A valuable predictive model for optimizing the timing of oocyte retrieval: a retrospective analysis of oocyte retrieval time in 49,961 oocyte pickup (OPU) cycles.

IF 4.7 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Yuting Huang, Zhe Kuang, Xi Shen, Yunhan Nie, Yuqi Zeng, Yali Liu, Li Wang
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引用次数: 0

Abstract

Background: In clinical practice, scheduling oocyte retrieval is a challenging issue that requires comprehensive consideration of factors such as the woman's age, ovarian response, hormone levels and other variables. Moreover, there is currently no consensus on how to effectively consider these factors and their weights in order to optimize the scheduling of oocyte retrieval for obtaining more mature oocytes.

Objective: To effectively identify the key determinants of oocyte retrieval time through an extensive analysis of retrospective clinical data, and to develop a valuable predictive model for optimizing the timing of oocyte retrieval in assisted reproductive technology (ART).

Study design: This retrospective study included 49,961 oocyte pickup (OPU) cycles, as well as 5567 subsequent ET cycles and 45,198 FET cycles between January 2010 and August 2024. Multiple linear regression (MLR) and directed acyclic graphs (DAG) were employed to identify the key determinants associated with oocyte retrieval time. Oocyte pickup (OPU) cycles achieving a minimum of 70% oocyte retrieval rate and 80% oocyte maturation rate, indicating well-organized timing of oocyte retrieval, were assigned to Group 1, while the remaining cycles were assigned to Group 2. The data from Group 1 was randomly divided into training and validation sets using the "sample" function in R software. The training set data was utilized to develop a predictive model for oocyte retrieval time based on former identified determinants using the "lm" function in R software. Subsequently, the performance of this model was evaluated and visualised using the "performance" and "plot" function, and further validated with the validation set from Group 1 as well as the data from Group 2.

Results: Female age, AFC, COH protocol, number of follicles > 14 mm in diameter on the day of trigger, and hormone levels on the day of trigger (including E2, P, and LH) were key determinants for the timing of oocyte retrieval. A valuable predictive formula for determining the optimal timing of oocyte retrieval has been formulated and validated: 37.43-0.02219*Female age + 0.01383*AFC + 0.00006* E2 level on the trigger day-0.00939*P level on the trigger day-0.05194*LH level on the trigger day + 0.01497*Number of follicles > 14 mm in diameter on the trigger day + β (β = 0.0000 in Short agonist protocol, β = -0.3320 in PPOS protocol, β = 0.8361 in GnRH antagonist protocol, β = -1.2280 in Mild stimulation protocol, β = 0.4160 in Long agonist protocol).

Conclusion: The female age, antral follicle count (AFC), controlled ovarian hyperstimulation (COH) protocol, number of follicles measuring > 14 mm in diameter on the trigger day, as well as hormone levels including E2, P, and LH on the trigger day are crucial factors influencing oocyte retrieval time. A robust predictive model for oocyte retrieval time was successfully developed from these factors and validated within a well-organized timing group for oocyte retrieval (oocyte retrieval rate ≥ 70% and oocyte maturation rate ≥ 80%).

优化卵母细胞提取时间的一个有价值的预测模型:对49,961个卵母细胞提取(OPU)周期中卵母细胞提取时间的回顾性分析。
背景:在临床实践中,安排卵母细胞回收是一个具有挑战性的问题,需要综合考虑妇女的年龄、卵巢反应、激素水平等因素。此外,如何有效地考虑这些因素及其权重,以优化卵母细胞回收的调度,获得更多成熟的卵母细胞,目前还没有达成共识。目的:通过对回顾性临床数据的广泛分析,有效识别影响卵母细胞取卵时间的关键因素,为辅助生殖技术(ART)中卵母细胞取卵时间的优化建立有价值的预测模型。研究设计:本回顾性研究包括2010年1月至2024年8月期间的49,961个卵母细胞采集(OPU)周期,5567个ET周期和45198个FET周期。采用多元线性回归(MLR)和有向无环图(DAG)来确定与卵母细胞回收时间相关的关键决定因素。卵母细胞拾取(OPU)周期达到至少70%的卵母细胞拾取率和80%的卵母细胞成熟率,表明卵母细胞拾取时间安排良好,被分配到第1组,而剩余的周期被分配到第2组。第1组的数据使用R软件中的“样本”函数随机分为训练集和验证集。利用训练集数据,利用R软件中的“lm”函数建立基于先前确定的决定因素的卵母细胞回收时间预测模型。随后,使用“performance”和“plot”函数对该模型的性能进行评估和可视化,并使用第1组的验证集和第2组的数据进一步验证。结果:女性年龄、AFC、COH方案、触发当天卵泡直径> ~ 14mm数量、触发当天激素水平(包括E2、P、LH)是取卵时机的关键决定因素。制定并验证了确定卵母细胞提取最佳时机的有价值的预测公式:37.43-0.02219*女性年龄+ 0.01383*AFC + 0.00006*触发日E2水平+ 0.00939*触发日P水平+ 0.05194*触发日LH水平+ 0.01497*触发日卵泡数>直径14mm + β(短激动剂方案β = 0.0000, PPOS方案β = -0.3320, GnRH拮抗剂方案β = 0.8361,轻度刺激方案β = -1.2280,长激动剂方案β = 0.4160)。结论:女性年龄、卵泡计数(AFC)、控制性卵巢过度刺激(COH)方案、触发日直径为> ~ 14mm的卵泡数以及触发日E2、P、LH等激素水平是影响卵母细胞回收时间的关键因素。根据这些因素成功建立了一个强大的卵母细胞提取时间预测模型,并在一个组织良好的卵母细胞提取时间组(卵母细胞提取率≥70%,卵母细胞成熟率≥80%)中进行了验证。
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
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.
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