To explore the relative factors for best ovarian response in patients undergoing assisted reproductive technology with the gonadotropin-releasing hormone antagonist protocol and to establish a nomogram prediction model of ovarian response.
A retrospective cohort analysis of the clinical data of 1,944 patients who received assisted reproductive treatment in the Center for Reproductive Medicine of Fujian Maternity and Child Health Hospital from April 1, 2018, to June 30, 2020. According to the number of oocytes obtained, there were 659 cases in the low ovarian response group (no more than five oocytes were retrieved), 920 cases in the normal ovarian response group (the number of retrieved oocytes was >5 but ≤18), and 365 cases in the high ovarian response group (>18 oocytes retrieved). Independent factors affecting ovarian responsiveness were screened by logistic regression, which were the model entry variables, and a nomogram prediction model was established based on the regression coefficients.
There were statistically significant differences in age, anti-Mullerian hormone, antral follicle count, the diagnosis of endometriosis, decreased ovarian reserve, polycystic ovary syndrome, basal follicle-stimulating hormone and basal luteinizing hormone among the three groups (P < 0.001). Multifactorial stepwise regression analysis showed that female age (0.95 [0.92–0.97],
The nomogram model was successfully developed to effectively, intuitively, and visually predict the ovary reactivity in the gonadotropin-releasing hormone antagonist protocol and provide guidance for clinical practice.