Dataset Information

Impact of Women Obesity and Obesity Severity on Live Birth Rate after In Vitro Fertilization.

ABSTRACT: Access to in vitro fertilization (IVF) for obese women varies across centers, and the impact of obesity on IVF outcomes is widely discussed. We assessed the impact of obesity and its severity on live birth rate (LBR) after IVF. We included women treated for IVF in our center. Data were prospectively collected in the BabySentryTM software. LBR per cycle and cumulative LBR including all attempts of the couple were calculated, considering transfer of both fresh and frozen embryos. Of 1588 included women (2379 controlled ovarian stimulations), 70.2%, 19.5%, 7.9%, and 2.4% were normal-weight, overweight, class I obesity, and class II/III obesity, respectively. For each cycle, LBR did not differ according to BMI category. Adjusted odds ratios (95% confidence intervals) for obtaining a live birth at the first cycle were 1.11 (0.78-1.58) for overweight, 1.17 (0.70-1.95) for class I obese, and 1.05 (0.48-2.31) for class II/III obese women, as compared with normal-weight women. Similarly, no significant associations were found at cycles 2, 3, and 4. Cumulative LBR increased with the number of cycles, independently of the BMI class (p log-rank = 0.91). After adjustment, obesity status did not impact significantly the miscarriage rate, regardless of the cycle. In conclusion, neither women obesity nor its severity impacted the cumulative LBR after IVF.

SUBMITTER: Brunet C

PROVIDER: S-EPMC7463979 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Impact of Women Obesity and Obesity Severity on Live Birth Rate after In Vitro Fertilization.

Brunet Cécile C Aouinti Safa S Huguet Fanchon F Macioce Valérie V Ranisavljevic Noémie N Gala Anna A Avignon Antoine A Mura Thibault T Sultan Ariane A

Journal of clinical medicine 20200728 8

Access to in vitro fertilization (IVF) for obese women varies across centers, and the impact of obesity on IVF outcomes is widely discussed. We assessed the impact of obesity and its severity on live birth rate (LBR) after IVF. We included women treated for IVF in our center. Data were prospectively collected in the BabySentry<sup>TM</sup> software. LBR per cycle and cumulative LBR including all attempts of the couple were calculated, considering transfer of both fresh and frozen embryos. Of 158 ...[more]

PMID: 32731470

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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: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:ImportanceAlthough multiple mechanisms have been proposed to explain the infertility related to endometriosis, there are no conclusive data on the association of endometriosis with endometrial receptivity. The oocyte donation model in assisted reproduction technology (ART) cycles can clarify this issue.ObjectiveTo explore the association of a history of endometriosis with ART outcomes in recipients of oocyte donation.Data sourcesIn this systematic review and meta-analysis, electronic databases were searched from inception until August 31, 2023, using combinations of relevant keywords. Moreover, we retrieved data from the databases of the Society for Assisted Reproductive Technology (SART) in the US and the Human Fertilization and Embryology Authority (HFEA) in the United Kingdom.Study selectionObservational studies were included if they investigated the impact of endometriosis on ART outcomes with donor oocytes.Data extraction and synthesisPublicly available data related to ART from various sources were gathered, and a retrospective aggregate and nonaggregate analysis using registries of in vitro fertilization cycles with oocyte or embryo donation was conducted.Main outcomes and measuresThe primary outcome was live birth rate (LBR) following oocyte donor cycles. The effect measures of comparisons between groups are presented as odds ratios (ORs) with a 95% CI.ResultsThis study analyzed 7212 oocyte donation cycles from 4 studies for the meta-analysis, along with 162 082 cycles from 2 registries (137 182 from SART and 24 900 from HFEA). No significant differences between the groups were observed in the meta-analysis of published data after adjusting for confounding factors (OR, 0.54; 95% CI, 0.19-1.57). A statistically significant lower LBR was identified in women with endometriosis when analyzing the aggregate data from SART and HFEA databases (OR, 0.89; 95% CI, 0.81-0.97).Conclusions and relevanceThis study found a modest decrease in LBR among women with a history of endometriosis, although only results from the pooled analysis of registry data and not those from the meta-analysis reached statistical significance. These findings suggest that a marginal impairment of uterine receptivity may contribute to infertility mechanisms in women affected by endometriosis.

Dataset Information

Impact of Women Obesity and Obesity Severity on Live Birth Rate after In Vitro Fertilization.

Publications

Impact of Women Obesity and Obesity Severity on Live Birth Rate after In Vitro Fertilization.

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