GnRH agonist versus GnRH antagonist in in vitro fertilization and embryo transfer (IVF/ET)-Reference-Cited by-同舟云学术

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GnRH agonist versus GnRH antagonist in in vitro fertilization and embryo transfer (IVF/ET)

Published:2012 Issue:1 Volume:10 Page:26
ISSN:1477-7827
Container-title:Reproductive Biology and Endocrinology
language:en
Short-container-title:Reprod Biol Endocrinol

Author:

Depalo Raffaella,Jayakrishan K,Garruti Gabriella,Totaro Ilaria,Panzarino Mariantonietta,Giorgino Francesco,Selvaggi Luigi E

Publisher

Springer Science and Business Media LLC

Subject

Developmental Biology,Endocrinology,Reproductive Medicine,Obstetrics and Gynecology

Reference29 articles.

1. Improved pregnancy outcome with gonadotropin releasing hormone agonist (GnRH-a) stimulation is due to the improvement in oocyte quantity rather than quality

2. Relationship between gonadotropin releasing hormone agonist dosage andin vitrofertilization outcome

3. Friendly IVF: the way of the future?

4. Are GnRH antagonists comparable to agonists for use in IVF?

5. An OHSS-Free Clinic by segmentation of IVF treatment

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1. Effect of LH level on HCG trigger day on clinical outcomes in patients with diminished ovarian reserve undergoing GnRH-antagonist protocol;Reproductive Biology and Endocrinology;2024-08-22

2. Acupuncture combined with gonadotropin-releasing hormone agonists improves endometrial receptivity and pregnancy outcome in patients with recurrent implantation failure of in vitro fertilization-embryo transfer;Journal of Assisted Reproduction and Genetics;2024-06-07

3. Lower Pregnancy and Live Birth Rates with Vaginal Endometrin Plus Intramuscular Progesterone Every Third Day Versus Intramuscular Progesterone Alone in Programmed Frozen Embryo Transfers: A Retrospective Case-control Study;Reproductive Sciences;2024-06-04

4. Gonadotropin-Releasing Hormone (GnRH) Agonist Protocol Improves Pregnancy Outcomes During In Vitro Fertilization (IVF) and Intracytoplasmic Sperm Injection (ICSI) Treatment in Young Infertile Women: A Retrospective Study;Cureus;2024-06-02

5. Using Machine Learning to Construct the Blood–Follicle Distribution Models of Various Trace Elements and Explore the Transport-Related Pathways with Multiomics Data;Environmental Science & Technology;2024-04-23

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