Risk Factors and Methods for Predicting Ovarian Hyperstimulation Syndrome (OHSS) in the in vitro Fertilization.

Ovarian hyperstimulation syndrome (OHSS) is the most severe and life-threatening complication of assisted reproductive technologies (ART). OHSS is based on an excessive ovarian response to ovarian stimulation; however, the pathogenesis has not been fully understood yet. The most serious complications of OHSS are thromboembolic complications and ovarian torsion. The current study describes the risk factors for the development of ovarian hyperstimulation syndrome and proposes a method for specific prediction of this syndrome. This study was designed to investigate 671 therapeutic cycles in the IVF program during 2009-2018. All patients were divided into two groups. Group one (n=56) included women who developed OHSS during the IVF procedure. Group two (n=615) consisted of women who did not have this complication during the IVF procedure. All the observation and examination outcomes were entered into a specially developed questionnaire, and then into a Microsoft Excel spreadsheet. The data were processed by variable statistics using Statistica 10.0. Analyzing of the recorded data revealed that the rate of OHSS was higher in the group of younger women, aged 30.76±3.67 years, in comparison with those aged 32.78±4.40 years in the group of patients without OHSS (p<0.05). The analysis of the initial phase of the reproductive system has confirmed that the group of patients with OHSS had a higher level of prolactin, 462.84±191.56 mIU/L in comparison with 363.43±187.84 mIU/L, which corresponded to the group of women without OHSS (p<0.05). In our results, 7.15±1.04% of cases with OHSS had obesity, while of the patients from the group without OHSS suffered from it (p<0.05). OHSS is the most severe iatrogenic complication of ART, therefore it is extremely important to consider its risk factors and take timely preventive measures. This study has established a high relationship between the studied risk factors and ovarian hyperstimulation syndrome and proposed a model for predicting this syndrome.