Outcomes and Recommendations of an Indian Expert Panel for Improved Practice in Controlled Ovarian Stimulation for Assisted Reproductive Technology.
Baiju AhemmedVani SundarapandianRohit GutgutiaSathya BalasubramanyamRicha JagtapReeta BiliangadyPriti GuptaSachin JadhavRuma SatwikPavitra Raj DewdaPriti ThakorSandro C EstevesPublished in: International journal of reproductive medicine (2017)
Purpose. To improve success of in vitro fertilization (IVF), assisted reproductive technology (ART) experts addressed four questions. What is optimum oocytes number leading to highest live birth rate (LBR)? Are cohort size and embryo quality correlated? Does gonadotropin type affect oocyte yield? Should "freeze-all" policy be adopted in cycles with progesterone >1.5 ng/mL on day of human chorionic gonadotropin (hCG) administration? Methods. Electronic database search included ten studies on which panel gave opinions for improving current practice in controlled ovarian stimulation for ART. Results. Strong association existed between retrieved oocytes number (RON) and LBRs. RON impacted likelihood of ovarian hyperstimulation syndrome (OHSS). Embryo euploidy decreased with age, not with cohort size. Progesterone > 1.5 ng/dL did not impair cycle outcomes in patients with high cohorts and showed disparate results on day of hCG administration. Conclusions. Ovarian stimulation should be designed to retrieve 10-15 oocytes/treatment. Accurate dosage, gonadotropin type, should be selected as per prediction markers of ovarian response. Gonadotropin-releasing hormone (GnRH) antagonist based protocols are advised to avoid OHSS. Cumulative pregnancy rate was most relevant pregnancy endpoint in ART. Cycles with serum progesterone ≥1.5 ng/dL on day of hCG administration should not adopt "freeze-all" policy. Further research is needed due to lack of data availability on progesterone threshold or index.
Keyphrases
- pregnancy outcomes
- healthcare
- public health
- hiv infected
- mental health
- estrogen receptor
- endothelial cells
- preterm birth
- pregnant women
- antiretroviral therapy
- quality improvement
- clinical practice
- type diabetes
- emergency department
- metabolic syndrome
- deep learning
- electronic health record
- machine learning
- artificial intelligence
- induced pluripotent stem cells
- adverse drug
- glycemic control