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Does assisted hatching affect live birth in fresh, first cycle in vitro fertilization in good and poor prognosis patients?

ABSTRACT: PURPOSE:To assess the effect of assisted hatching (AH) on live birth rate (LBR) in first cycle, fresh in vitro fertilization (IVF) in good and poor prognosis patients. METHODS:Retrospective cohort using cycles reported to the Society for Assisted Reproductive Technology Clinic Outcomes Reporting System. Live birth rate was compared in women who underwent first cycle, autologous, fresh IVF cycles with (n = 48,858) and without (n = 103,413) AH from 2007 to 2015. RESULTS:The propensity-weighted LBR was 39.2% with AH versus 43.9% without AH in all patients. The rate difference (RD) with AH was - 4.7% ([CI - 0.053, - 0.040], P < 0.001) with the calculated number needed to harm being 22. AH affected live birth in both good prognosis and poor prognosis patients. The propensity-weighted monozygotic twinning (MZT) rate was 2.3% in patients treated with AH as compared to 1.2% patients that did not receive AH. The RD with AH on MZT in fresh, first IVF cycles was 1.1% ([0.008, 0.014], P < 0.001). CONCLUSION:AH may affect LBR across all patients and in poor prognosis patients in fresh IVF cycles. Caution should be exercised when applying this technology. More prospective research is needed.

SUBMITTER: McLaughlin JE

PROVIDER: S-EPMC6911124 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Does assisted hatching affect live birth in fresh, first cycle in vitro fertilization in good and poor prognosis patients?

McLaughlin Jessica E JE Choi Byeong Y BY Liu Qianqian Q Gelfond Jonathan A JA Robinson Randal D RD Chang T Arthur TA Knudtson Jennifer F JF

Journal of assisted reproduction and genetics 20191112 12

<h4>Purpose</h4>To assess the effect of assisted hatching (AH) on live birth rate (LBR) in first cycle, fresh in vitro fertilization (IVF) in good and poor prognosis patients.<h4>Methods</h4>Retrospective cohort using cycles reported to the Society for Assisted Reproductive Technology Clinic Outcomes Reporting System. Live birth rate was compared in women who underwent first cycle, autologous, fresh IVF cycles with (n = 48,858) and without (n = 103,413) AH from 2007 to 2015.<h4>Results</h4>The p ...[more]

PMID: 31713775

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Project description:INTRODUCTION:Recent data suggest a higher clinical pregnancy rate performing assisted hatching (AH) on previously cryopreserved embryos but fail to demonstrate significant effects on live birth rate. However, current evidence is based on studies with a small sample size and may hide a type II error. Moreover, poor attention has been given to the specific effect of AH on frozen/thawed blastocysts. To shed light on this topic, we developed the present protocol for a randomised trial to investigate the benefits of the laser-mediated partial removal of the zona pellucida in vitrified/warmed blastocysts. METHODS AND ANALYSIS:The pArtiaL zonA pelluciDa removal by assisteD hatchINg of blastocysts (ALADDIN) study is a multicentric prospective comparative study with a parallel randomised controlled design aiming to investigate whether AH performed on warmed blastocysts before embryo transfer can improve live birth rate. Women allocated to the control group will undergo embryo transfer of blastocysts not previously subjected to AH. Two infertility units will be involved in the study. Enrolment of patients will last 18 months with quarterly monitoring and the entire study is foreseen to be closed in 36 months. Secondary outcomes include: proportion of transferred blastocysts/thawed blastocyst, morphological features of blastocysts before embryo transfer, implantation, biochemical pregnancy, clinical pregnancy (ultrasound visible gestational sac), miscarriage, multiple pregnancy, preterm birth (<37 weeks of gestation), obstetrical and neonatal complications and congenital anomaly rates. ETHICS AND DISSEMINATION:This protocol received a favourable ethical opinion from the Ethical Committee of IRCCS San Raffaele Scientific Institute and the Ethical Committee Area 2 Milan. Each participant will provide written consent to participate and remain encoded during the study. The trial results will be published in peer-reviewed journals and presented at conferences. TRIAL REGISTRATION NUMBER:NCT03623659; Pre-results.

Project description:In-vitro fertilization (IVF) is a popular method of resolving complications such as endometriosis, poor egg quality, a genetic disease of mother or father, problems with ovulation, antibody problems that harm sperm or eggs, the inability of sperm to penetrate or survive in the cervical mucus and low sperm counts, resulting human infertility. Nevertheless, IVF does not guarantee success in the fertilization. Choosing IVF is burdensome for the reason of high cost and uncertainty in the result. As the complications and fertilization factors are numerous in the IVF process, it is a cumbersome task for fertility doctors to give an accurate prediction of a successful birth. Artificial Intelligence (AI) has been employed in this study for predicting the live-birth occurrence. This work mainly focuses on making predictions of live-birth occurrence when an embryo forms from a couple and not a donor. Here, we compare various AI algorithms, including both classical Machine Learning, deep learning architecture, and an ensemble of algorithms on the publicly available dataset provided by Human Fertilisation and Embryology Authority (HFEA). Insights on data and metrics such as confusion matrices, F1-score, precision, recall, receiver operating characteristic (ROC) curves are demonstrated in the subsequent sections. The training process has two settings Without feature selection and With feature selection to train classifier models. Machine Learning, Deep learning, ensemble models classification paradigms have been trained in both settings. The Random Forest model achieves the highest F1-score of 76.49% in without feature selection setting. For the same model, the precision, recall, and area under the ROC Curve (ROC AUC) scores are 77%, 76%, and 84.60%, respectively. The success of the pregnancy depends on both male and female traits and living conditions. This study predicts a successful pregnancy through the clinically relevant parameters in In-vitro fertilization. Thus artificial intelligence plays a promising role in decision making process to support the diagnosis, prognosis, treatment etc.

Project description:ImportanceThe likelihood of achieving a live birth with repeat in vitro fertilization (IVF) is unclear, yet treatment is commonly limited to 3 or 4 embryo transfers.ObjectiveTo determine the live-birth rate per initiated ovarian stimulation IVF cycle and with repeated cycles.Design, setting, and participantsProspective study of 156,947 UK women who received 257,398 IVF ovarian stimulation cycles between 2003 and 2010 and were followed up until June 2012.ExposuresIn vitro fertilization, with a cycle defined as an episode of ovarian stimulation and all subsequent separate fresh and frozen embryo transfers.Main outcomes and measuresLive-birth rate per IVF cycle and the cumulative live-birth rates across all cycles in all women and by age and treatment type. Optimal, prognosis-adjusted, and conservative cumulative live-birth rates were estimated, reflecting 0%, 30%, and 100%, respectively, of women who discontinued due to poor prognosis and having a live-birth rate of 0 had they continued.ResultsAmong the 156,947 women, the median age at start of treatment was 35 years (interquartile range, 32-38; range, 18-55), and the median duration of infertility for all 257,398 cycles was 4 years (interquartile range, 2-6; range, <1-29). In all women, the live-birth rate for the first cycle was 29.5% (95% CI, 29.3%-29.7%). This remained above 20% up to and including the fourth cycle. The cumulative prognosis-adjusted live-birth rate across all cycles continued to increase up to the ninth cycle, with 65.3% (95% CI, 64.8%-65.8%) of women achieving a live birth by the sixth cycle. In women younger than 40 years using their own oocytes, the live-birth rate for the first cycle was 32.3% (95% CI, 32.0%-32.5%) and remained above 20% up to and including the fourth cycle. Six cycles achieved a cumulative prognosis-adjusted live-birth rate of 68.4% (95% CI, 67.8%-68.9%). For women aged 40 to 42 years, the live-birth rate for the first cycle was 12.3% (95% CI, 11.8%-12.8%), with 6 cycles achieving a cumulative prognosis-adjusted live-birth rate of 31.5% (95% CI, 29.7%-33.3%). For women older than 42 years, all rates within each cycle were less than 4%. No age differential was observed among women using donor oocytes. Rates were lower for women with untreated male partner-related infertility compared with those with any other cause, but treatment with either intracytoplasmic sperm injection or sperm donation removed this difference.Conclusions and relevanceAmong women in the United Kingdom undergoing IVF, the cumulative prognosis-adjusted live-birth rate after 6 cycles was 65.3%, with variations by age and treatment type. These findings support the efficacy of extending the number of IVF cycles beyond 3 or 4.

Project description:Study questionDoes the interval from delivery to initiation of a subsequent ART treatment cycle impact clinical pregnancy or live birth rates?Summary answerAn interval from delivery to treatment start of <6 months or ?24 months is associated with decreased likelihood of clinical pregnancy and live birth.What is known alreadyShort interpregnancy intervals are associated with poor obstetric outcomes in the naturally conceiving population prompting birth spacing recommendations of 18-24 months from international organizations. Deferring a subsequent pregnancy attempt means a woman will age in the interval with an attendant decline in her fertility.Study design, size, durationRetrospective analysis of the Society for Assisted Reproductive Technology Clinical Outcome Reporting System (SARTCORS) cohort containing 61 686 ART cycles from 2004 to 2013.Participants/materials, setting, methodsThe delivery-to-cycle interval (DCI) was calculated for patients from SARTCORS with a history of live birth from ART who returned to the same clinic for a first subsequent treatment cycle. Generalized linear models were fit to determine the risk of clinical pregnancy and live birth by DCI with subsequent adjustment for factors associated with outcomes of interest. Predicted probabilities of clinical pregnancy and live birth were generated from each model.Main results and the role of chanceA DCI of <6 months was associated with a 5.6% reduction in probability of clinical pregnancy (40.1 ± 1.9 versus 45.7 ± 0.6%, P = 0.009) and 6.8% reduction in live birth (31.6 ± 1.7 versus 38.4 ± 0.6%, P = 0.001) per cycle start compared to a DCI of 12 to <18 months. A DCI of ?24 months was associated with a 5.1% reduction in probability of clinical pregnancy (40.6 ± 0.5 versus 45.7 ± 0.6%, P < 0.001) and 5.7% reduction in live birth (32.7 ± 0.5 versus 38.4 ± 0.6%, P < 0.001) compared to 12 to <18 months.Limitations, reasons for cautionThe SART database is reliant upon self-report of many variables of interest including live birth. It remains unclear whether poorer outcomes are a result of residual confounding from factors inherent to the population with a very short or long DCI or the interval itself.Wider implications of the findingsBirth spacing recommendations for naturally conceiving populations may not be generally applicable to patients with a history of infertility. Patients planning ART treatment should wait a minimum of 6 months, but not more than 24 months, from a live birth for optimization of clinical pregnancy and live birth rates.Study funding/competing interest(s)National Center for Advancing Translational Sciences, National Institutes of Health, UCSF-CTSI Grant number UL1TR001872. The authors have no competing interests.

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Does assisted hatching affect live birth in fresh, first cycle in vitro fertilization in good and poor prognosis patients?

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Does assisted hatching affect live birth in fresh, first cycle in vitro fertilization in good and poor prognosis patients?

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