Streamlining follicular monitoring during controlled ovarian stimulation: a data-driven approach to efficient IVF care in the new era of social distancing

Author:

Robertson I,Chmiel F P1,Cheong Y2

Affiliation:

1. IT Innovation Centre, School of Electronics and Computer Science, University of Southampton, Southampton SO16 7NS, UK

2. Human Development and Health, University of Southampton, Southampton SO16 5YA, UK

Abstract

Abstract STUDY QUESTION What is the optimal follicular tracking strategy for controlled ovarian stimulation (COS) in order to minimise face-to-face interactions? SUMMARY ANSWER 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. WHAT IS KNOWN ALREADY 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. MAIN RESULTS AND THE ROLE OF CHANCE 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. WIDER IMPLICATIONS OF THE FINDINGS 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. TRIAL REGISTRATION NUMBER N/A.

Funder

NIHR Applied Research Collaboration Wessex

Publisher

Oxford University Press (OUP)

Subject

Obstetrics and Gynecology,Rehabilitation,Reproductive Medicine

Reference14 articles.

1. Timed oocyte collection in an assisted conception program using GnRH analog;Abdalla;Hum Reprod,1989

2. ART in Europe, 2015: results generated from European registries by ESHRE;De Geyter;Hum Reprod Open,2020

3. Understanding the perceptions of and emotional barriers to infertility treatment: a survey in four European countries;Domar;Hum Reprod,2012

4. ESHRE guideline: ovarian stimulation for IVF/ICSI;ESHRE;Hum Reprod Open,2020

5. Self-operated endovaginal telemonitoring versus traditional monitoring of ovarian stimulation in assisted reproduction: an RCT;Gerris;Hum Reprod,2014

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3