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植入前子宫动脉多普勒检查与辅助生殖技术中临床妊娠的关联:一项系统评价和荟萃分析

Association of Pre-Implantation Uterine Artery Doppler with Clinical Pregnancy in Assisted Reproductive Technology: A Systematic Review and Meta-Analysis.

作者信息

Siargkas Antonios, Faka Areti, Kripouri Panagiota, Papanikolaou Evangelos, Stavros Sofoklis, Domali Ekaterini, Sioutis Dimos, Christodoulaki Chrysi, Mamopoulos Apostolos, Tsakiridis Ioannis, Dagklis Themistoklis

机构信息

3rd Department of Obstetrics and Gynecology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Agiou Dimitriou, 54124 Thessaloniki, Greece.

3rd Department of Obstetrics and Gynecology, University Hospital "ATTIKON", Medical School, National and Kapodistrian University of Athens, 12462 Athens, Greece.

出版信息

Medicina (Kaunas). 2025 May 28;61(6):1004. doi: 10.3390/medicina61061004.

Abstract

This meta-analysis aimed to determine whether pre-implantation uterine artery (UtA) Doppler measurements are associated with clinical pregnancy in women undergoing assisted reproductive technologies (ART). A systematic search of MEDLINE, Scopus, and the Cochrane Library from inception until 25 March 2025 was conducted to identify relevant studies. Additional records were retrieved through grey literature searching and manual reference checks. Eligible publications were observational studies or clinical trials that evaluated UtA Doppler indices prior to embryo transfer in adult women undergoing ART. Studies were required to report on clinical pregnancy rates, while those enrolling participants under 18 years of age, lacking Doppler data, or providing no pregnancy endpoints were excluded. Three reviewers independently assessed study quality using the Newcastle-Ottawa Scale and the Quality in Prognosis Studies tool. Meta-analyses were performed using a random-effects model to calculate mean differences (MDs) with 95% confidence intervals (CIs). Heterogeneity was examined via Cochran's Q and the I statistic. Sensitivity analyses excluded studies at high risk of bias. In total, 12 studies met the inclusion criteria, including a population of 3317 women. Women who achieved clinical pregnancy had a lower mean UtA pulsatility index (PI) (MD, -0.26; 95% CI, -0.46 to -0.06) and a higher peak systolic velocity (PSV) (MD, 8.59; 95% CI, 2.31 to 14.87) than those who did not conceive. Subgroup analyses showed that UtA PI measured during the menstrual cycle was lower in clinical pregnancy cases (MD, -0.38; 95% CI, -0.66 to -0.10). Measurements on the day of hCG administration or the day before showed a non-significant difference in UtA PI (MD, -0.43; 95% CI, -1.03 to 0.17), while assessments on the day of embryo transfer showed no significant difference between groups (MD, -0.02; 95% CI, -0.28 to 0.24). This meta-analysis suggests that lower UtA PI and higher PSV prior to embryo transfer are associated with higher clinical pregnancy rates in ART, particularly when measurements are taken during the menstrual cycle. Although these findings highlight a potential role for uterine hemodynamics in successful clinical pregnancy, UtA Doppler alone may not be a reliable predictor. Future studies should focus on earlier-cycle Doppler measurements and their integration into multifactorial models to improve prognostic accuracy.

摘要

本荟萃分析旨在确定在接受辅助生殖技术(ART)的女性中,植入前子宫动脉(UtA)多普勒测量与临床妊娠是否相关。对MEDLINE、Scopus和Cochrane图书馆从创刊至2025年3月25日进行了系统检索,以识别相关研究。通过灰色文献检索和手动参考文献检查获取了额外的记录。符合条件的出版物为观察性研究或临床试验,这些研究评估了接受ART的成年女性在胚胎移植前的UtA多普勒指数。研究需要报告临床妊娠率,而纳入18岁以下参与者、缺乏多普勒数据或未提供妊娠终点的研究被排除。三位评审员使用纽卡斯尔-渥太华量表和预后研究质量工具独立评估研究质量。使用随机效应模型进行荟萃分析,以计算95%置信区间(CIs)的平均差异(MDs)。通过Cochran's Q和I统计量检查异质性。敏感性分析排除了存在高偏倚风险的研究。总共12项研究符合纳入标准,包括3317名女性。与未受孕的女性相比,实现临床妊娠的女性平均UtA搏动指数(PI)较低(MD,-0.26;95%CI,-0.46至-0.06),收缩期峰值速度(PSV)较高(MD,8.59;95%CI,2.31至14.87)。亚组分析显示,在月经周期期间测量的UtA PI在临床妊娠病例中较低(MD,-0.38;95%CI,-0.66至-0.10)。在注射hCG当天或前一天进行的测量显示UtA PI无显著差异(MD,-0.43;95%CI,-1.03至0.17),而在胚胎移植当天进行的评估显示两组之间无显著差异(MD,-0.02;95%CI,-0.28至0.24)。 本荟萃分析表明,胚胎移植前较低的UtA PI和较高的PSV与ART中较高的临床妊娠率相关,特别是在月经周期期间进行测量时。尽管这些发现突出了子宫血流动力学在成功临床妊娠中的潜在作用,但仅UtA多普勒可能不是一个可靠的预测指标。未来的研究应侧重于更早周期的多普勒测量及其纳入多因素模型以提高预后准确性。

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