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With infertility rising globally, more infants are conceived via in vitro fertilization-embryo transfer (IVF-ET). However, multiple pregnancies have emerged as a significant complication in assisted reproduction. Clinicians often face a dilemma between maximizing pregnancy rates and ensuring maternal-fetal safety. Historically, transferring two or more embryos was common practice to boost success. Today, the medical community increasingly advocates for Single Embryo Transfer IVF to mitigate these risks. While double embryo transfer (DET) may offer a higher per-cycle clinical pregnancy rate, it significantly increases the likelihood of twins and triplets. These multiple gestations carry higher risks of preterm birth, low birth weight, and preeclampsia.
The primary barrier to adopting SET is the perceived lower pregnancy rate compared to DET. Many patients and clinicians hesitate to choose a single embryo because they fear a failed cycle. Consequently, researchers are developing new tools to enhance embryo selection. Advanced technologies now help identify the embryo with the highest developmental potential. For instance, the integration of time-lapse imaging with artificial intelligence provides an objective way to evaluate morphological changes. These AI models analyze kinetic data that the human eye might miss. Furthermore, molecular biology techniques like non-invasive preimplantation genetic testing (niPGT) are refining how we assess chromosomal health. These advancements help bridge the success gap between SET and DET.
Future fertility care relies on standardizing these technological breakthroughs. Standardized clinical practices and multicenter validation will eventually optimize SET success rates. Currently, multi-omics-based biomarker screening offers another layer of precision by identifying viable embryos through their metabolic signatures. Although transformative breakthroughs are still evolving, the ongoing refinement of these tools is promising. Implementing Single Embryo Transfer IVF as the default strategy will eventually address the multiple pregnancy challenge at its source. This shift ensures that the goal of IVF remains a healthy singleton birth rather than just a positive pregnancy test.
SET is preferred because it significantly reduces the risk of multiple pregnancies. This approach minimizes maternal complications like gestational diabetes and neonatal issues like premature delivery, leading to healthier outcomes for both mother and child.
Artificial intelligence analyzes time-lapse images of developing embryos to rank them by implantation potential. By providing an objective and data-driven assessment, AI helps embryologists select the single best embryo, which increases the success rate of SET cycles.
Yes. While a single DET cycle might have a slightly higher pregnancy rate than a single SET cycle, the cumulative success rate over two SET cycles is often equal to or higher than one DET cycle, with far fewer medical risks.
Disclaimer: This content is for informational and educational purposes only and does not constitute medical advice. It is not intended to be a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified healthcare provider with any questions you may have regarding a medical condition. Refer to the latest local and national guidelines for clinical practice.
References
Wu X et al. Addressing multiple pregnancies in in vitro fertilization-embryo transfer: Current status, challenges, and solutions. Int J Gynaecol Obstet. 2026 Feb 28. doi: 10.1002/ijgo.70917. PMID: 41761862.
Indian Society for Assisted Reproduction (ISAR). Consensus Guidelines on Safety and Ethical Practices in In vitro Fertilization Clinics. 2025.
NVIDIA Technical Blog. Time-Lapse AI Model Enhances IVF Embryo Selection: BELA and STORK-V Algorithms. December 2024.
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A comprehensive look at why Single Embryo Transfer (SET) is replacing double embryo transfer to minimize IVF risks and how AI technology is improving outcom...
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