受精障碍预测：106728 个治疗周期的受精/卵胞浆内单精子注射回顾性研究。
Prediction of Fertilization Disorders in the Fertilization/Intracytoplasmic Sperm Injection: A Retrospective Study of 106,728 Treatment Cycles.
机构信息
Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China.
National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China.
出版信息
Front Endocrinol (Lausanne). 2022 Apr 20;13:870708. doi: 10.3389/fendo.2022.870708. eCollection 2022.
PURPOSE
This study aimed to develop a risk prediction of fertilization disorders during the fertilization/intracytoplasmic sperm injection (IVF/ICSI).
METHODS
A retrospective study was performed with 106,728 fresh embryo IVF/ICSI cycles from 2009 to 2019. Basic characteristics of patients, clinical treatment data, and laboratory parameters were involved. The associations between the selected variables and risks for low fertilization rate (LFR) and total fertilization failure (TFF) were investigated. Ordinal logistic regression and the receiver operating characteristic curves (ROCs) were used to construct and evaluate the prediction models.
RESULTS
A total of 97,181 controls, 4,343 LFR and 5,204 TFF cases were involved in this study. The model based on clinical characteristics (the ages of the couples, women's BMI, types of infertility, ART failure history, the diminished ovarian reserve, sperm quality, insemination method, and the number of oocytes retrieved) had an AUC of 0.743 for TFF. The laboratory model showed that primary infertility, ART failure history, minimal-stimulation cycle/natural cycle, numbers of oocyte retrieved < 5, IVF, and Anti-Mullerian hormone (AMH) level < 1.1ng/ml are predictors of TFF, with an AUC of 0.742.
CONCLUSION
We established a clinical and a laboratory prediction model for LFR/TFF. Both of the models showed relatively high AUCs.
目的
本研究旨在建立受精/卵胞浆内单精子注射（IVF/ICSI）受精障碍的风险预测模型。
方法
回顾性研究纳入了 2009 年至 2019 年期间 106728 例新鲜胚胎 IVF/ICSI 周期。研究纳入了患者的基本特征、临床治疗数据和实验室参数。分析了所选变量与低受精率（LFR）和总受精失败（TFF）风险之间的关系。采用有序逻辑回归和受试者工作特征曲线（ROC）构建和评估预测模型。
结果
本研究共纳入了 97181 例对照组、4343 例 LFR 组和 5204 例 TFF 组。基于临床特征（夫妇年龄、女性 BMI、不孕类型、ART 失败史、卵巢储备功能减退、精子质量、授精方式和获卵数）的模型对 TFF 的 AUC 为 0.743。实验室模型表明，原发不孕、ART 失败史、微刺激/自然周期、获卵数<5、IVF 和抗苗勒管激素（AMH）水平<1.1ng/ml 是 TFF 的预测因素，其 AUC 为 0.742。
结论
本研究建立了 LFR/TFF 的临床和实验室预测模型。两个模型的 AUC 均较高。
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