Human Development and Health, University of Southampton, Southampton SO16 5YA, UK.
IT Innovation Centre, School of Electronics and Computer Science, University of Southampton, Southampton SO16 7NS, UK.
Hum Reprod. 2021 Jan 1;36(1):99-106. doi: 10.1093/humrep/deaa251.
What is the optimal follicular tracking strategy for controlled ovarian stimulation (COS) in order to minimise face-to-face interactions?
As data from follicular tracking scans on Days 5, 6 or 7 of stimulation are the most useful to accurately predict trigger timing and risk of over-response, scans on these days should be prioritised if streamlined monitoring is necessary.
British Fertility Society guidance for centres restarting ART following coronavirus disease 2019 (COVID-19) pandemic-related shutdowns recommends reducing the number of patient visits for monitoring during COS. Current evidence on optimal monitoring during ovarian stimulation is sparse, and protocols vary significantly. Small studies of simplifying IVF therapy by minimising monitoring have reported no adverse effects on outcomes, including live birth rate. There are opportunities to learn from the adaptations necessary during these extraordinary times to improve the efficiency of IVF care in the longer term.
STUDY DESIGN, SIZE, DURATION: A retrospective database analysis of 9294 ultrasound scans performed during monitoring of 2322 IVF cycles undertaken by 1875 women in a single centre was performed. The primary objective was to identify when in the IVF cycle the data obtained from ultrasound are most predictive of both oocyte maturation trigger timing and an over-response to stimulation. If a reduced frequency of clinic visits is needed due to COVID-19 precautions, prioritising attendance for monitoring scans on the most predictive cycle days may be prudent.
PARTICIPANTS/MATERIALS, SETTING, METHODS: The study comprised anonymised retrospective database analysis of IVF/ICSI cycles at a tertiary referral IVF centre. Machine learning models are used in combining demographic and follicular tracking data to predict cycle oocyte maturation trigger timing and over-response. The primary outcome was the day or days in cycle from which scan data yield optimal model prediction performance statistics. The model for predicting trigger day uses patient age, number of follicles at baseline scan and follicle count by size for the current scan. The model to predict over-response uses age and number of follicles of a given size.
The earliest cycle day for which our model has high accuracy to predict both trigger day and risk of over-response is stimulation Day 5. The Day 5 model to predict trigger date has a mean squared error 2.16 ± 0.12 and to predict over-response an area under the receiver operating characteristic curve 0.91 ± 0.01.
LIMITATIONS, REASONS FOR CAUTION: This is a retrospective single-centre study and the results may not be generalisable to centres using different treatment protocols. The results are derived from modelling, and further clinical validation studies will verify the accuracy of the model.
Follicular tracking starting at Day 5 of stimulation may help to streamline the amount of monitoring required in COS. Previous small studies have shown that minimal monitoring protocols did not adversely impact outcomes. If IVF can safely be made less onerous on the clinic's resources and patient's time, without compromising success, this could help to reduce burden-related treatment drop-out.
STUDY FUNDING/COMPETING INTEREST(S): F.P.C. acknowledges funding from the NIHR Applied Research Collaboration Wessex. The authors declare they have no competing interests in relation to this work.
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为了将面对面的互动次数降至最低,控制性卵巢刺激(COS)的最佳卵泡跟踪策略是什么?
由于刺激第 5、6 或 7 天的卵泡跟踪扫描数据最有助于准确预测触发时机和过度反应的风险,因此如果需要简化监测,应优先进行这些天的扫描。
英国生育协会为因 2019 年冠状病毒病(COVID-19)大流行而关闭的中心重新启动辅助生殖技术(ART)的建议,建议减少 COS 期间监测患者就诊的次数。目前关于卵巢刺激期间最佳监测的证据很少,方案差异很大。通过最小化监测简化 IVF 治疗的小型研究报告称,对结局没有不良影响,包括活产率。从这些特殊时期的适应中吸取经验教训,有助于提高 IVF 护理的效率。
研究设计、大小和持续时间:对在一个中心进行的 2322 个 IVF 周期中 1875 名妇女进行的 9294 次超声扫描进行了回顾性数据库分析。主要目的是确定在 IVF 周期中何时获得的超声数据最能预测卵母细胞成熟触发时机和对刺激的过度反应。如果由于 COVID-19 预防措施需要减少就诊次数,那么优先进行最具预测性的周期日的监测扫描可能是明智的。
参与者/材料、地点和方法:该研究包括对三级转诊 IVF 中心的 IVF/ICSI 周期进行的匿名回顾性数据库分析。机器学习模型用于结合人口统计学和卵泡跟踪数据来预测周期卵母细胞成熟触发时机和过度反应。主要结果是从扫描数据中获得最佳模型预测性能统计数据的周期日或几天。预测触发日的模型使用患者年龄、基线扫描时的卵泡数量和当前扫描时的卵泡大小计数。预测过度反应的模型使用年龄和特定大小的卵泡数量。
我们的模型具有最高精度来预测触发日期和过度反应风险的最早周期日是刺激第 5 天。用于预测触发日期的第 5 天模型的均方误差为 2.16±0.12,用于预测过度反应的接收者操作特征曲线下面积为 0.91±0.01。
局限性、谨慎的原因:这是一项回顾性单中心研究,结果可能不适用于使用不同治疗方案的中心。结果是从建模中得出的,进一步的临床验证研究将验证模型的准确性。
刺激第 5 天开始的卵泡跟踪可能有助于简化 COS 所需的监测量。先前的小型研究表明,最小化监测方案不会对结局产生不利影响。如果可以安全地减少 IVF 对诊所资源和患者时间的负担,而不影响成功,这可能有助于减少与负担相关的治疗脱落。
研究资金/利益冲突:F.P.C. 得到了 NIHR 应用研究合作 Wessex 的资助。作者声明他们在这项工作中没有利益冲突。
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