Construction and validation of a prediction model to minimize twin rates at preserved high live birth rates after IVF

Perinatal Outcomes of Monochorionic Twin Pregnancies Conceived Naturally Versus through Assisted Reproductive Techniques

Objective: It has been reported that monochorionic twin pregnancies conceived through assisted reproductive techniques (ART) display a higher risk of second-trimester miscarriage, cesarean delivery, and neonatal death than those conceived naturally. The aim of this study was to compare the perinatal outcomes of monochorionic diamniotic (MCDA) twin pregnancies conceived naturally and through ART in a tertiary hospital. Methods: This was a retrospective cohort study of all MCDA twin pregnancies that received obstetric care and delivered at La Fe University and Polytechnic Hospital between 2015 and 2021. MCDA pregnancies that were referred to the tertiary hospital for specialized management, follow-up, and delivery were also included. The study was approved by The Health Research Institute Hospital La Fe (IIS La Fe). Results: Among the 184 MCDA pregnancies, 149 (81%) had a natural conception, and 35 (19%) were conceived through ART. Patients with an MCDA pregnancy who conceived through ART had a significantly older maternal age (38.0 [35.5-42.5] vs. 32.0 [29.0-36.0], p < 0.001) and an elevated rate of nulliparity (80.0% vs. 50.3%, p = 0.001). Regarding pregnancy complications, MCDA pregnancies through ART were associated with a significantly higher incidence of gestational diabetes (22.9% vs. 2.7%, p < 0.001), hypertensive disorders during pregnancy (22.9% vs. 9.4%, p = 0.04), and other pregnancy complications such as threatened labor or preterm prelabor rupture of membranes (14.3% vs. 36.2%, p = 0.015), than naturally conceived MCDA pregnancies. No differences were found in the incidence of twin-to-twin transfusion syndrome (20% vs. 33.6%, p = 0.155). MCDA pregnancies through natural conception had a greater rate of vaginal delivery than MCDA through ART (16.8% vs. 2.9%, p = 0.032). When adjusted for confounding factors, MCDA pregnancies through ART were only more likely to develop gestational diabetes than those naturally conceived (aOR 7.86, 95% CI 1.55-39.87). No differences were found regarding neonatal outcomes between groups. Conclusions: Compared with naturally conceived MCDA twin pregnancies, those conceived through ART displayed a significantly higher risk of developing gestational diabetes. No differences regarding other pregnancy complications, mode of delivery, or neonatal outcomes were found between groups.

Association between chemical mixtures and female fertility in women undergoing assisted reproduction in Sweden and Estonia

OBJECTIVE

Women of reproductive age are exposed to ubiquitous chemicals such as phthalates, parabens, and per- and polyfluoroalkyl substances (PFAS), which have potential endocrine disrupting properties and might affect fertility. Our objective was to investigate associations between potential endocrine-disrupting chemicals (EDCs) and female fertility in two cohorts of women attending fertility clinics.

METHODS

In a total population of 333 women in Sweden and Estonia, we studied the associations between chemicals and female fertility, evaluating ovarian sensitivity index (OSI) as an indicator of ovarian response, as well as clinical pregnancy and live birth from fresh and frozen embryo transfers. We measured 59 chemicals in follicular fluid samples and detected 3 phthalate metabolites, di-2-ethylhexyl phthalate (DEHP) metabolites, 1 paraben, and 6 PFAS in >90% of the women. Associations were evaluated using multivariable-adjusted linear or logistic regression, categorizing EDCs into quartiles of their distributions, as well as with Bayesian Kernel Machine Regression.

RESULTS

We observed statistically significant lower OSI at higher concentrations of the sum of DEHP metabolites in the Swedish cohort (Q4 vs Q1, β = -0.21, 95% CI: -0.38, -0.05) and methylparaben in the Estonian cohort (Q3 vs Q1, β = -0.22, 95% CI: -0.44, -0.01). Signals of potential associations were also observed at higher concentrations of PFUnDA in both the combined population (Q2 vs. Q1, β = -0.16, 95% CI -0.31, -0.02) and the Estonian population (Q2 vs. Q1, β = -0.27, 95% CI -0.45, -0.08), and for PFOA in the Estonian population (Q4 vs. Q1, β = -0.31, 95% CI -0.61, -0.01). Associations of chemicals with clinical pregnancy and live birth presented wide confidence intervals.

CONCLUSIONS

Within a large chemical mixture, we observed significant inverse associations levels of DEHP metabolites and methylparaben, and possibly PFUnDA and PFOA, with OSI, suggesting that these chemicals may contribute to altered ovarian function and infertility in women.

Nomogram based on clinical and laboratory characteristics of euploid embryos using the data in PGT-A: a euploid-prediction model

BACKGROUND

The evaluation of embryo morphology may be inaccurate. A euploid prediction model is needed to provide the best and individualized counseling about embryo selection based on patients and embryo characteristics.

METHODS

Our objective was to develop a euploid-prediction model for evaluating blastocyst embryos, based on data from a large cohort of patients undergoing pre-implantation genetic testing for aneuploidy (PGT-A). This retrospective, single-center cohort study included data from 1610 blastocysts which were performed PGT-A with known genetic outcomes. The study population was divided into the training and validation cohorts in a 3:1 ratio. The performance of the euploid-prediction model was quantified using the area under the receiver operating characteristic (ROC) curve (AUC). In addition, a nomogram was drawn to provide quantitative and convenient tools in predicting euploid.

RESULTS

We developed a reliable euploid-prediction model and can directly assess the probability of euploid with the AUC (95%CI) of 0.859 (0.834,0.872) in the training cohort, and 0.852 (0.831,0.879) in the validation cohort, respectively. The euploid-prediction model showed sensitivities of 0.903 and specificities of 0.578.

CONCLUSIONS

The euploid-prediction model is a reliable prediction model and can directly assess the probability of euploid.

Individualized embryo selection strategy developed by stacking machine learning model for better in vitro fertilization outcomes: an application study

BACKGROUND

To minimize the rate of in vitro fertilization (IVF)- associated multiple-embryo gestation, significant efforts have been made. Previous studies related to machine learning in IVF mainly focused on selecting the top-quality embryos to improve outcomes, however, in patients with sub-optimal prognosis or with medium- or inferior-quality embryos, the selection between SET and DET could be perplexing.

METHODS

This was an application study including 9211 patients with 10,076 embryos treated during 2016 to 2018, in Tongji Hospital, Wuhan, China. A hierarchical model was established using the machine learning system XGBoost, to learn embryo implantation potential and the impact of double embryos transfer (DET) simultaneously. The performance of the model was evaluated with the AUC of the ROC curve. Multiple regression analyses were also conducted on the 19 selected features to demonstrate the differences between feature importance for prediction and statistical relationship with outcomes.

RESULTS

For a single embryo transfer (SET) pregnancy, the following variables remained significant: age, attempts at IVF, estradiol level on hCG day, and endometrial thickness. For DET pregnancy, age, attempts at IVF, endometrial thickness, and the newly added P1 + P2 remained significant. For DET twin risk, age, attempts at IVF, 2PN/ MII, and P1 × P2 remained significant. The algorithm was repeated 30 times, and averaged AUC of 0.7945, 0.8385, and 0.7229 were achieved for SET pregnancy, DET pregnancy, and DET twin risk, respectively. The trend of predictive and observed rates both in pregnancy and twin risk was basically identical. XGBoost outperformed the other two algorithms: logistic regression and classification and regression tree.

CONCLUSION

Artificial intelligence based on determinant-weighting analysis could offer an individualized embryo selection strategy for any given patient, and predict clinical pregnancy rate and twin risk, therefore optimizing clinical outcomes.

The optimal number of embryo cells for effective pregnancy and decrease of multiple pregnancy rate in frozen-thawed embryo transfer

To investigate the effect of the number of embryo cells on the clinical outcome of frozen-thawed embryo transfer and explore the optimal policy for decreases of multiple pregnancy rate, patients who experienced day 3 vitrified double frozen-thawed embryo transfer were retrospectively analyzed. According to the number of embryonic cells in each pre-frozen embryo, the patients were divided into six groups: 8C₂ (two 8-cell embryos), 8C₁- < 8C₁ (one 8-cell embryo and one under-8-cell embryo), 8C₁- > 8C₁ (one 8-cell embryo and one over-8-cell embryo), < 8C₂ (two under-8-cell embryos), < 8C₁- > 8C₁ (one under-8-cell embryo and one over-8-cell embryo), and > 8C₂ (two over-8-cell embryos). The clinical data were analyzed. The classification decision tree was used to analyze the optimal transfer strategy. A total of 2184 cycles of day 3 vitrified double frozen-thawed embryo transfer were enrolled. In day 3 double frozen-thawed embryo cycles, the 8C₂ group and 8C₁- > 8C₁ group had significantly (P < 0.05) higher pregnancy and multiple pregnancy rates than the other groups. No significant (P > 0.05) difference existed in the pregnancy rate and live birth rate between the 8C₁- < 8C₁ group, 8C₂ group and 8C₁- > 8C₁ group, but the implantation rate and multiple pregnancy rate in the 8C₁- < 8C₁ group were significantly (P < 0.05) lower than in the other two groups. Compared with the multiple pregnancy rate of all cycles, the cycles in two branches showed significantly (P < 0.05) higher multiple pregnancy rates (≤ 29 years old: 8C₂ / 8C₁- > 8C₁; 29 < age ≤ 36 years for the first transfer: 8C₂ / 8C₁- < 8C₁ / 8C₁- > 8C₁, one branch showed similar rate (≤ 29 years old: 8C₂ / 8C₁- > 8C₁) for the first transfer, and the remaining four branches demonstrated significantly (P < 0.05) lower rates. The clinical pregnancy rates before and after optimization were 51.0% vs 50.5%, and the multiple pregnancy rates were 38.5% vs 16.9%. In conclusion, the number of pre-frozen embryonic cells is an important factor affecting the clinical outcome of frozen-thawed embryo transfer in day 3 double good embryos frozen-thawed cycles. The age of patient, number of embryo cells, and the first time of transfer are the most valuable parameters for prediction. For women ≤ 29 years old, the single embryo transfer (SET) strategy was to choose an embryo ≥ 8 cells, and for women with < 29 age ≤ 36 years old, the SET strategy in the first transfer was to choose an embryo ≥ 8 cells.