To investigate how uterine size and volume are associated with live birth rate in patients undergoing assisted reproduction technology. This prospective cohort study was conducted at the Reproductive Medicine Centre from January 2010 to May 2017. Multivariate binary logistic regression was used to evaluate the relations between uterine size, total volume, and live birth outcomes, after they were adjusted for the main influencing factors. A total of 7320 women of clinical pregnancy were enrolled. Compared with uterine lengths of 50 to 59 mm (referent), women with uterine lengths ≥60 mm had a lower live birth rate (RR = 1.541). Compared with uterine widths of ≥50 mm (referent), women with uterine widths <30 mm had a lower live birth rate (RR = 1.430). Compared with uterine anteroposterior diameters of <30 mm (referent), women with uterine anteroposterior diameters ≥50 mm had a lower live birth rate (RR = 1.636). Compared with uterine volumes of 30 to 49 mL (referent), women with volumes <30 mL and ≥70 mL had lower live birth rates (RR = 1.368 and 1.742, respectively). Our findings indicate that uterine sizes and volumes that were too large or too small reduced the live birth rate.

Live birth is the most important concern for assisted reproductive technology (ART) patients. Therefore, in the medical reproductive centre, obstetricians often need to answer the following question: “What are the chances that I will have a healthy baby after ART treatment?” To date, our obstetricians have no reference on which to base the answer to this question. Our research aimed to solve this problem by establishing prediction models of live birth for ART patients. Between January 1, 2010, and May 1, 2017, we conducted a retrospective cohort study of women undergoing ART treatment at the Reproductive Medicine Centre, Xiangya Hospital of Central South University, Hunan, China. The birth of at least one live-born baby per initiated cycle or embryo transfer procedure was defined as a live birth, and all other pregnancy outcomes were classified as no live birth. A live birth prediction model was established by stepwise multivariate logistic regression. All eligible subjects were randomly allocated to two groups: group 1 (80% of subjects) for the establishment of the prediction models and group 2 (20% of subjects) for the validation of the established prediction models. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each prediction model at different cut-off values were calculated. The prediction model of live birth included nine variables. The area under the ROC curve was 0.743 in the validation group. The sensitivity, specificity, PPV, and NPV of the established model ranged from 97.9–24.8%, 7.2–96.3%, 44.8–83.8% and 81.7–62.5%, respectively, at different cut-off values. A stable, reliable, convenient, and satisfactory prediction model for live birth by ART patients was established and validated, and this model could be a useful tool for obstetricians to predict the live rate of ART patients. Meanwhile, it is also a reference for obstetricians to create good conditions for infertility patients in preparation for pregnancy.