AUTHOR=Cao Yurong , Shi Hao , Ma Yue , Ma Linna , Zhai Jun 

TITLE=Effect and Relationship of Seasons on the High Risk of Ovarian Hyperstimulation Syndrome After Oocyte Retrieval in Patients With Polycystic Ovary Syndrome

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 11 - 2020

YEAR=2021

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2020.610828

DOI=10.3389/fendo.2020.610828

ISSN=1664-2392

ABSTRACT=Objective: To investigate the effect of seasons on the incidence of high risk of OHSS after IVF/ICSI in PCOS patients and establish a nomogram to predict the risk of OHSS.
Design: Single-center, retrospective cohort study
Setting: University-affiliated reproductive medicine center
Patient(s): A total of 2,030 infertile patients with PCOS underwent follicular phase long-acting long protocol IVF/ICSI in medicine center from January 2017 to December 2019.
Intervention(s): None.
Main Outcome Measure(s): Logistic regression analysis was used to analysis the related factors of high risk of OHSS and we further established nomogram to predict the risk of OHSS in infertile patients with PCOS after IVF/ICSI.
Result(s): Among seasons, the incidence of high risk of OHSS was significant difference, especially higher in summer and winter. Multivariate logistic analysis showed that gonadotropins (Gn) dosage, number of retrieved oocytes, E2 level and average size of bilateral ovaries on HCG day, infertility type, average temperature were independent risk factors for OHSS after retrieved oocytes in PCOS patients. Based on the above independent risk factors, we constructed the prediction model for the OHSS risk. In order to evaluate the efficiency of prediction model, we calculated C-index (0.849) , AUC(0.849) and internal validation C-index (0.846). Decision curve analysis (DCA) suggested the prediction model exhibited great net benefits.
Conclusion(s): The incidence of high risk of OHSS after IVF/ICSI in patients with PCOS was fluctuating with seasonal temperature changes, particularly significantly higher in extreme climates. The prediction model had favorable predictive performance and certain clinical application value.