A risk Nomogram model for delayed ovarian hyperstimulation syndrome in patients undergoing ovarian stimulation
HUANG Jingya
Abstract：Objective:To construct a Nomogram model for predicting the risk of delayed ovarian hyperstimulation syndrome(OHSS)in patients undergoing ovarian stimulation.Methods:A total of 1 030 patients receiving ovarian stimulation admitted to Nanchang Reproductive Hospital from June 2021 to June 2023 were retrospectively selected as the study objects,and were divided into a modeling group(721 cases)and a validation group(309 cases)according to a 7:3 allocation ratio.The modeling group was divided into normal group and syndrome group according to whether patients developed delayed OHSS.Clinical baseline data of patients in the model group were collected before treatment,and univariate analysis was performed to determine the related factors affecting the development of delayed OHSS in patients receiving ovarian stimulation.Binary Logistic regression analysis was performed on related factors to screen independent risk factors,and a Nomogram model was established based on the independent risk factors,and the verification and prediction value analysis of the Nomogram model was completed through data collection of the verification group.Results:The causes of infertility,the regimen of ovarian stimulation,the expression level of E2 on the day of HCG injection and the number of follicles＞12 mm on the day of HCG injection were all related factors affecting the occurrence of delayed OHSS in patients receiving ovarian stimulation(all P＜0.05).A Nomogram prediction model was constructed based on independent influencing factors,and verified by receiver operating characteristic curve(ROC),the AUC of the modeling suite was 0.980,and that of the verification group was 0.980.The calibration curves in both the training set and the verification set showed a good fit.Further decision curve(DCA)analysis showed that when the threshold probability of the training set and the verification set was 0.11％～99.99％,the prediction model with this column graph had a higher net benefit.Conclusion:To construct a Nomogram prediction model based on infertility causes,ovarian stimulation regimen,E2 expression level on HCG injection day and follicle number＞12 mm on HCG injection day,it is helpful to improve the identification and screening ability of late-onset OHSS,so as to facilitate the presetting,formulation and implementation of targeted nursing programs.
Keywords：infertilityovarian stimulationdelayed ovarian hyperstimulation syndromeprediction modelNomograph
Publication Date：2024-06-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 2179-2183 )