Analysis of relative factors and prediction model for optimal ovarian response in patients with follicular phase long-acting long protocol
10.3760/cma.j.cn101441-20210310-00119
- VernacularTitle:卵泡期长效长方案促排卵患者获得最佳卵巢反应的相关因素分析及预测模型建立
- Author:
Wenwen JIANG
1
;
Xiuhua LIAO
;
Xiaojing CHEN
;
Suqin ZHU
;
Rongshan LI
;
Huale ZHANG
;
Beihong ZHENG
Author Information
1. 福建省妇幼保健院/福建医科大学附属医院生殖医学中心，福州 350001
- Publication Type:Journal Article
- Keywords:
Follicular phase long-acting long protocol;
Ovarian response;
Nomogram prediction model
- From:
Chinese Journal of Reproduction and Contraception
2022;42(4):338-344
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the relative factors for best ovarian response in patients undergoing assisted reproductive technology with follicular phase long-acting long protocol, and to establish a Nomogram prediction model of ovarian response.Methods:This retrospective cohort study analyzed the clinical data of 1289 patients who received assisted reproductive treatment in the Center for Reproductive Medicine of Fujian Maternity and Child Health Hospital from July 1, 2018 to July 30, 2019. According to the number of oocytes retrieved, there were 164 cases in the low ovarian response group (≤5 oocytes retrieved), 891 cases in the normal ovarian response group (the number of retrieved oocytes was >5, and ≤18), and 234 cases in the high ovarian response group (>18 oocytes retrieved). Independent factors affecting ovarian reactivity were screened by logistic regression, which were the model entry variables, and a Nomogram prediction model was established based on the regression coefficients in the model.Results:There were statistically significant differences in age, anti-Müllerian hormone (AMH) level and antral follicle count (AFC) among the three groups [32.43±3.99, 31.48±3.89, 29.91±3.73; (2.53±1.90) μg/L, (3.79±2.20) μg/L, (5.94±3.12) μg/L; 10.24±3.10, 14.50±3.29, 19.81±3.44; all P<0.001]. There were no significant differences in body mass index (BMI), duration of infertility and causes of tubal infertility (all P>0.05). The initial dosage of gonadotropin (Gn) used for ovarian hyperstimulation among the three groups was statistically different [(182.62±53.96) U, (166.79±48.20) U, (159.13±43.92) U, P<0.001], while the duration of Gn used and clinical pregnancy rate had no significant differences (all P>0.05). Multifactorial stepwise aggression analysis showed that female age [0.93(0.90-0.96), P=0.007], AFC [1.07(1.03-1.09), P=0.001], AMH [1.29(1.20-1.39), P=0.001], basal follicle-stimulating hormone [0.79(0.73-0.86), P=0.001], luteinizing hormone value [1.11(1.06-1.23), P=0.010], initial dosage of Gn used [1.00(1.00-1.01), P=0.003], total dosage of Gn usd [1.00(0.99-1.00), P=0.001] and the presence or absence of diagnosis of endometriosis [0.63(0.47-0.86), P=0.001] and polycystic ovary syndrome [0.30(0.22-0.91), P=0.030] were independent factors for the occurrence of different ovarian responses during ovarian hyperstimulation. The prediction model of ovarian reactivity was constructed based on the above factors, and the accuracy of predicting the optimal ovarian response state was 95%. The above model was verified with 306 patients' data from August 1, 2019 to October 30, 2019 in this center, and the predicted ovarian response (number of oocytes obtained) of a total of 279 patients was consistent with the actual situation, with a coincidence degree of 91.2%. The consistency index of the model was 0.71. Conclusion:We screened out the relevant factors affecting ovarian response in patients undergoing assisted reproductive technology with follicular phase long-acting long protocol, and established a Nomogram prediction model of ovarian response, which could effectively, intuitively and visually predict ovarian reactivity in hyperstimulation.
