Identifying key predictive features for live birth rate in advanced maternal age patients undergoing single vitrified-warmed blastocyst transfer

胚泡移植 单胚胎移植 胚泡 生殖医学 活产 医学 男科 胚胎移植 怀孕 生物 胚胎 胚胎发生 遗传学 细胞生物学
作者
Lidan Liu,Zhihua Wang,Ming Liao,Qiuying Gan,Qianyi Huang,Yihua Yang
出处
期刊:Reproductive Biology and Endocrinology [BioMed Central]
卷期号:22 (1)
标识
DOI:10.1186/s12958-024-01295-7
摘要

Infertility affects one in six couples worldwide, with advanced maternal age (AMA) posing unique challenges due to diminished ovarian reserve and reduced oocyte quality. Single vitrified-warmed blastocyst transfer (SVBT) has shown promise in assisted reproductive technology (ART), but success rates in AMA patients remain suboptimal. This study aimed to identify and refine predictive factors for live birth following SVBT in AMA patients, with the goal of enhancing clinical decision-making and enabling personalized treatment strategies. This retrospective cohort study analyzed 1,168 SVBT cycles conducted between June 2016 and December 2022 at the First Affiliated Hospital of Guangxi Medical University and Nanning Maternity and Child Health Hospital. Nineteen machine-learning models were applied to identify key predictive factors for live birth. Feature selection and 10-fold cross-validation were employed to validate the models. The most significant predictors of live birth included inner cell mass quality, trophectoderm quality, number of oocytes retrieved, endometrial thickness, and the presence of 8-cell blastomeres on day 3. The stacking model demonstrated the best predictive performance (AUC: 0.791), followed by Extra Trees (AUC: 0.784) and Random Forest (AUC: 0.768). These models outperformed traditional methods, achieving superior accuracy, sensitivity, and specificity. Leveraging advanced machine-learning models and identifying critical predictive factors can improve the accuracy of live birth outcome predictions for AMA patients undergoing SVBT. These findings offer valuable insights for enhancing clinical decision-making and managing patient expectations. Further research is needed to validate these results in larger, multi-center cohorts and to explore additional factors, including fresh embryo transfers, to broaden the applicability of these models in clinical practice.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
一叶知秋应助niuniu采纳,获得10
刚刚
刚刚
1秒前
xuanzhezhou完成签到,获得积分10
1秒前
卷卷更快乐完成签到 ,获得积分10
2秒前
李健应助deway采纳,获得10
2秒前
seven发布了新的文献求助20
2秒前
5秒前
6秒前
xuanzhezhou发布了新的文献求助10
7秒前
友好雅山完成签到,获得积分10
9秒前
量子星尘发布了新的文献求助10
9秒前
脑洞疼应助TQ采纳,获得10
9秒前
9秒前
乐乐应助哦啦啦采纳,获得10
9秒前
何佳丽完成签到,获得积分10
9秒前
希望天下0贩的0应助余欢采纳,获得10
10秒前
10秒前
11秒前
木悠完成签到,获得积分10
11秒前
充电宝应助过奖啦采纳,获得10
11秒前
千寻完成签到,获得积分0
12秒前
12秒前
优雅山柏发布了新的文献求助10
12秒前
12秒前
12秒前
13秒前
13秒前
Cici完成签到 ,获得积分10
14秒前
高兴的翠曼完成签到,获得积分10
14秒前
14秒前
14秒前
年轻的迎南完成签到,获得积分10
14秒前
14秒前
JamesPei应助林子青采纳,获得10
15秒前
风趣小蜜蜂完成签到 ,获得积分10
15秒前
曾绍炜完成签到,获得积分20
15秒前
16秒前
lczy发布了新的文献求助10
16秒前
17秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Handbook of Milkfat Fractionation Technology and Application, by Kerry E. Kaylegian and Robert C. Lindsay, AOCS Press, 1995 1000
The Social Work Ethics Casebook(2nd,Frederic G. R) 600
A novel angiographic index for predicting the efficacy of drug-coated balloons in small vessels 500
Textbook of Neonatal Resuscitation ® 500
The Affinity Designer Manual - Version 2: A Step-by-Step Beginner's Guide 500
Affinity Designer Essentials: A Complete Guide to Vector Art: Your Ultimate Handbook for High-Quality Vector Graphics 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5074163
求助须知:如何正确求助?哪些是违规求助? 4294315
关于积分的说明 13380837
捐赠科研通 4115699
什么是DOI,文献DOI怎么找? 2253823
邀请新用户注册赠送积分活动 1258466
关于科研通互助平台的介绍 1191322