International Journal of Fertility and Sterility (Oct 2023)

Joint Modeling of In Vitro Fertilization Outcomes among A Population of Iranian Infertile Couples: A Historical Cohort

  • Maryam Mohammadi,
  • Amir Kavousi,
  • Tahereh Madani,
  • Payam Amini,
  • Azadeh Ghaheri

DOI
https://doi.org/10.22074/ijfs.2023.562653.1374
Journal volume & issue
Vol. 17, no. 4
pp. 306 – 311

Abstract

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Background: Women who undergo in vitro fertilization (IVF) cycles should successfully go via multiple stages (i.e.,clinical pregnancy, no abortion under 12 weeks, no abortion under 20 weeks, and delivery) to achieve a live birth. Inthis study, data from multiple IVF cycles and its multiple stages were reanalyzed to illustrate the success factors associatedwith various stages of IVF cycles in a population of Iranian infertile women.Materials and Methods: This historical cohort study includes 3676 assisted reproductive technology (ART) cycles.Covariates take into account in this study were women’s age, type of infertility (primary, secondary), body mass index(BMI), cause of infertility, history of abortion, duration of infertility, number of oocytes, number of embryos, fertilizationrate, semen factors (Spermogram) and having polycystic ovarian syndrome (PCOS) during IVF cycles. Joint modelingwas fitted to apply informative cluster size.Results: Increasing age un women was associated with an increase in the BMI and a positive history of abortion andPCOS, and also, an increase in the number of treatment cycles, while in men was associated with the negative spermogram.With the increase in the number of treatment cycles, the result of the IVF success decreased, but with theincrease in the number of embryos, fertilization rate and also, quality and / or quantity parameters of spermogram, weencountered with an increase in the IVF success rate.Conclusion: It seems that a joint model of the number of treatment cycles and the result of IVF is a valuable statistical modelthat does not ignore the significant effect of cycle numbers, while this issue is ignored usually in the univariate models.

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