Abstract
Objective
Ovarian responsiveness to ovulation induction agents is essential for a successful clinical outcome in assisted reproductive technology (ART) cycles. We aimed to evaluate the accuracy of multinominal logistic models for the prediction of ovarian reserve and pregnancy in women undergoing ART cycles.
Patients and methods
1,970 patients who underwent ovarian stimulation for ART programs were evaluated. Patients were designated to ovarian response with body mass index (BMI) and age.
Results
When evaluating the factors affecting the egg quantity in poor responder and high responder patient groups according to the BMI, we observed that there was a lower probability of extracting less than five eggs in patients with a BMI of over 30 kg/m2. The BMI was not an influential parameter for the amount of eggs obtained when compairing norm responder and high responder patient groups. Otherwise, obesity does not constitute a risk factor for positive pregnancy. Being 36–40 years of age is an important risk factor in foreseeing pregnancy.
Conclusion
Predicting and managing the variability between patients is a significant clinical challenge in stimulation protocols. Research into predictive factors and the construction of multivariate models are the first steps towards evidence-based individualized treatment. The current practice of individualized treatment is based only on clinical experience and has poor reproducibility.
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Kilic, S., Yilmaz, N., Zülfikaroglu, E. et al. Obesity alters retrieved oocyte count and clinical pregnancy rates in high and poor responder women after in vitro fertilization. Arch Gynecol Obstet 282, 89–96 (2010). https://doi.org/10.1007/s00404-010-1359-7
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DOI: https://doi.org/10.1007/s00404-010-1359-7