AUTHOR=Li Fei , Chen Ying , Niu Aiqin , He Yajing , Yan Ying 

TITLE=Nomogram Model to Predict the Probability of Ovarian Hyperstimulation Syndrome in the Treatment of Patients With Polycystic Ovary Syndrome

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2021.619059

DOI=10.3389/fendo.2021.619059

ISSN=1664-2392

ABSTRACT=[Abstract] Objective: The objective of this study was to explore and identify the risk factors of ovarian hyperstimulation syndrome (OHSS) in patients with polycystic ovary syndrome (PCOS) undergoing in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI), and to establish a nomogram model evaluate the probability of OHSS in PCOS patients.
Methods: We retrospectively analyzed clinical data from 4,351 patients with PCOS receiving IVF/ICSI in our reproductive medical center. The clinical cases were divided into a modeling group (3231 cases) and a verification group (1120 cases). The independent risk factors correlation with the occurrence of OHSS was identified by logistic regression analysis. Based on the selected independent risk factors and correlated regression coefficients, we established a nomogram model to predict the probability of OHSS in PCOS patients, and the predictive accuracy of the model was measured using the area under the receiver-operating curve (AUC).
Results: Multiple single factor logistic regression analysis showed that FSH (OR 0.901; 95% CI 0.847~0.958; P<0.001), AMH (OR 11.259; 95% CI 1.206~1.315; P<0.001), E2 value on the day of hCG injection (OR 1.122; 95% CI 1.021~1.153; P<0.001), total dosage of Gn used (OR 1.010; 95% CI 1.002~1.016; P=0.041), and follicle number on the day of hCG injection (OR 0.134; 95% CI 1.020~1.261; P=0.02) are the independent risk factors for OHSS in PCOS patients. The AUC of the modeling group is 0.827 (95% CI=0.795~0.859), and the AUC of the verification group is 0.757 (95% CI=0.733~0.782). 
Conclusion: Our new established nomogram model has proved to be a novel tool that can effectively, easily and intuitively predict the probability of OHSS in the patients with PCOS, by which clinician can set up better clinical management strategies for conducting a precise personal adjuvant therapy.