Clinical outcomes of single blastocyst transfer with machine learning guided noninvasive chromosome screening grading system in infertile patients.

IF 4.2 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM Reproductive Biology and Endocrinology Pub Date : 2024-05-23 DOI:10.1186/s12958-024-01231-9
Xiaoxi Li, Yaxin Yao, Dunmei Zhao, Xiufeng Chang, Yi Li, Huilan Lin, Huijuan Wei, Haiye Wang, Ying Mi, Lei Huang, Sijia Lu, Weimin Yang, Liyi Cai
{"title":"Clinical outcomes of single blastocyst transfer with machine learning guided noninvasive chromosome screening grading system in infertile patients.","authors":"Xiaoxi Li, Yaxin Yao, Dunmei Zhao, Xiufeng Chang, Yi Li, Huilan Lin, Huijuan Wei, Haiye Wang, Ying Mi, Lei Huang, Sijia Lu, Weimin Yang, Liyi Cai","doi":"10.1186/s12958-024-01231-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Prospective observational studies have demonstrated that the machine learning (ML) -guided noninvasive chromosome screening (NICS) grading system, which we called the noninvasive chromosome screening-artificial intelligence (NICS-AI) grading system, can be used embryo selection. The current prospective interventional clinical study was conducted to investigate whether this NICS-AI grading system can be used as a powerful tool for embryo selection.</p><p><strong>Methods: </strong>Patients who visited our centre between October 2018 and December 2021 were recruited. Grade A and B embryos with a high probability of euploidy were transferred in the NICS group. The patients in the control group selected the embryos according to the traditional morphological grading. Finally, 90 patients in the NICS group and 161 patients in the control group were compared statistically for their clinical outcomes.</p><p><strong>Results: </strong>In the NICS group, the clinical pregnancy rate (70.0% vs. 54.0%, p < 0.001), the ongoing pregnancy rate (58.9% vs. 44.7%, p = 0.001), and the live birth rate (56.7% vs. 42.9%, p = 0.001) were significantly higher than those of the control group. When the female was ≥ 35 years old, the clinical pregnancy rate (67.7% vs. 32.1%, p < 0.001), ongoing pregnancy rate (56.5% vs. 25.0%, p = 0.001), and live birth rate (54.8% vs. 25.0%, p = 0.001) in the NICS group were significantly higher than those of the control group. Regardless of whether the patients had a previous record of early spontaneous abortion or not, the live birth rate of the NICS group was higher than that of the control group (61.0% vs. 46.9%; 57.9% vs. 34.8%; 33.3% vs. 0%) but the differences were not statistically significant.</p><p><strong>Conclusions: </strong>NICS-AI was able to improve embryo utilisation rate, and the live birth rate, especially for those ≥ 35 years old, with transfer of Grade A embryos being preferred, followed by Grade B embryos. NICS-AI can be used as an effective tool for embryo selection in the future.</p>","PeriodicalId":21011,"journal":{"name":"Reproductive Biology and Endocrinology","volume":"22 1","pages":"61"},"PeriodicalIF":4.2000,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11112939/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Reproductive Biology and Endocrinology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12958-024-01231-9","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Prospective observational studies have demonstrated that the machine learning (ML) -guided noninvasive chromosome screening (NICS) grading system, which we called the noninvasive chromosome screening-artificial intelligence (NICS-AI) grading system, can be used embryo selection. The current prospective interventional clinical study was conducted to investigate whether this NICS-AI grading system can be used as a powerful tool for embryo selection.

Methods: Patients who visited our centre between October 2018 and December 2021 were recruited. Grade A and B embryos with a high probability of euploidy were transferred in the NICS group. The patients in the control group selected the embryos according to the traditional morphological grading. Finally, 90 patients in the NICS group and 161 patients in the control group were compared statistically for their clinical outcomes.

Results: In the NICS group, the clinical pregnancy rate (70.0% vs. 54.0%, p < 0.001), the ongoing pregnancy rate (58.9% vs. 44.7%, p = 0.001), and the live birth rate (56.7% vs. 42.9%, p = 0.001) were significantly higher than those of the control group. When the female was ≥ 35 years old, the clinical pregnancy rate (67.7% vs. 32.1%, p < 0.001), ongoing pregnancy rate (56.5% vs. 25.0%, p = 0.001), and live birth rate (54.8% vs. 25.0%, p = 0.001) in the NICS group were significantly higher than those of the control group. Regardless of whether the patients had a previous record of early spontaneous abortion or not, the live birth rate of the NICS group was higher than that of the control group (61.0% vs. 46.9%; 57.9% vs. 34.8%; 33.3% vs. 0%) but the differences were not statistically significant.

Conclusions: NICS-AI was able to improve embryo utilisation rate, and the live birth rate, especially for those ≥ 35 years old, with transfer of Grade A embryos being preferred, followed by Grade B embryos. NICS-AI can be used as an effective tool for embryo selection in the future.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
不孕症患者使用机器学习引导的无创染色体筛查分级系统进行单囊胚移植的临床效果。
背景:前瞻性观察研究表明,机器学习(ML)指导下的无创染色体筛查(NICS)分级系统(我们称之为无创染色体筛查-人工智能(NICS-AI)分级系统)可用于胚胎选择。本次前瞻性介入临床研究旨在探究该NICS-AI分级系统能否作为胚胎选择的有力工具:招募2018年10月至2021年12月期间到我中心就诊的患者。在 NICS 组中移植了极易发生非整倍体的 A 级和 B 级胚胎。对照组患者根据传统的形态学分级选择胚胎。最后,对 NICS 组的 90 名患者和对照组的 161 名患者的临床结果进行统计比较:结果:NICS 组的临床妊娠率(70.0% 对 54.0%,PNICS-AI能够提高胚胎利用率和活产率,尤其是对于年龄≥35岁的患者,A级胚胎是首选,其次是B级胚胎。未来,NICS-AI 可作为胚胎选择的有效工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Reproductive Biology and Endocrinology
Reproductive Biology and Endocrinology 医学-内分泌学与代谢
CiteScore
7.90
自引率
2.30%
发文量
161
审稿时长
4-8 weeks
期刊介绍: Reproductive Biology and Endocrinology publishes and disseminates high-quality results from excellent research in the reproductive sciences. The journal publishes on topics covering gametogenesis, fertilization, early embryonic development, embryo-uterus interaction, reproductive development, pregnancy, uterine biology, endocrinology of reproduction, control of reproduction, reproductive immunology, neuroendocrinology, and veterinary and human reproductive medicine, including all vertebrate species.
期刊最新文献
Contrast induced nephropathy in women with infertility undergoing hysterosalpingography. Müllerian anomalies and endometriosis: associations and phenotypic variations. Is oral dydrogesterone equivalent to vaginal micronized progesterone for luteal phase support in women receiving oocyte donation? Pre-pregnancy LDL/HDL and total Cholesterol/HDL ratios are strong predictors of gestational diabetes mellitus in women undergoing assisted reproductive technologies. Whole-exome sequencing and Drosophila modelling reveal mutated genes and pathways contributing to human ovarian failure.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1