Risk factors for recurrent implantation failure as defined by the European Society for Human Reproduction and Embryology.

IF 6 1区 医学 Q1 OBSTETRICS & GYNECOLOGY
Can Wang, Youhui Lu, Miaoxian Ou, Lingxuan Qian, Yingying Zhang, Yuxin Yang, Lu Luo, Qiong Wang
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引用次数: 0

Abstract

Study question: What are the unrecognized risk factors for recurrent implantation failure (RIF) as defined in the ESHRE recommendation?

Summary answer: Anti-Müllerian hormone (AMH) is the strongest predictor for RIF, followed by chronic endometritis (CE), intrauterine adhesions, and BMI.

What is known already: Advanced age is a well-known risk factor for implantation failure, and the definition of RIF was stratified by age in the 2023 ESHRE recommendation. However, the literature identifies other risk factors, including CE, endometriosis, BMI, endometrial polyps, intrauterine adhesions, hydrosalpinx, uterine malformation, submucosal myoma, polycystic ovary syndrome, thyroid dysfunction, rheumatic diseases, and hyperprolactinemia, to be associated with implantation failure. In addition, our clinical experience suggests AMH and a history of previous livebirth affect RIF. It remains unclear which of these factors are the best predictors of RIF.

Study design, size, duration: A cohort study drawn from ART cycles between June 2019 and June 2022.

Participants/materials, setting, methods: Two hundred and ninety-eight RIF patients and 2056 controls (women who achieved successful embryo implantation within 1-2 transfer cycles) were identified from 15 329 ART cycles at the Reproductive Medical Center at the First Affiliated Hospital of Sun Yat-sen University. RIF was defined according to the recommendation of ESHRE 2023. Basic characteristics, reproductive history, laboratory indicators (autoantibodies and endocrine factors), ultrasound, laparoscopy, hysteroscopy, hysterosalpingography, biopsy, and immunohistochemistry results were collected from the electronic medical record system. The Random Forest procedure was applied to build a machine learning model for predicting RIF. Overall predictive accuracy was assessed by using the AUC of receiver-operator characteristic curve and calibration plots. The SHapley Additive exPlanations (SHAP) framework was used to interpret the model.

Main results and the role of chance: From 32 variables, elevated AMH level and greater number of live births were associated with lower risk of RIF, while CE, intrauterine adhesions, high FSH level, high testosterone level, advanced female age, polyps, history of recurrent pregnancy loss, history of cesarean section, polycystic ovary syndrome, and rheumatic diseases were associated with higher risk of RIF according to the established random forest model. The predictive model yielded AUCs of 0.83 (95% CI: 0.80-0.86) in training dataset and 0.78 (95% CI: 0.73-0.84) in testing dataset. The calibration curve indicated good predictive performance in both training and testing datasets. SHAP values indicated that AMH had the greatest influence on the RIF risks, whereas CE, intrauterine adhesions, and BMI were the second, third, and fourth most significant risk factors for predicting RIF, respectively.

Limitations, reasons for caution: This research was limited by its retrospective design from a single reproductive medical center. Moreover, some diseases, such as polyps, submucosal myomas, and rheumatic diseases, had been treated before ART, which indicates that these factors impact RIF even after treatment.

Wider implications of the findings: In addition to age, certain high-risk factors, such as AMH, should also be included in the considerations for RIF. Patients with a combination of these high-risk factors may require more attempts to achieve a successful pregnancy.

Study funding/competing interest(s): This work was supported by the Guangzhou Municipal Science and Technology Project under Grant (202206010003) and the National Natural Science Foundation of China under Grant (81871159). None of the authors has any conflict of interest.

Trial registration number: N/A.

欧洲人类生殖与胚胎学会定义的反复植入失败的危险因素。
研究问题:ESHRE推荐中定义的复发性植入失败(RIF)的未被识别的危险因素是什么?总结回答:抗勒氏激素(AMH)是RIF最强的预测因子,其次是慢性子宫内膜炎(CE)、宫腔粘连和BMI。已知情况:高龄是众所周知的植入失败的危险因素,在2023年ESHRE推荐中,RIF的定义按年龄分层。然而,文献发现其他危险因素,包括CE、子宫内膜异位症、BMI、子宫内膜息肉、宫内粘连、输卵管积水、子宫畸形、粘膜下肌瘤、多囊卵巢综合征、甲状腺功能障碍、风湿性疾病和高催乳素血症,都与植入失败有关。此外,我们的临床经验表明AMH和以前的活产史影响RIF。目前尚不清楚这些因素中哪一个是RIF的最佳预测因素。研究设计、规模、持续时间:一项来自2019年6月至2022年6月ART周期的队列研究。参与者/材料、环境、方法:从中山大学第一附属医院生殖医学中心的15 329个ART周期中筛选出298例RIF患者和2056例对照(1-2个移植周期内胚胎植入成功的女性)。RIF是根据ESHRE 2023的建议定义的。从电子病历系统中收集患者的基本特征、生殖史、实验室指标(自身抗体和内分泌因子)、超声、腹腔镜、宫腔镜、子宫输卵管造影、活检和免疫组织化学结果。应用随机森林方法建立预测RIF的机器学习模型。利用接收机-算子特征曲线的AUC和标定图对总体预测精度进行了评价。采用SHapley加性解释(SHAP)框架对模型进行解释。主要结果及偶发因素的作用:根据建立的随机森林模型,在32个变量中,AMH水平升高、活产数增加与RIF风险降低相关,CE、宫内粘连、高FSH水平、高睾酮水平、女性年龄偏大、息肉、反复流产史、剖宫产史、多囊卵巢综合征、风湿病与RIF风险升高相关。该预测模型在训练数据集中的auc为0.83 (95% CI: 0.80-0.86),在测试数据集中的auc为0.78 (95% CI: 0.73-0.84)。校准曲线在训练和测试数据集上都显示出良好的预测性能。SHAP值表明,AMH对RIF风险的影响最大,而CE、宫内粘连和BMI分别是预测RIF的第二、第三和第四重要危险因素。局限性,谨慎的原因:本研究受限于其来自单一生殖医学中心的回顾性设计。此外,一些疾病,如息肉、粘膜下肌瘤和风湿性疾病,在ART之前就已经治疗过了,这表明这些因素即使在治疗后也会影响RIF。研究结果的更广泛意义:除了年龄,某些高风险因素,如AMH,也应包括在RIF的考虑因素中。合并这些高危因素的患者可能需要更多的尝试才能成功怀孕。研究经费/竞争利益:本工作由广州市科技计划项目(202206010003)和国家自然科学基金(81871159)资助。没有作者有任何利益冲突。试验注册号:无。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Human reproduction
Human reproduction 医学-妇产科学
CiteScore
10.90
自引率
6.60%
发文量
1369
审稿时长
1 months
期刊介绍: Human Reproduction features full-length, peer-reviewed papers reporting original research, concise clinical case reports, as well as opinions and debates on topical issues. Papers published cover the clinical science and medical aspects of reproductive physiology, pathology and endocrinology; including andrology, gonad function, gametogenesis, fertilization, embryo development, implantation, early pregnancy, genetics, genetic diagnosis, oncology, infectious disease, surgery, contraception, infertility treatment, psychology, ethics and social issues.
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