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Information Journal Paper

Title

PREDICTION MODELS IN IVF

Author(s)

VAN DER VEEN F.

Pages

  22-23

Keywords

Not Registered.

Abstract

 Initially, in vitro fertilization (IVF) was solely performed in couples with bilateral tubal occlusion. In 1992 intracytoplasmic sperm injection (ICSI) was discovered and initiated in couples with severe male subfertilty. Later on IVF/ICSI was also applied in couples who did not suffer from sterility, such as couples with cervical hostility, failed ovulation induction, endometriosis, unilateral tubal pathology or even unexplained subfertility. The major difference between the original indication and the indications for which IVF is conducted nowadays is that the couples with bilateral tubal pathology or severe male subfertility are sterile and have a (near) zero chance of natural conception and completely depend on IVF/ICSI for a pregnancy, while the other couples are subfertile: they do have chances of natural conception, which may or may not be better than with IVF.Despite the lack of evidence that IVF is effective in subfertile couples, IVF is often considered as a last resort for all couples regardless of the etiology of their subfertility.Contrary to the perception of many, IVF does not guarantee success; almost 50% of couples that start IVF will remain childless, even if they undergo multiple IVF cycles. Subfertile couples should therefore be well informed about the chances of success with IVF before starting their first or before continuing with a new IVF cycle.Based on a couple’s specific probability, one should decide whether the chances of success with IVF outweigh the burden, risks and costs of the treatment.To do so, prediction models have been developed. Most existing models are of limited use for several reasons.They were developed before current clinical and laboratory protocols were established. They do not include the transfer of frozen-thawed embryos. They calculate pregnancy chances only for the first IVF cycle or after one failed IVF.We developed a model that would calculate pregnancy chances during the complete IVF procedure, after failed cycles, and that included pregnancies after fresh and frozen-thawed embryo transfer which performed well after internal and external, temporal validation.If couples start or continue with IVF, the aim should be to achieve optimal pregnancy chances with a low risk multiple pregnancies. The optimal embryo transfer strategy would be a ‘‘individualized embryo transfer strategy’’ that takes the woman’s prognostic profile and embryo characteristics into account; a prediction model that is able to select which and how many embryo (s) should be transferred to obtain optimal ongoing pregnancy rates with low multiple pregnancy rates. To develop such a model, we first constructed a model that was able to rank embryos on day 3 after oocyte retrieval based on their ongoing implantation potential. We then developed an embryo transfer model that consisted of two variables: one variable being the sum of all coefficients of the IVF model and the second variable being the sum of all coefficients of the embryo implantation model. These models will be presented.With help of these prediction models a more uniform treatment strategy is possible, and also a more ‘patient tailored’ treatment.

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    APA: Copy

    VAN DER VEEN, F.. (2012). PREDICTION MODELS IN IVF. INTERNATIONAL JOURNAL OF FERTILITY AND STERILITY, 6(SUPPLEMENT 1), 22-23. SID. https://sid.ir/paper/305056/en

    Vancouver: Copy

    VAN DER VEEN F.. PREDICTION MODELS IN IVF. INTERNATIONAL JOURNAL OF FERTILITY AND STERILITY[Internet]. 2012;6(SUPPLEMENT 1):22-23. Available from: https://sid.ir/paper/305056/en

    IEEE: Copy

    F. VAN DER VEEN, “PREDICTION MODELS IN IVF,” INTERNATIONAL JOURNAL OF FERTILITY AND STERILITY, vol. 6, no. SUPPLEMENT 1, pp. 22–23, 2012, [Online]. Available: https://sid.ir/paper/305056/en

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    مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
    مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
    مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
    مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
    مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
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