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How does PGD impact the success rates of assisted reproductive technologies?

Answer

Guideline-Aligned (High Confidence)
Generated by iatroX. Developer: Dr Kola Tytler MBBS CertHE MBA MRCGP (General Practitioner).
Last reviewed: 22 August 2025

Preimplantation genetic diagnosis (PGD) can positively impact the success rates of assisted reproductive technologies (ART) by enabling the selection of embryos free from specific genetic defects, thereby potentially increasing implantation and live birth rates. PGD allows for the identification and transfer of genetically normal embryos, which is particularly beneficial in couples at risk of transmitting inherited genetic disorders or chromosomal abnormalities, improving the likelihood of a successful pregnancy and reducing miscarriage rates 1.

While UK guidelines on fertility treatment emphasize embryo quality assessment and recommend strategies such as single embryo transfer to optimize outcomes, they do not explicitly mandate PGD as a routine part of IVF protocols but acknowledge the importance of genetic counselling and testing in cases with known genetic risks 1.

Recent literature supports that PGD, by screening embryos for aneuploidy or specific genetic conditions, can enhance ART success by reducing implantation failure and miscarriage associated with chromosomal abnormalities (Sullivan-Pyke and Dokras, 2018). However, even euploid embryos may fail to implant due to other factors, indicating that PGD improves but does not guarantee success (Cimadomo et al., 2023).

Furthermore, PGD is particularly valuable in managing hemoglobinopathies and other monogenic disorders, allowing couples to avoid transmission of these conditions while improving ART outcomes (Mamas et al., 2022).

In summary, PGD contributes to improved ART success rates by enabling the transfer of genetically normal embryos, especially in high-risk couples, but it should be integrated with comprehensive clinical assessment and counselling as recommended by UK guidelines 1 and supported by recent evidence (Sullivan-Pyke and Dokras, 2018; Mamas et al., 2022; Cimadomo et al., 2023).

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