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A prediction model for selecting patients undergoing in vitro fertilization for elective single embryo transfer
Claudine C Hunault1, Marinus J C Eijkemans, Math H E C Pieters
1Division of Reproductive Medicine, Department of Obstetrics and Gynecology, Erasmus University Medical Center, The, Rotterdam, Netherlands.
Fertility and Sterility
|April 9, 2002
Summary
This study developed a prediction model to help select patients for single embryo transfer (SET) during in vitro fertilization (IVF). The model aims to reduce twin pregnancies while maintaining singleton pregnancy rates.
Area of Science:
- Reproductive Medicine
- In Vitro Fertilization (IVF)
- Embryo Transfer
Background:
- Optimizing embryo transfer strategies is crucial in IVF to improve success rates and minimize multiple pregnancies.
- Patient selection for single embryo transfer (SET) requires accurate predictive tools.
Purpose of the Study:
- To construct and validate a prediction model for selecting suitable candidates for elective single embryo transfer (ET).
- To identify key factors influencing ongoing and multiple pregnancy rates in first-time IVF cycles.
Main Methods:
- Retrospective cohort study involving 642 women undergoing their first IVF cycle with one or two embryo transfers.
- Database analysis to identify predictors of pregnancy outcomes.
- Multivariate analysis to assess the impact of female age, oocyte yield, embryo quality, and transfer day.
Main Results:
- Female age, oocyte yield, embryo developmental and morphology scores, and transfer day were significant predictors of ongoing pregnancy.
- Younger age and high-quality embryos increased the risk of multiple pregnancies.
- The model predicts probabilities of singleton and twin pregnancies, identifying an age threshold for improved singleton rates with SET.
Conclusions:
- The developed prediction model can aid in selecting patients for single ET, potentially reducing twin pregnancy rates.
- Application of the model may improve the safety and efficiency of IVF treatments without compromising singleton pregnancy success.