Prediction of ovarian hyperstimulation syndrome in women undergoing in vitro fertilization: A systematic review

Alshammari, Ibtesam Fawaz and Alyahya, Maya Abdullah and AlSalem, Shumukh Okab K and Elsayed, Suha Hashim Hassan and Aljumah, Muneerah A and Hatim, Ragdah faisal al (2025) Prediction of ovarian hyperstimulation syndrome in women undergoing in vitro fertilization: A systematic review. World Journal of Advanced Research and Reviews, 27 (2). pp. 295-302. ISSN 2581-9615

Background: Ovarian hyperstimulation syndrome (OHSS) is a significant complication of controlled ovarian stimulation in assisted reproductive technologies (ART). Identifying predictors of OHSS is important to optimize patient outcomes and prevent severe complications. This systematic review aimed to discuss evidence on predictive markers of OHSS in women undergoing in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) cycles. Methods: Following the PRISMA guidelines, electronic searches conducted in PubMed, Scopus, Web of Science, and Google Scholar databases. Keywords related to OHSS prediction and IVF were used, restricted to English-language full-text articles published between 2009 and 2024. Eligible studies included original prospective, retrospective, observational, or cohort studies investigating predictors of OHSS. Twelve studies were included in the qualitative synthesis. Results: Antral follicle count (AFC), anti-Müllerian hormone (AMH) levels, serum estradiol (E2) concentrations on the day of hCG administration, number of follicles, and number of retrieved oocytes emerged as the most evaluated predictors. High AFC, elevated AMH, and increased E2 levels were associated with development of OHSS. Several studies developed predictive models, including nomograms, with good discriminatory performance (AUC 0.70–0.85). Intrafollicular melatonin concentrations and coagulation factors were also studied. Conclusion: AFC, AMH, and E2 levels are reliable predictors of OHSS risk in IVF/ICSI cycles. Integrating traditional markers with emerging predictive tools allow earlier identification of high-risk patients, and enable stimulation protocols and improved clinical outcomes.