • Children born from multiple pregnancies
  • Children conceived through oocyte and sperm donation

结局指标

主要结局

Biochemical pregnancy rate

时间窗: From enrollment to the end of treatment at 3 weeks

Positive urinary pregnancy test after fresh or frozen embryo transfer per embryo transfer.

Clinical pregnancy rate

时间窗: From enrollment to the end of treatment at 8 weeks.

Presence of gestational sac at ultrasound control after fresh or frozen embryo transfer per embryo transfer.

Live birth rate

时间窗: From enrollment to the end of treatment at delivery.

Live birth per embryo transfer after fresh and frozen embryo transfer.

次要结局

  • Number of frozen embryos(From enrollment to the end of treatment at 5 days.)
  • Miscarriage rate(From enrollment to the end of treatment before 22 weeks.)

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Panagiotis Tsiartas

Associate Professor

Karolinska Institutet

研究点 (1)

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