Treatment algorithms for high responders: What we can learn from randomized controlled trials, real-world data and
Panagiotis Drakopoulos1, Yakoub Khalaf2, Sandro C Esteves3
1Centre for Reproductive Medicine, Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel, Brussels, Belgium; Department of Obstetrics and Gynaecology, University of Alexandria, Alexandria, 21526, Egypt.
Best Practice & Research. Clinical Obstetrics & Gynaecology
|January 16, 2023
Summary
Managing high ovarian response during fertility treatment is crucial. Identifying at-risk patients and tailoring stimulation protocols can significantly reduce the risk of ovarian hyper-stimulation syndrome (OHSS).
Area of Science:
- Reproductive Endocrinology
- Infertility Treatment
- Ovarian Stimulation
Background:
- High ovarian response, defined by numerous follicles or oocytes, increases OHSS risk.
- Predictive markers include AMH and AFC, particularly in PCOS patients.
- OHSS affects up to 30% of high responders.
Purpose of the Study:
- To provide a framework for identifying and managing high responders.
- To outline strategies for reducing OHSS risk in these patients.
- To address the need for defined management protocols for predicted and unexpected high responses.
Main Methods:
- Review of current definitions and diagnostic criteria for high ovarian response.
- Analysis of predictive indices for high responders, including AMH and AFC.
- Discussion of management strategies including individualized gonadotropin dosing, monitoring, and transfer protocols.
Main Results:
- High ovarian response is characterized by >18-20 follicles or oocytes retrieved.
- Predictive markers like AMH >3.4 ng/mL and AFC >24 suggest high response in PCOS.
- Individualized management can significantly reduce the risk of OHSS.
Conclusions:
- Early identification and tailored management are key to mitigating OHSS risk in high responders.
- Optimizing stimulation protocols, monitoring, and transfer strategies are essential.
- Further research is needed for definitive management of predicted and unexpected high responders.
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