School of Nursing, University of South China, Hengyang, 421001, Hunan, China.
Department of Epidemiology and Health Statistics, XiangYa School of Public Health, Central South University, Changsha, 410008, Hunan, China.
Sci Rep. 2021 Jan 11;11(1):331. doi: 10.1038/s41598-020-79308-9.
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.
活产是辅助生殖技术（ART）患者最关心的问题。因此，在医疗生殖中心，产科医生经常需要回答以下问题：“在 ART 治疗后，我有健康婴儿的机会有多大？” 迄今为止，我们的产科医生没有参考依据来回答这个问题。我们的研究旨在通过建立 ART 患者活产预测模型来解决这个问题。
2010 年 1 月 1 日至 2017 年 5 月 1 日期间，我们对在中国湖南中南大学湘雅医院生殖医学中心接受 ART 治疗的女性进行了回顾性队列研究。每个启动周期或胚胎移植过程中至少有一个活产婴儿的分娩被定义为活产，所有其他妊娠结局均归类为无活产。通过逐步多变量逻辑回归建立活产预测模型。所有符合条件的受试者被随机分配到两组：组 1（80%的受试者）用于建立预测模型，组 2（20%的受试者）用于验证建立的预测模型。在不同的截止值下，计算每个预测模型的灵敏度、特异性、阳性预测值（PPV）和阴性预测值（NPV）。
活产预测模型包括 9 个变量。在验证组中，ROC 曲线下面积为 0.743。建立模型的灵敏度、特异性、PPV 和 NPV 在不同截止值下分别为 97.9-24.8%、7.2-96.3%、44.8-83.8%和 81.7-62.5%。
建立并验证了一种稳定、可靠、方便、满意的 ART 患者活产预测模型，该模型可为产科医生预测 ART 患者的活产率提供有用的工具。同时，这也是产科医生为不孕患者创造良好妊娠准备条件的参考。
