Which factors are most predictive for live birth after in vitro fertilization and intracytoplasmic sperm injection (IVF/ICSI) treatments? Analysis of 100 prospectively recorded variables in 8,400 IVF/ICSI single-embryo transfers

Comparison of Time to Pregnancy in In Vitro Fertilisation between Endometriosis and Nonendometriosis

Background

This study is to compare the time to pregnancy (TTP) between patients with endometriosis and nonendometriosis undergoing in vitro fertilisation (IVF).Material and Methods.This is an observational retrospective cohort study. We included 291 patients (53 with endometriosis and 238 without endometriosis) achieving biochemical pregnancy, whether singleton or multifetal (serum beta-hCG >5 mIU/mL), between 1st January 2014 and 31st March 2020. We excluded patients with incomplete case notes and those declining participation. Time to pregnancy is the interval between the time when infertility was established to the date of confirmed biochemical pregnancy, expressed in months. Endometriosis diagnosis includes any form of endometriosis through surgical confirmation. A statistical analysis was done through the Mann-Whitney U test. Time to pregnancy was assessed through the Kaplan-Meier test. A p value <0.05 is considered statistically significant.

Results

Endometriosis patients had a shorter infertility duration (4 years vs. 5 years, p=0.024). Both groups had similar median age and body mass index at presentation. There was no significant difference in the TTP between endometriosis and nonendometriosis groups (57.7 vs. 70.9 months, p=0.060), further confirmed by a Cox regression test incorporating confounders (IVF protocol (OR: 1.482, 95% CI 0.667-3.292, and p=0.334) and type of the cycle (OR 1.071, 95% CI 0.803-1.430, and p=0.640)). The endometriosis group reached the maximum cumulative pregnancy rate at around 169 months postinfertility diagnosis, whilst the nonendometriosis group at around 255 months postinfertility diagnosis.

Conclusion

Time to pregnancy between endometriosis and nonendometriosis is not significantly different. However, infertility among patients with endometriosis tends to be shorter.

Angiogenic factor-driven improvement of refractory thin endometrium with autologous platelet-rich plasma intrauterine infusion in frozen embryo transfer cycles

Objective

A beneficial effect on endometrial thickness (EMT) and improvement of pregnancy outcome after intrauterine infusion of platelet-rich plasma (PRP) has been suggested. This study assessed the effect of intrauterine PRP infusion on live birth rate and obstetrical outcomes and analyzed cytokines that can potentially improve pregnancy outcomes through PRP.

Method

This study was a prospective cohort study conducted in a university hospital fertility center. The study included ninety-one patients who had a history of two or more failed in vitro fertilization (IVF) attempts and refractory thin endometrium that remained unresponsive after at least two conventional treatments for thin endometrium. Patients were treated with an intrauterine infusion of autologous PRP between days 7 and 14 of their hormone replacement therapy-frozen embryo transfer (HRT-FET) cycle. PRP was administered at 3-day intervals until their EMT reached 7mm. After a maximum of three PRP administrations, embryo transfer (ET) was performed. The primary outcome was the live birth rate. Secondary outcomes included the implantation rate and increase in EMT compared to the previous cycle. We compared the cytokines related to angiogenesis in a patient's whole blood (WB) and PRP by utilizing a commercial screening kit.

Results

The live birth rate in the PRP treatment cycle was 20.9% (19 of 91 patients), significantly superior to the previous cycle without PRP infusion (p < 0.001). The implantation rate was also significantly higher during the PRP treatment cycle (16.4%) compared to the previous cycle (3.1%) (p < 0.001). The mean EMT post-PRP treatment was 6.1 mm, showing a significant increase of 0.8 mm (p < 0.001). Nonetheless, an increase in EMT was also observed in the non-pregnancy group. No adverse effects were reported by patients treated with autologous PRP. Cytokine array analysis confirmed marked increases in well-known pro-angiogenic factors such as Ang-1, EGF, LAP (TGF-b1), MMP-8, PDGF-AA, and PDGF-AB/PDGF-BB.

Conclusion

Intrauterine PRP infusion offers a safe and effective treatment for patients with refractory thin endometrium and implantation failures. The angiogenic cytokines present in PRP are the primary drivers of this improvement.

Parabens effects on female reproductive health - Review of evidence from epidemiological and rodent-based studies

Parabens have been used as antimicrobial preservatives since the 1920s. The prevalent use of parabens increases their detection in the environment and in women's biological samples including reproductive tissues. Recent studies suggest parabens may alter endocrine function and thus female reproductive health may be affected. In this literature review, we summarize findings on parabens and female reproduction while focusing on epidemiological and rodent-based studies. The topics reviewed include paraben effects on cyclicity, pregnancy, newborn and pubertal development, reproductive hormones, and ovarian and uterine specific outcomes. Overall, the scientific literature on paraben effects on female reproduction is limited and with some conflicting results. Yet, some epidemiological and/or rodent-based experimental studies report significant findings in relation to paraben effects on cyclicity, fertility, gestation length, birth weight, postnatal development and pubertal onset, hormone levels, and hormone signaling in reproductive tissues. Future epidemiological and experimental studies are needed to better understand paraben effects on female reproduction while focusing on human related exposures including mixtures, physiologic concentrations of parabens, and multi-generational studies.

Does it affect the live birth rates to have a maximum endometrial thickness of 7, 8, or 9 mm in in-vitro fertilization-embryo transfer cycles?

OBJECTIVE

To assess the effect of endometrial thickness (EMT) on live birth rates (LBR) in women with endometrial lining between 7.0-9.9 mm.

METHODS

This retrospective cohort study included women who underwent fresh and frozen embryo transfers between 2008 and 2018, grouped according to their maximum EMT; group 1, 7.0-7.9 mm; group 2, 8.0-8.9 mm; and group 3, 9.0-9.9 mm and underwent blastocyst transfer.

RESULTS

The study included 7,091 in-vitro fertilization cycles: 1,385 in group 1, 3,000 in group 2, and 2,706 in group 3. The combined LBR was 22.2%. The mean age of women at oocyte retrieval day was 36.7±4.5 years. There was no difference in female age at oocyte retrieval or in the quality of embryos transferred between the three groups. Group 1 had more diagnoses of diminished ovarian reserve (25.8% vs. 19.5% and 19.1%; p<0.001) and less male factor infertility compared with group 2 and 3, respectively (25.0% vs. 28.8% and 28.5%; P=0.024). LBR was higher with increasing endometrial thickness, group 2 vs. group 1 (22.0% vs. 17.4%; P=0.0004), group 3 vs. group 1 (25.0% vs. 17.2%; p<0.001), and group 3 vs. group 2 (25.0% vs. 22.0%; P=0.008). After controlling for confounding factors, these three groups did not differ in LBR (group 1 vs. group 2, odds ratio [OR], 1.08; 95% confidence interval [CI], 0.83-1.4; P=0.54 and group 1 vs. group 3, OR, 1.16; 95% CI, 0.90-1.51; P=0.24).

CONCLUSION

Live birth rates in women with endometrial thickness between 7.0-9.9 mm were not affected by different cut-offs when blastocyst transfer was performed.

Predicting personalized cumulative live birth rate after a complete in vitro fertilization cycle: an analysis of 32,306 treatment cycles in China

BACKGROUND

The cumulative live birth rate (CLBR) has been regarded as a key measure of in vitro fertilization (IVF) success after a complete treatment cycle. Women undergoing IVF face great psychological pressure and financial burden. A predictive model to estimate CLBR is needed in clinical practice for patient counselling and shaping expectations.

METHODS

This retrospective study included 32,306 complete cycles derived from 29,023 couples undergoing IVF treatment from 2014 to 2020 at a university-affiliated fertility center in China. Three predictive models of CLBR were developed based on three phases of a complete cycle: pre-treatment, post-stimulation, and post-treatment. The non-linear relationship was treated with restricted cubic splines. Subjects from 2014 to 2018 were randomly divided into a training set and a test set at a ratio of 7:3 for model derivation and internal validation, while subjects from 2019 to 2020 were used for temporal validation.

RESULTS

Predictors of pre-treatment model included female age (non-linear relationship), antral follicle count (non-linear relationship), body mass index, number of previous IVF attempts, number of previous embryo transfer failure, type of infertility, tubal factor, male factor, and scarred uterus. Predictors of post-stimulation model included female age (non-linear relationship), number of oocytes retrieved (non-linear relationship), number of previous IVF attempts, number of previous embryo transfer failure, type of infertility, scarred uterus, stimulation protocol, as well as endometrial thickness, progesterone and luteinizing hormone on trigger day. Predictors of post-treatment model included female age (non-linear relationship), number of oocytes retrieved (non-linear relationship), cumulative Day-3 embryos live-birth capacity (non-linear relationship), number of previous IVF attempts, scarred uterus, stimulation protocol, as well as endometrial thickness, progesterone and luteinizing hormone on trigger day. The C index of the three models were 0.7559, 0.7744, and 0.8270, respectively. All models were well calibrated (p = 0.687, p = 0.468, p = 0.549). In internal validation, the C index of the three models were 0.7422, 0.7722, 0.8234, respectively; and the calibration P values were all greater than 0.05. In temporal validation, the C index were 0.7430, 0.7722, 0.8234 respectively; however, the calibration P values were less than 0.05.

CONCLUSIONS

This study provides three IVF models to predict CLBR according to information from different treatment stage, and these models have been converted into an online calculator ( https://h5.eheren.com/hcyc/pc/index.html#/home ). Internal validation and temporal validation verified the good discrimination of the predictive models. However, temporal validation suggested low accuracy of the predictive models, which might be attributed to time-associated amelioration of IVF practice.

Endometrial Elasticity is an Ultrasound Marker for Predicting Clinical Pregnancy Outcomes after Embryo Transfer

Endometrial elasticity is a potential new marker for assessing endometrial receptivity and pregnancy outcomes based on endometrial thickness and type. Currently, little research has been conducted on the elasticity of the endometrium using shear wave elasticity imaging (SWEI). This study aimed to explore whether endometrial elasticity is an ultrasound marker for predicting clinical pregnancy outcomes after embryo transfer. A total of 245 infertile women underwent ultrasonography before embryo transfer at the Peking University Third Hospital. We compared the endometrial elasticity and sub-endometrial blood flow rate using SWEI in the groups with different pregnancy outcomes. Trends in clinical pregnancy outcomes across the quartiles of endometrial elasticity in the fundus of the uterus (E1) were assessed. Logistic regression analysis was performed to obtain odds ratios for clinical pregnancy outcomes based on the quartiles of E1, with or without adjusting for potential confounding variables. Women in the clinical pregnancy group had higher E1 values and sub-endometrial blood flow rates in the uterine fundus than those in the non-pregnancy group. Women in the highest quartile of E1 had the most favorable clinical pregnancy rates. Endometrial elasticity measured using SWEI is a promising ultrasound marker for predicting clinical pregnancy outcomes after embryo transfer.

Predictors of success after in vitro fertilization

The last few decades have witnessed a rise in the global uptake of in vitro fertilization (IVF) treatment. To ensure optimal use of this technology, it is important for patients and clinicians to have access to tools that can provide accurate estimates of treatment success and understand the contribution of key clinical and laboratory parameters that influence the chance of conception after IVF treatment. The focus of this review was to identify key predictors of IVF treatment success and assess their impact in terms of live birth rates. We have identified 11 predictors that consistently feature in currently available prediction models, including age, duration of infertility, ethnicity, body mass index, antral follicle count, previous pregnancy history, cause of infertility, sperm parameters, number of oocytes collected, morphology of transferred embryos, and day of embryo transfer.

Safety evaluation of single-sperm cryopreservation technique applied in intracytoplasmic sperm injection

Intracytoplasmic sperm injection (ICSI) is a technique that directly injects a single sperm into the cytoplasm of mature oocytes. Here, we explored the safety of single-sperm cryopreservation applied in ICSI. This retrospective study enrolled 186 couples undergoing ICSI-assisted pregnancy. Subjects were allocated to the fresh sperm (group A)/single-sperm cryopreservation (group B) groups based on sperm type, with their clinical baseline/pathological data documented. We used ICSI-compliant sperm for subsequent in vitro fertilization and followed up on all subjects. The recovery rate/cryosurvival rate/sperm motility of both groups, the pregnancy/outcome of women receiving embryo transfer, and the delivery mode/neonatal-related information of women with successful deliveries were recorded. The clinical pregnancy rate, cumulative clinical pregnancy rate, abortion rate, ectopic pregnancy rate, premature delivery rate, live birth delivery rate, neonatal birth defect rate, and average birth weight were analyzed. The two groups showed no significant differences in age, body mass index, ovulation induction regimen, sex hormone [anti-Müllerian hormone (AMH)/follicle-stimulating hormone (FSH)/luteinizing hormone (LH)] levels, or oocyte retrieval cycles. The sperm recovery rate (51.72%-100.00%) and resuscitation rate (62.09% ± 16.67%) in group B were higher; the sperm motility in the two groups demonstrated no significant difference and met the ICSI requirements. Group B exhibited an increased fertilization rate, decreased abortion rate, and increased safety versus group A. Compared with fresh sperm, the application of single-sperm cryopreservation in ICSI sensibly improved the fertilization rate and reduced the abortion rate, showing higher safety.

A novel machine-learning framework based on early embryo morphokinetics identifies a feature signature associated with blastocyst development

BACKGROUND

Artificial Intelligence entails the application of computer algorithms to the huge and heterogeneous amount of morphodynamic data produced by Time-Lapse Technology. In this context, Machine Learning (ML) methods were developed in order to assist embryologists with automatized and objective predictive models able to standardize human embryo assessment. In this study, we aimed at developing a novel ML-based strategy to identify relevant patterns associated with the prediction of blastocyst development stage on day 5.

METHODS

We retrospectively analysed the morphokinetics of 575 embryos obtained from 80 women who underwent IVF at our Unit. Embryo morphokinetics was registered using the Geri plus® time-lapse system. Overall, 30 clinical, morphological and morphokinetic variables related to women and embryos were recorded and combined. Some embryos reached the expanded blastocyst stage on day 5 (BL Group, n = 210), some others did not (nBL Group, n = 365).

RESULTS

The novel EmbryoMLSelection framework was developed following four-steps: Feature Selection, Rules Extraction, Rules Selection and Rules Evaluation. Six rules composed by a combination of 8 variables were finally selected, and provided a predictive power described by an AUC of 0.84 and an accuracy of 81%.

CONCLUSIONS

We provided herein a new feature-signature able to identify with an high performance embryos with the best developmental competence to reach the expanded blastocyst stage on day 5. Clear and clinically relevant cut-offs were identified for each considered variable, providing an objective tool for early embryo developmental assessment.

The POPI-Plus tool: prediction model of outcome of pregnancy in in vitro fertilization from a large retrospective cohort

OBJECTIVE

To create a tool that accurately predicts live birth chances after a positive pregnancy test after elective single embryo transfer (ET).

DESIGN

Retrospective cohort.

SETTING

CHUM hospital and Ovo clinic in Montreal, Canada.

PATIENT(S)

Patients with a positive pregnancy test result who underwent their first single ET after in vitro fertilization (IVF) at the CHUM hospital and Ovo clinic in Montreal, Canada, from 2012 to 2016 were selected. A total of 1,995 patients were included in this study.

INTERVENTION(S)

The data from both centers were combined and divided into training (70%, n = 1,398) and validation (30%, n = 597) sets. The predictive model was developed using backward selection method for the following variables: age of patient at egg retrieval; log β-human chorionic gonadotropin (β-hCG) (β-hCG) 1; log β-hCG 2; and IVF treatment type. Moreover, the classification tree, random forest, and neural network models were generated.

MAIN OUTCOME MEASURE(S)

The measured outcomes were live birth (live fetus ≥24 weeks of gestation) and nonviable pregnancies. The performance of all models was evaluated by area under the receiver operating characteristic curve (AUC).

RESULT(S)

Advancing age was negatively correlated with live birth. The odds ratio (OR) of age of patient at the time of egg retrieval was 0.95 (95% confidence interval [CI], 0.91-0.99). The log β-hCG 1 and log β-hCG 2 were positively correlated with live birth in the univariate analysis (OR, 4.15 [95% CI, 3.19-5.39], and OR, 3.84 [95% CI, 2.99-4.93], respectively). The β-hCG 1 level needed for a successful pregnancy was lower in frozen ET and modified natural IVF than in simulated IVF (OR, 0.55 [95% CI, 0.34-0.91], and OR, 0.49 [95% CI, 0.26-0.95], respectively). The best performance in terms of the AUC was the updated logistic model: POPI-Plus. The AUC values were 0.76 (95% CI, 0.73-0.79) and 0.78 (95% CI, 0.74-0.82) for the training and validation data, respectively. The other models (classification tree, random forest, and neural network) also performed adequately, with an AUC of ≥0.7, but remained below POPI-Plus. An open-access calculator was generated and can be found on the website of the University of Montreal on the following link: https://deptobsgyn.umontreal.ca/departement/divisions/medecine-et-biologie-de-la-reproduction/the-popi-plus-tool/.

CONCLUSION(S)

The POPI-Plus tool offers individualized counseling for patients after an initial positive β-hCG test result. Future studies will assess its impact on patient anxiety while awaiting viability ultrasound and perform prospective validation on new patients.

Prediction of Reproductive Outcomes of Intracytoplasmic Sperm Injection Cycles Using a Multivariate Scoring System

Background

Prediction of in vitro fertilisation (IVF)/intracytoplasmic sperm injection (ICSI) success is crucial in counselling patients about their real chance of getting a live birth before commencing treatment. A multivariate scoring system proposed by Younis et al., 2010, was amongst the predictive models used to evaluate IVF/ICSI success. The score entitles basal endocrine, clinical and sonographic parameters.

Aims

The objective of this study is to assess the predictability of the Younis multivariate score for pregnancy outcomes in ICSI cycles.

Settings and Design

This prospective observational cohort study (NCT03846388) included patients who pursued IVF or ICSI in a tertiary infertility unit between February 2019 and December 2021.

Materials and Methods

The score variables were age, body mass index, antral follicle count, basal follicle-stimulating hormone (FSH), basal FSH/luteinising hormone ratio, infertility duration, number of previous cancellations and mean ovarian volume. For each woman included in the study, Younis multivariate score was calculated. Then, we correlate the different reproductive outcomes with score levels to validate the score predictability. A score of ≤14 was defined as a low score based on the previous study's results.

Statistical Analysis Used

The student's t-test and Mann-Whitney test were used to compare numerical variables, whereas categorical variables were analysed using the Chi-square test. A receiver operating curve (ROC) and a multivariate logistic regression model were used to investigate the predictability of the Younis scoring model for cycle outcomes.

Results

Two hundred ninety-two ICSI-ET cycles were analysed. Of the total cohort, 143 (48.97%) women included showed a low score (≤14), whereas 149 (51.03%) women showed a high score (>14). Women with low scores had significantly higher pregnancy and live birth rates compared to women with high scores (60.1% vs. 7.4%, respectively, P < 0.001; 44.7% vs. 6.7%, respectively, P < 0.001). The area under the curve (AUC) in the ROC curve analysis showed a higher predictability for the scoring system for live birth rate with an AUC of 0.796, with a sensitivity of 86.5% and specificity of 63.8% when using a cut-off level of ≤14. For pregnancy prediction, the AUC was 0.829, with a sensitivity of 88.66% and a specificity of 70.77% when using the same cut-off. Women who have a low score have a high chance of having frozen embryos. Likewise, women who have a high score have a very high chance of cycle cancellation.

Conclusions

The Younis multivariate score can be used for the prediction of ICSI cycle outcomes and to calculate the chance of cycle cancellation, pregnancy and take-home baby before ICSI.

Associations between Phthalate Metabolite Concentrations in Follicular Fluid and Reproductive Outcomes among Women Undergoing in Vitro Fertilization/Intracytoplasmic Sperm Injection Treatment

BACKGROUND

Phthalates have been reported to impair fertility in various studies. However, evidence exploring the associations between phthalate metabolites in follicular fluid (FF) and reproductive outcomes is lacking.

OBJECTIVES

To investigate the associations between phthalate metabolite concentrations in FF and in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) outcomes among women recruited from a fertility clinic.

METHODS

We included 641 women undergoing IVF/ICSI treatment from December 2018 to January 2020. The levels of eight phthalate metabolites, including monoethyl phthalate (MEP), mono-isobutyl phthalate (MiBP), mono-n -butyl phthalate (MBP), monobenzyl phthalate (MBzP), mono(2-ethylhexyl) phthalate (MEHP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono(2-ethyl-5-oxohexyl) phthalate (MEOHP), and mono(2-ethyl-5-carboxypentyl) phthalate (MECPP), were quantified in FF collected on the oocyte retrieval day. Associations between quartiles of individual phthalate metabolite concentrations and nine IVF/ICSI outcomes, including oocyte yield, mature oocyte number, two distinct pronuclei (2PN) zygote number, fertilization rate, blastocyst formation rate, implantation, clinical pregnancy, miscarriage, and live birth, were estimated with generalized linear models. The effects of phthalate mixtures on IVF/ICSI outcomes were assessed using Bayesian kernel machine regression (BKMR) models.

RESULTS

After adjusting for relevant confounders, elevated quartiles of MBzP, MEHHP, and MEHP in FF were inversely associated with the numbers of retrieved oocytes, mature oocytes, and 2PN zygotes (all p for trends < 0.10 ). In comparison with the lowest quartile, the highest quartile of molar sum of di(2-ethylhexyl) phthalate metabolites (Σ DEHP ) was associated with a reduction of 9.1% [95% confidence interval (CI): - 17.1 % , - 0.37 % ] and 10.3% (95% CI: - 18.8 % , - 0.94 % ) in yielded oocyte and mature oocyte numbers, respectively. Furthermore, the BKMR models revealed inverse associations between phthalate mixtures and the numbers of retrieved oocytes and mature oocytes. We generally found null results for implantation, clinical pregnancy, miscarriage, and live birth.

DISCUSSION

Certain phthalate metabolites in FF are inversely associated with the numbers of retrieved oocytes, mature oocytes, and 2PN zygotes among women undergoing IVF/ICSI treatment. https://doi.org/10.1289/EHP11998.

A critical appraisal of studies on endometrial thickness and embryo transfer outcome

A receptive endometrium is required for successful embryo implantation. Endometrial thickness, as measured by ultrasonography, is the most commonly used marker of endometrial receptivity in assisted reproductive technology cycles. Several factors simultaneously affect both endometrial thickness and probability of live birth, including age, oestradiol concentration and oocyte number, among others. Most of the studies investigating a relationship between endometrial thickness and embryo transfer outcomes are retrospective and do not adequately address confounding factors, in addition to other limitations. Despite multiple meta-analyses and studies with large numbers of cycles, controversy still exists. The difference between the results from prospective and retrospective studies is also striking. This article presents a critical appraisal of the studies on endometrial thickness and embryo transfer outcomes in order to highlight methodological issues and how they can be overcome in future studies. Currently available evidence does not seem to support a modification of management just because endometrial thickness is below an arbitrary threshold.

A combined clinical and specific genes' model to predict live birth for in vitro fertilization and embryo transfer patients

BACKGROUND

We aimed to develop an accurate model to predict live birth for patients receiving in vitro fertilization and embryo transfer (IVF-ET) treatment.

METHODS

This is a prospective nested case-control study. Women aged between 18 and 38 years, whose body mass index (BMI) were between the range of 18.5-24 kg/m2, who had an endometrium of ≥ 8 mm at the thickest were enrolled from 2018/9 to 2020/8. All patients received IVF-ET treatment and were followed up until Jan. 2022 when they had reproductive outcomes. Endometrial samples during the window of implantation (LH + 6 to 9 days) were subjected to analyze specific endometrial receptivity genes' expression using real-time PCR (RT-PCR). Patients were divided into live birth group and non-live birth group based on IVF-ET outcomes. Clinical signatures relevant to live birth were collected, analyzed, and used to establish a predictive model for live birth by univariate analysis (clinical model). Specific endometrial receptivity genes' expression was analyzed, selected, and used to construct a predictive model for live birth by The Least Absolute Shrinkage and Selection Operator (LASSO) analysis (gene model). Finally, significant clinical factors and genes were used to construct a combined model for predicting live birth using multivariate logistical regression (combined model). Different models' Area Under Curve (AUC) were compared to identify the most predictive model.

RESULTS

Thirty-nine patients were enrolled in the study, twenty-four patients had live births, fifteen did not. In univariate analysis, the odds of live birth for women with ovulation dysfunction was 4 times higher than that for women with other IVF-ET indications (OR = 4.0, 95% CI: 1.125 - 8.910, P = 0.018). Age, body mass index, duration of infertility, primary infertility, repeated implantation failure, antral follicle counting, ovarian sensitivity index, anti-Mullerian hormone, controlled ovarian hyperstimulation protocol and duration, total dose of FSH/hMG, number of oocytes retrieved, regiment of endometrial preparation, endometrium thickness before embryo transfer, type of embryo transferred were not associated with live birth (P > 0.05). Only ovulation dysfunction was used to construct the clinical model and its AUC was 0.688. In lasso analysis, GAST, GPX3, THBS2 were found to promote the risk of live birth. AUCs for GAST, GPX3, THBS2 reached to 0.736, 0.672, and 0.678, respectively. The gene model was established based on these three genes and its AUC was 0.772. Ovulation dysfunction, GAST, GPX3, and THBS2 were finally used to construct the combined model, reaching the highest AUC (AUC = 0.842).

CONCLUSIONS

Compared to the single model, the combined model of clinical (Ovulation dysfunction) and specific genes (GAST, GPX3, THBS2) was more accurate to predict live birth for IVF-ET patients.

Traditional Chinese medicine Dingkun pill to increase fertility in women with a thin endometrium-a prospective randomized study

Objective

The aim of this study is to optimize the treatment methods of infertility, which is suggested to be mainly caused by thin endometrium, using a special form of traditional Chinese medicine, the Dingkun pill (DKP), to increase the beneficial endometrial effect of conventional hormone/progestogen therapy.

Methods

A total of 307 patients visiting our specialized gynecological endocrinology department because of infertility, which we suggested to be caused by thin endometrium [endometrial thickness (EMT) < 7 mm], were randomly assigned to the experimental group and the control group. The experimental group was treated with estradiol + sequential dydrogesterone + DKP (every day); the control group received hormonal treatment without the Chinese medicine. All patients were monitored in terms of follicle diameter, EMT, and endometrial type every 2 days from the 8th to the 10th day of the menstrual cycle until ovulation day during three menstrual cycles. Serum progesterone levels on 7-8 days after ovulation were measured, and the cumulative pregnancy rate during three menstrual cycles between the two groups was compared.

Results

EMT on ovulation day in the experimental group was significantly higher than that in the control group (7.88 vs. 7.15 mm; p < 0.001). The proportion of type A and type B endometrium in total was significantly higher in the experimental group than that in the control group (83.2% vs. 77.7%; p < 0.05). Progesterone levels were significantly higher in the experimental group than those in the control group (10.874 vs. 10.074 ng/mL; p < 0.001). The cumulative pregnancy rate, the main outcome of the study, was significantly higher in the experimental group than that in the control group (29.2% vs. 15.7%; p < 0.05).

Conclusion

DKP added to conventional estrogen/progestogen therapy can significantly improve EMT and luteal function in patients attending due to infertility. Because this regimen increased the cumulative pregnancy rate in our study, we conclude that DKP can be used to increase the so-called "thin endometrium infertility".

Reproductive history does not compromise subsequent live birth and perinatal outcome following in-vitro fertilization: analysis of 25 329 first frozen-thawed embryo transfer cycles without preimplantation genetic testing for aneuploidy

OBJECTIVE

To investigate the effect of women's reproductive history on live-birth rate and perinatal outcome after first frozen-thawed embryo transfer (FET) without preimplantation genetic testing for aneuploidy.

METHODS

This was a retrospective cohort study of women who had undergone their first FET cycle between January 2014 and December 2020 at a university-affiliated fertility center. No transferred embryo underwent preimplantation genetic testing for aneuploidy. The women were categorized into five groups based on their reproductive history: no previous pregnancy; previous termination of pregnancy (TOP); previous pregnancy loss; previous ectopic pregnancy (EP); and previous live birth. The women with no previous pregnancy were considered as the reference group. The primary outcome was the live-birth rate and secondary endpoints included rates of positive pregnancy test, clinical pregnancy, pregnancy loss and EP as well as perinatal outcomes such as birth weight and preterm birth. Multivariable logistic regression analyses were used to control for a number of potential confounders, including age, body mass index, education level, duration and cause of infertility, insemination method, type of endometrial preparation, number of embryos transferred, embryo developmental stage, quality of the embryos transferred, year of treatment and endometrial thickness. Additionally, propensity score matching (PSM) was used to check the robustness of the main findings.

RESULTS

In total, 25 329 women were included in the final analysis. On univariate analysis, each reproductive-history type except for previous EP was significantly associated with worse pregnancy outcome following in-vitro fertilization (IVF), including rates of positive pregnancy test, clinical pregnancy, pregnancy loss and live birth, when compared with the group of women with no previous pregnancy. However, after correcting for several potential confounders, the differences in rates of live birth, pregnancy loss, positive pregnancy test and clinical pregnancy were no longer significant between the study and control groups on multivariable regression models, while the risk of EP after embryo transfer was elevated among women with a previous TOP or EP. There was no increased risk of adverse perinatal outcome associated with reproductive history compared with the control group. Notably, similar results were obtained from the PSM models, confirming the robustness of the main findings.

CONCLUSION

Relative to women without a previous pregnancy, those with a prior TOP, pregnancy loss, EP or live birth did not have compromised live-birth rate or perinatal outcomes following FET without preimplantation genetic testing for aneuploidy, with the exception of an increased risk of EP in those with prior TOP or EP. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

AI-Based Optimal Treatment Strategy Selection for Female Infertility for First and Subsequent IVF-ET Cycles

Over the last 20 years, China's infertility rate has risen from 3% to 12.5%-15%. Infertility has become the third largest disease following cancer and cardiovascular disease. Then, the in vitro fertilization and embryo transfer (IVF-ET) becomes more and more important in infertility treatment field. However, the reported success rate for IVT-ET is 30%-40% and costs are gradually rising. Meanwhile, to increase success rates and decrease costs, the optimal selection of the IVF-ET treatment strategy is crucial. In a clinical work, the IVF-ET treatment strategy selection is always based on the experience of the doctor without a uniform standard. To solve this important and complex problem, we proposed an artificial intelligence (AI)-based optimal treatment strategy selection system to extract implicit knowledge from clinical data for new and returning patients, by mimicking the IVF-ET process and analysing a myriad of treatment decisions. We demonstrated that the performance of the model was different in 10 AI classification algorithms. Hence, we need to select the optimal method for predicting patient pregnancy result in different IVF-ET treatment strategies. Moreover, feature ranking is determined in the proposed model to measure the importance of each patient characteristics. Therefore, better advice can be provided for individual patient characteristics, doctors can provide more valid suggestions regarding certain patient characteristics to improve the accuracy of diagnosis and efficiency.

Treatment options for endometrial hypoproliferation

PURPOSE OF REVIEW

Endometrial hypoproliferation refers to the failure of the endometrium to reach optimal thickness during fresh or frozen embryo transfer cycles in women undergoing infertility treatment with in-vitro fertilization (IVF). This review discusses the treatment options for endometrial hypoproliferation.

RECENT FINDINGS

Apart from factors related to the embryo quality, ultrasonographic findings associated with the endometrium, such as endometrial thickness, endometrial pattern and subendometrial blood flow, are considered key factors associated with the outcome of assisted reproductive treatment. To date, a consensus has not been reached regarding the definition of thin endometrium, while thresholds of 6, 7 or 8 mm have been used in the literature. Strategies to increase endometrial thickness can be reviewed in three groups: endocrine approaches, vitamins & supplements, and new experimental therapeutic interventions. Some of the recently introduced experimental therapeutic interventions such as platelet-rich plasma injection, stem cell treatment and tissue bioengineering are exciting potential therapies that need to be further studied.

SUMMARY

Despite a large number of publications on the topic, diagnosing and treating endometrial hypoproliferation remains a challenge. Well designed studies are needed to establish a widely accepted endometrial thickness cut-off value below which endometrial hypoproliferation is diagnosed and to generate meaningful data that would allow an evidence-based discussion of available therapeutic options with patients.

Nomogram for Predicting Live Birth after the First Fresh Embryo Transfer in Patients with PCOS Undergoing IVF/ICSI Treatment with the GnRH-Ant Protocol

Polycystic ovary syndrome (PCOS) is the leading cause of anovulatory infertility. A better understanding of factors associated with pregnancy outcomes and successful prediction of live birth after IVF/ICSI are important to guide clinical practice. This was a retrospective cohort study investigating live birth after the first fresh embryo transfer using the GnRH-ant protocol in patients with PCOS between 2017 and 2021 at the Reproductive Center of Peking University Third Hospital. A total of 1018 patients with PCOS were qualified for inclusion in this study. BMI, AMH level, initial FSH dosage, serum LH and progesterone levels on the hCG trigger day, and endometrial thickness were all independent predictors of live birth. However, age and infertility duration were not significant predictors. We developed a prediction model based on these variables. The predictive ability of the model was demonstrated well, with areas under the curve of 0.711 (95% CI, 0.672-0.751) and 0.713 (95% CI, 0.650-0.776) in the training cohort and validation cohort, respectively. Additionally, the calibration plot showed good agreement between the prediction and the observation (p = 0.270). The novel nomogram could be helpful for clinicians and patients in clinical decision-making and outcome evaluation.

Predicted probabilities of live birth following assisted reproductive technology using United States national surveillance data from 2016 to 2018

BACKGROUND

As the use of in vitro fertilization continues to increase in the United States, up-to-date models that estimate cumulative live birth rates after multiple oocyte retrievals and embryo transfers (fresh and frozen) are valuable for patients and clinicians weighing treatment options.

OBJECTIVE

This study aimed to develop models that generate predicted probabilities of live birth in individuals considering in vitro fertilization based on demographic and reproductive characteristics.

STUDY DESIGN

Our population-based cohort study used data from the National Assisted Reproductive Technology Surveillance System 2016 to 2018, including 196,916 women who underwent 207,766 autologous embryo transfer cycles and 25,831 women who underwent 36,909 donor oocyte transfer cycles. We used data on autologous in vitro fertilization cycles to develop models that estimate a patient's cumulative live birth rate after all embryo transfers (fresh and frozen) within 12 months after 1, 2, and 3 oocyte retrievals in new and returning patients. Among patients using donor oocytes, we estimated the cumulative live birth rate after their first, second, and third embryo transfers. Multinomial logistic regression models adjusted for age, prepregnancy body mass index (imputed for 18% of missing values), parity, gravidity, and infertility diagnoses were used to estimate the cumulative live birth rate.

RESULTS

Among new and returning patients undergoing autologous in vitro fertilization, female age had the strongest association with cumulative live birth rate. Other factors associated with higher cumulative live birth rates were lower body mass index and parity or gravidity ≥1, although results were inconsistent. Infertility diagnoses of diminished ovarian reserve, uterine factor, and other reasons were associated with a lower cumulative live birth rate, whereas male factor, tubal factor, ovulatory disorders, and unexplained infertility were associated with a higher cumulative live birth rate. Based on our models, a new patient who is 35 years old, with a body mass index of 25 kg/m2, no previous pregnancy, and unexplained infertility diagnoses, has a 48%, 69%, and 80% cumulative live birth rate after the first, second, and third oocyte retrieval, respectively. Cumulative live birth rates are 29%, 48%, and 62%, respectively, if the patient had diminished ovarian reserve, and 25%, 41%, and 52%, respectively, if the patient was 40 years old (with unexplained infertility). Very few recipient characteristics were associated with cumulative live birth rate in donor oocyte patients.

CONCLUSION

Our models provided estimates of cumulative live birth rate based on demographic and reproductive characteristics to help inform patients and providers of a woman's probability of success after in vitro fertilization.

Impact of Insulin Resistance on Ovarian Sensitivity and Pregnancy Outcomes in Patients with Polycystic Ovary Syndrome Undergoing IVF

BACKGROUND

Ovarian sensitivity index (OSI) is an accurate index to reflect the ovarian sensitivity to exogenous gonadotropins in in vitro fertilization (IVF). How insulin resistance (IR) affects OSI and pregnancy outcomes during IVF remains unclear.

METHODS

This was a large retrospective, cohort study. A total of 2055 women with polycystic ovary syndrome (PCOS) undergoing the first fresh IVF cycle were enrolled. They were grouped into terciles based on the homeostasis model assessment of insulin resistance (HOMA-IR) values as control, medium and IR group for comparison. Multivariate regression analysis was also conducted.

RESULTS

HOMA-IR had a significantly negative impact on OSI (adjusted β = -0.24; 95% CI, -0.35 to -0.13), especially in lean patients with an adjusted β of -0.33 (95% CI, -0.51 to -0.16). The interaction analysis revealed an interactive association between HOMA-IR and body mass index (BMI) (p = 0.017). IR was related to an increased early miscarriage risk independently with an odds ratio (OR) of 2.21 (95% CI, 1.13 to 4.33), without significant impact on pregnancy and live birth rate.

CONCLUSION

IR decreased the ovarian response in PCOS patients undergoing IVF, especially in the lean subgroup. IR may result in a higher risk of early miscarriage, but did not impair pregnancy and live birth rate.

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.

Hormone replacement therapy alone or in combination with tamoxifen in women with thin endometrium undergoing frozen-thawed embryo transfer: A retrospective study

RESEARCH QUESTION

To investigate the effects of two protocols (hormone replacement therapy (HRT) alone or in combination with tamoxifen) on the endometrium and pregnancy outcome of patients with thin endometrium in frozen-thawed embryo transfer (FET) cycles.

DESIGN

A total of 465 infertile patients with thin endometrium who underwent FET between January 2020 to June 2021 at the Drum Tower Hospital affiliated with Nanjing University Medical School were retrospectively analyzed. A total of 187 patients were given tamoxifen in addition to HRT (TMXF-HRT group), whereas 278 patients were given only HRT (HRT group). Clinical data were compared between the two groups, including general characteristics, endometrial thickness, and clinical pregnancy outcomes.

RESULTS

There were no significant differences in baseline characteristics of all enrolled patients between two groups. Serum progesterone (P) was higher in HRT group than in the TMXF-HRT group (0.28 ± 0.53 ng/mL vs. 0.15 ± 0.25 ng/mL, P = 0.002). There was a significant increase in endometrial thickness in the TMXF-HRT group compared with the HRT group (OR: 1.54, 95% CI: 1.32-1.75, P < 0.001). There were no significant differences in the clinical pregnancy rate, embryo implantation rate, early miscarriage rate, or live birth rate between these two groups.

CONCLUSION

Although tamoxifen when used in combination with hormone replacement therapy can significantly increase endometrial thickness, it may not have a role in improving the pregnancy outcomes of patients with thin endometrium undergoing FET cycles.

Clinical pregnancy outcomes prediction in vitro fertilization women based on random forest prediction model: A nested case-control study

The present study aimed to analyze the risk factors influencing the in vitro fertilization embryo transfer (IVF-ET) pregnancy and to construct a prediction model for clinical pregnancy outcome in patients receiving IVF-ET based on the predictors. In this nested case-control study, the data of 369 women receiving IVF-ET were enrolled. Univariate and multivariate Logistic regression analyses were conducted to identify the potential predictors. Ten-fold cross validation method was used to validate the random forest model for predicting the clinical pregnancy. The receiver operating characteristic curve was drawn to evaluate the prediction ability of the model. The importance of variables was shown according to Mean Decrease Gini. The data delineated that age (odds ratio [OR]= 1.093, 95% confidence interval [CI]: 1.036-1.156, P = .0010), body mass index (BMI) (OR = 1.094, 95%CI: 1.021-1.176, P = .012), 3 cycles (OR = 0.144, 95%CI: 0.028-0.534, P = .008), hematocrit (HCT) (OR = 0.865, 95% CI: 0.791-0.943, P = .001), luteinizing hormone (LH) (OR = 0.678, 95%CI: 0.549-0.823, P < .001), progesterone (P) (OR = 2.126, 95%CI: 1.112-4.141, P = .024), endometrial thickness (OR = 0.132, 95%CI: 0.034-0.496, P = .003) and FSH (OR = 1.151, 95%CI: 1.043-1.275, P = .006) were predictors associated with the clinical pregnancy outcome of patients receiving IVF-ET. The results might provide a novel method to identify patients receiving IVF-ET with a high risk of poor pregnancy outcomes and provide interventions in those patients to prevent the occurrence of poor pregnancy outcomes.

The Future Is Coming: Artificial Intelligence in the Treatment of Infertility Could Improve Assisted Reproduction Outcomes-The Value of Regulatory Frameworks

Infertility is a global health issue affecting women and men of reproductive age with increasing incidence worldwide, in part due to greater awareness and better diagnosis. Assisted reproduction technologies (ART) are considered the ultimate step in the treatment of infertility. Recently, artificial intelligence (AI) has been progressively used in the many fields of medicine, integrating knowledge and computer science through machine learning algorithms. AI has the potential to improve infertility diagnosis and ART outcomes estimated as pregnancy and/or live birth rate, especially with recurrent ART failure. A broad-ranging review has been conducted, focusing on clinical AI applications up until September 2022, which could be estimated in terms of possible applications, such as ultrasound monitoring of folliculogenesis, endometrial receptivity, embryo selection based on quality and viability, and prediction of post implantation embryo development, in order to eliminate potential contributing risk factors. Oocyte morphology assessment is highly relevant in terms of successful fertilization rate, as well as during oocyte freezing for fertility preservation, and substantially valuable in oocyte donation cycles. AI has great implications in the assessment of male infertility, with computerised semen analysis systems already in use and a broad spectrum of possible AI-based applications in environmental and lifestyle evaluation to predict semen quality. In addition, considerable progress has been made in terms of harnessing AI in cases of idiopathic infertility, to improve the stratification of infertile/fertile couples based on their biological and clinical signatures. With AI as a very powerful tool of the future, our review is meant to summarise current AI applications and investigations in contemporary reproduction medicine, mainly focusing on the nonsurgical aspects of it; in addition, the authors have briefly explored the frames of reference and guiding principles for the definition and implementation of legal, regulatory, and ethical standards for AI in healthcare.

Nomogram prediction for the prediction of clinical pregnancy in Freeze-thawed Embryo Transfer

BACKGROUND

This study aimed to identify multiple endometrial receptivity related factors by applying non-invasive, repeatable multimodal ultrasound methods. Combined with basic clinical data, we further established a practical prediction model for early clinical outcomes in Freeze-thawed Embryo Transfer (FET).

METHODS

Retrospective analysis of clinical data of infertility patients undergoing FET cycle in our Center from January 2017 to September 2019. Receiver operating characteristic (ROC) curve and decision curve analyses were performed by 500 bootstrap resamplings to assess the determination and clinical value of the nomogram, respectively.

RESULTS

A total of 2457 FET cycles were included. We developed simple nomograms that predict the early clinical outcomes in FET cycles by using the parameters of age, BMI, type and number of embryos transferred, endometrial thickness, FI, RI, PI and number of endometrial and sub-endometrial blood flow. In the training cohort, the area under the ROC curve (AUC) showed statistical accuracy (AUC = 0.698), and similar results were shown in the subsequent validation cohort (AUC = 0.699). Decision curve analysis demonstrated the clinical value of this nomogram.

CONCLUSIONS

Our nomogram can predict clinical outcomes and it can be used as a simple, affordable and widely implementable tool to provide guidance and treatment recommendations for FET patients.

Adaptive data-driven models to best predict the likelihood of live birth as the IVF cycle moves on and for each embryo transfer

PURPOSE

To dynamically assess the evolution of live birth predictive factors' impact throughout the in vitro fertilization (IVF) process, for each fresh and subsequent frozen embryo transfers.

METHODS

In this multicentric study, data from 13,574 fresh IVF cycles and 6,770 subsequent frozen embryo transfers were retrospectively analyzed. Fifty-seven descriptive parameters were included and split into four categories: (1) demographic (couple's baseline characteristics), (2) ovarian stimulation, (3) laboratory data, and (4) embryo transfer (fresh and frozen). All these parameters were used to develop four successive predictive models with the outcome being a live birth event.

RESULTS

Eight parameters were predictive of live birth in the first step after the first consultation, 9 in the second step after the stimulation, 11 in the third step with laboratory data, and 13 in the 4th step at the transfer stage. The predictive performance of the models increased at each step. Certain parameters remained predictive in all 4 models while others were predictive only in the first models and no longer in the subsequent ones when including new parameters. Moreover, some parameters were predictive in fresh transfers but not in frozen transfers.

CONCLUSION

This work evaluates the chances of live birth for each embryo transfer individually and not the cumulative outcome after multiple IVF attempts. The different predictive models allow to determine which parameters should be taken into account or not at each step of an IVF cycle, and especially at the time of each embryo transfer, fresh or frozen.

Predicting clinical pregnancy using clinical features and machine learning algorithms in in vitro fertilization

INTRODUCTION

Assisted reproductive technology has been proposed for women with infertility. Moreover, in vitro fertilization (IVF) cycles are increasing. Factors contributing to successful pregnancy have been widely explored. In this study, we used machine learning algorithms to construct prediction models for clinical pregnancies in IVF.

MATERIALS AND METHODS

A total of 24,730 patients entered IVF and intracytoplasmic sperm injection cycles with clinical pregnancy outcomes at Taipei Medical University Hospital. Data used included patient characteristics and treatment. We used machine learning methods to develop prediction models for clinical pregnancy and explored how each variable affects the outcome of interest using partial dependence plots.

RESULTS

Experimental results showed that the random forest algorithm outperforms logistic regression in terms of areas under the receiver operating characteristics curve. The ovarian stimulation protocol is the most important factor affecting pregnancy outcomes. Long and ultra-long protocols have shown positive effects on clinical pregnancy among all protocols. Furthermore, total frozen and transferred embryos are positive for a clinical pregnancy, but female age and duration of infertility have negative effects on clinical pregnancy.

CONCLUSION

Our findings show the importance of variables and propensity of each variable by random forest algorithm for clinical pregnancy in the assisted reproductive technology cycle. This study provides a ranking of variables affecting clinical pregnancy and explores the effects of each treatment on successful pregnancy. Our study has the potential to help clinicians evaluate the success of IVF in patients.

Predicting the probability of a live birth after a freeze-all based in vitro fertilization-embryo transfer (IVF-ET) treatment strategy

BACKGROUND

The predictors for live birth rate (LBR) following one episode of in vitro fertilization (IVF) cycle for patients using a "freeze-all" strategy are not entirely clear.

METHODS

A retrospective cohort study utilizing a prediction model was developed to assess the relationship to the LBR. Women undergoing IVF with a freeze-all strategy were screened. Univariate models were first fitted for female age at oocytes retrieval/frozen-thawed embryo transfer (FET), body mass index (BMI), duration and etiology of infertility, previous IVF failures, total dose and duration of gonadotrophin, ovarian sensitivity index (OSI), number of oocytes collected, method of fertilization, number of embryos created, number and stage of embryos frozen, type and number of FET cycles, endometrial thickness (EMT)/pattern, hormone level on transplantation day, storage duration, number of embryos thawed and damaged thawed embryos, number and stage of embryos transferred and number of different quality embryos transferred. Variables with P<0.05 in the univariate model were selected for further analysis of the final multivariate discrete-time logistic regression model.

RESULTS

A total of 7,602 women undergoing one ovarian stimulation resulted in 9,964 FETs, of whom 3,066 (40.33%) had a live-birth after their first FET and 3,929 (51.68%) after total FETs. The EMT and woman's age at oocyte retrieval were the most important predictors. In the first FET, the LBR of women with an EMT ≤8 mm [27.40%; 95% confidence interval (CI): (21.60-33.81%)] was significantly lower than that of women with EMT between 9 and 11 mm [36.51%; 95% CI: (34.25-38.81%)] and thicker than 12 mm [44.23%; 95% CI: (42.22-46.25%)] (P<0.05). The optimistic and conservative cumulative LBRs of women younger than 31 years [87.5%; 95% CI: (86.32-88.61%) and 63.04%; 95% CI: (61.36-64.69%)] were significantly decreased in women aged 31-35, 36-40 and >40 (P<0.001).

CONCLUSIONS

Our study provides an effective prediction model for a woman's chance of having a baby after a "freeze-all" policy. The use of EMT and female age as tools to identify LBR are shown to be justified, and repeated FETs cannot reverse the age-dependent decline in fertility.

Machine Learning Approach to Predict Clinical Pregnancy Potential in Women Undergoing IVF Program

Objective: Hidden knowledge could be discovered within a large practical data of in vitro fertilization (IVF) practice. In this study, Machine learning-based data mining techniques were utilized to construct a reliable prediction model for clinical pregnancy in IVF.

Study Design: A retrospective cohort multicenter study involving 4.570 IVF cycles. All patients underwent fresh embryo transfer at either the cleavage or blastocyst stage between January 2015 and December 2019. The experiment focused on utilizing tree-based classifiers to generate and compare the most effective prediction model that could predict a clinical pregnancy through clinical data. Additionally, each classifier is optimized via a genetic algorithm technique, along with the selection of variables.

Results: Both the decision tree and random forest showed similar performance that was much better than the gradient boost. The two superior classifiers achieved a balanced accuracy of roughly 0.62. Additionally, each prediction model was shown to work optimally with different combinations of variables, with some variables being consistently included, such as female age, and some consistently excluded, which provides an insight into the relationship between the variables and each prediction model.

Conclusion: Machine learning algorithm remains effective for the purpose of data mining and knowledge extraction in IVF clinical datasets through which a relatively reliable prediction system for clinical pregnancy could be constructed, provided the available data is sufficient.

Follicular fluid and blood levels of persistent organic pollutants and reproductive outcomes among women undergoing assisted reproductive technologies

Persistent organic pollutants (POPs) are industrial chemicals resistant to degradation and have been shown to have adverse effects on reproductive health in wildlife and humans. Although regulations have reduced their levels, they are still ubiquitously present and pose a global concern. Here, we studied a cohort of 185 women aged 21-43 years with a median of 2 years of infertility who were seeking assisted reproductive technology (ART) treatment at the Carl von Linné Clinic in Uppsala, Sweden. We analyzed the levels of 9 organochlorine pesticides (OCPs), 10 polychlorinated biphenyls (PCBs), 3 polybrominated diphenyl ethers (PBDEs), and 8 perfluoroalkyl substances (PFASs) in the blood and follicular fluid (FF) samples collected during ovum pick-up. Impact of age on chemical transfer from blood to FF was analyzed. Associations of chemicals, both individually and as a mixture, to 10 ART endpoints were investigated using linear, logistic, and weighted quantile sum regression, adjusted for age, body mass index, parity, fatty fish intake and cause of infertility. Out of the 30 chemicals, 20 were detected in more than half of the blood samples and 15 in FF. Chemical transfer from blood to FF increased with age. Chemical groups in blood crossed the blood-follicle barrier at different rates: OCPs > PCBs > PFASs. Hexachlorobenzene, an OCP, was associated with lower anti-Müllerian hormone, clinical pregnancy, and live birth. PCBs and PFASs were associated with higher antral follicle count and ovarian response as measured by ovarian sensitivity index, but also with lower embryo quality. As a mixture, similar findings were seen for the sum of PCBs and PFASs. Our results suggest that age plays a role in the chemical transfer from blood to FF and that exposure to POPs significantly associates with ART outcomes. We strongly encourage further studies to elucidate the underlying mechanisms of reproductive effects of POPs in humans.

The Role of Endometrial Stem/Progenitor Cells in Recurrent Reproductive Failure

Recurrent implantation failure (RIF) and recurrent pregnancy loss (RPL), collectively referred to as recurrent reproductive failure (RRF), are both challenging conditions with many unanswered questions relating to causes and management options. Both conditions are proposed to be related to an aberrant endometrial microenvironment, with different proposed aetiologies related to a restrictive or permissive endometrium for an invading embryo. The impressive regenerative capacity of the human endometrium has been well-established and has led to the isolation and characterisation of several subtypes of endometrial stem/progenitor cells (eSPCs). eSPCs are known to be involved in the pathogenesis of endometrium-related disorders (such as endometriosis) and have been proposed to be implicated in the pathogenesis of RRF. This review appraises the current knowledge of eSPCs, and their involvement in RRF, highlighting the considerable unknown aspects in this field, and providing avenues for future research to facilitate much-needed advances in the diagnosis and management of millions of women suffering with RRF.

Internal validation and comparison of predictive models to determine success rate of infertility treatments: a retrospective study of 2485 cycles

Infertility is a significant health problem and assisted reproductive technologies to treat infertility. Despite all efforts, the success rate of these methods is still low. Also, each of these methods has side effects and costs. Therefore, accurate prediction of treatment success rate is a clinical challenge. This retrospective study aimed to internally validate and compare various machine learning models for predicting the clinical pregnancy rate (CPR) of infertility treatment. For this purpose, data from 1931 patients consisting of in vitro fertilization (IVF) or intra cytoplasmic sperm injection (ICSI) (733) and intra uterine insemination (IUI) (1196) treatments were included. Also, no egg or sperm donation data were used. The performance of machine learning algorithms to predict clinical pregnancy were expressed in terms of accuracy, recall, F-score, positive predictive value (PPV), brier score (BS), Matthew correlation coefficient (MCC), and receiver operating characteristic. The significance of the features with CPR and AUCs was evaluated by Student's t test and DeLong’s algorithm. Random forest (RF) model had the highest accuracy in the IVF/ICSI treatment. The sensitivity, F1 score, PPV, and MCC of the RF model were 0.76, 0.73, 0.80, and 0.5, respectively. These values for IUI treatment were 0.84, 0.80, 0.82, and 0.34, respectively. The BS was 0.13 and 0.15 for IVF/ICS and IUI, respectively. In addition, the estimated AUCs of the RF model for IVF/ICS and IUI were 0.73 and 0.7, respectively. Some essential features were obtained based on RF ranking for the two datasets, including age, follicle stimulation hormone, endometrial thickness, and infertility duration. The results showed a strong relationship between clinical pregnancy and a woman's age. Also, endometrial thickness and the number of follicles decreased with increasing female age in both treatments.

Influence of Maternal Age on the Relationship Between Endometrial Thickness and Ongoing Pregnancy Rates in Frozen-Thawed Embryo Transfer Cycles: A Retrospective Analysis of 2,562 Cycles

Background

In frozen-thawed embryo transfer (FET) cycles, endometrial thickness (EMT) has been used routinely as the main clinical monitoring index. However, the current findings are conflicting.

Method

This was a single-center retrospective study of 2,054 couples (2,562 cycles) who underwent FET (including cleavage stage embryos and blastocysts) between January 2017 and August 2020 in the reproductive centers of First Affiliated Hospital of Xinjiang Medical University. The primary outcome measure was the ongoing pregnancy rate (OPR); the secondary outcome was the clinical pregnancy rate.

Results

After stratified analysis and adjusting for confounders such as maternal age, duration of infertility, number of high-quality embryos transferred, endometrial preparation protocol, number of transfer cycles, and stages of embryo transferred, we found a curvilinear relationship between EMT and the OPR in women < 35 years of age. For women with EMT ≤ 8 mm, the OPR increased by 150% for cleavage stage embryo transfer for every 1 mm increase in the EMT; similarly, it increased by 97% for blastocyst stage FET. However, there was a linear relationship between EMT and OPR in women aged ≥ 35 years. When blastocysts were transferred, for every 1 mm increase in the EMT the OPR increased significantly by 12%. But OPR after frozen-thawed cleavage stage embryos transfer did not increase significantly with increased EMT.

Conclusions

Our study showed that the OPR increased significantly with increased EMT between young women aged < 35 years with EMT ≤ 8 mm and older women who underwent transfer of blastocysts.

Efficacy and safety of autologous adipose tissue-derived stromal vascular fraction in patients with thin endometrium: a protocol for a single-centre, longitudinal, prospective self-control study

INTRODUCTION

Endometrial thickness is an important parameter to evaluate endometrial receptivity. An appropriate endometrial thickness is necessary for both embryo implantation and maintaining normal pregnancy. Women with thin endometrium are one of the critical challenges in the clinic, and current therapeutic strategies for thin endometrium remain suboptimal. The stromal vascular fraction (SVF) derived from adipose tissue contains a variety of cells, mainly adipose-derived stem/stromal cells and adipose cells. Recently, adipose tissue-derived SVF showed tremendous potential for treating thin endometrium due to its capacity to repair and regenerate tissues. The application of SVF in animal models for treating thin endometrium has been investigated. However, limited evidence has demonstrated the efficacy and safety of autologous SVF in patients with thin endometrium.

METHODS AND ANALYSIS

This study is a single-centre, longitudinal, prospective self-control study to investigate the preliminary efficacy and safety of autologous SVF in improving the pregnancy outcome of infertile patients with thin endometrium. Thirty patients diagnosed with thin endometrium will be recruited based on the inclusion and exclusion criteria. The SVF suspension will be transferred into the uterine cavity via an embryo transfer catheter. Then, comparisons between pretreatment and post-treatment will be analysed, and the outcomes, including endometrial thickness, menstrual volume and duration, frequency and severity of adverse events and early pregnancy outcomes, will be measured within a 3-month follow-up, while late pregnancy outcomes and their offspring will be followed up via telephone for 2 years. The proportion of patients with improved symptoms will be calculated and compared.

ETHICS AND DISSEMINATION

This study was approved by the Ethics Committee of Peking University Third Hospital (reference number: REC2020-165). Written informed consent will be provided for patients before being included. The results will be presented at academic conferences and a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

ChiCTR2000035126.

Single-cell transcriptome analysis uncovers the molecular and cellular characteristics of thin endometrium

Infertility is a social and medical problem around the world and the incidence continues to rise. Thin endometrium (TE) is a great challenge of infertility treatment, even by in vitro fertilization and embryo transfer. It is widely believed that TE impairs endometrium receptivity. However, only a few studies have explained the molecular mechanism. Herein, in order to reveal the possible mechanism, we sampled endometrium from a TE patient and a control volunteer and got a transcriptomic atlas of 18 775 individual cells which was constructed using single-cell RNA sequencing, and seven cell types have been identified. The cells were acquired during proliferative and secretory phases, respectively. The proportion of epithelial cells and stromal cells showed a significant difference between the TE group and the control group. In addition, differential expressed genes (DEGs) in diverse cell types were revealed, the enriched pathways of DEGs were found closely related to the protein synthesis in TE of both proliferative and secretory phases. Some DEGs can influence cell-type ratio and impaired endometrial receptivity in TE. Furthermore, divergent expression of estrogen receptors 1 and progesterone receptors in stromal and epithelial cells were compared in the TE sample from the control. The cellular and molecular heterogeneity found in this study provided valuable information for disclosing the mechanisms of impaired receptivity in TE.

Informative predictors of pregnancy after first IVF cycle using eIVF practice highway electronic health records

The aim of this study is to determine the most informative pre- and in-cycle variables for predicting success for a first autologous oocyte in-vitro fertilization (IVF) cycle. This is a retrospective study using 22,413 first autologous oocyte IVF cycles from 2001 to 2018. Models were developed to predict pregnancy following an IVF cycle with a fresh embryo transfer. The importance of each variable was determined by its coefficient in a logistic regression model and the prediction accuracy based on different variable sets was reported. The area under the receiver operating characteristic curve (AUC) on a validation patient cohort was the metric for prediction accuracy. Three factors were found to be of importance when predicting IVF success: age in three groups (38-40, 41-42, and above 42 years old), number of transferred embryos, and number of cryopreserved embryos. For predicting first-cycle IVF pregnancy using all available variables, the predictive model achieved an AUC of 68% + /- 0.01%. A parsimonious predictive model utilizing age (38-40, 41-42, and above 42 years old), number of transferred embryos, and number of cryopreserved embryos achieved an AUC of 65% + /- 0.01%. The proposed models accurately predict a single IVF cycle pregnancy outcome and identify important predictive variables associated with the outcome. These models are limited to predicting pregnancy immediately after the IVF cycle and not live birth. These models do not include indicators of multiple gestation and are not intended for clinical application.

Thin endometrium is associated with higher risks of preterm birth and low birth weight after frozen single blastocyst transfer

BACKGROUND

It has been demonstrated that a thin endometrium is associated with a lower chance of pregnancy, but there is a paucity of research into whether a thin endometrium adversely affects perinatal outcomes.

METHODS

This was a retrospective cohort study on 10098 frozen cycles with single blastocyst transfer, resulting in 5505 singleton clinical pregnancies, and 4314 singleton live births. Patients were divided into a thin endometrium group (<8 mm) and a normal endometrium group (≥8 mm). Multivariable logistic regression with restricted cubic splines, receiver operating characteristic curve, and multivariable linear model were used for statistical analysis.

RESULTS

The incidences of preterm birth (15.65 vs. 9.80%, aOR=1.69 [1.19-2.42]), low birth weight (8.40 vs. 4.10%, aOR=2.05 [1.27-3.30]) and gestational diabetes (6.87 vs. 4.17%, aOR=1.74 [1.05-2.90]) were all higher in the endometrial thickness (EMT) <8 mm group. The miscarriage rate was higher in the EMT <8 mm group than the EMT ≥8 mm group (27.91 vs. 20.39%, aOR=1.40 [1.10-1.79]).

CONCLUSION

A thin endometrium may be associated with a higher incidence of preterm birth, low birth weight, and miscarriage. Therefore, embryo transfer should be performed with caution in these patients, and postponing to a later cycle with a thicker endometrium should be considered.

GVBD rate is an independent predictor for pregnancy in ICSI patients with surplus immature oocytes

INTRODUCTION

It was reported that there were still up to 30% immature retrieved oocyte at germinal vesicle (GV) or metaphase I (MI) stage. Whether the spontaneous maturity competency of immature oocytes associated to the clinical outcome of in vitro fertilization (IVF) cycles remains unclear and unexplored. This study aimed to investigate how the oocyte developmental parameters in in vitro maturation (IVM) affect clinical outcomes of intracytoplasmic sperm injection (ICSI) cycles.

METHODS

This retrospective cohort study included couples undergoing ICSI in a university-affiliated hospital. Surplus immature oocytes during ICSI were collected and cultured in vitro. The numbers of germinal vesicle (GV) oocytes undergoing GV breakdown (GVBD) and polar body 1 extrusion within 24 h culture were recorded. The main outcome measurements were demographic baselines and oocyte developmental parameters in IVM associated with pregnancy outcomes.

RESULTS

A total of 191 couples were included with an overall GVBD rate of 63.7% (327/513) and oocyte maturation rate of 46.8% (240/513). 53.4% (102/191) of them had embryos transferred freshly, which originated from metaphase II oocytes that matured spontaneously in vivo, and 60.8% (62/102) got pregnant. Among factors with a P-value < 0.2 in univariate logistic regression analyses of pregnancy correlation, GVBD rate (OR 3.220, 95% CI 1.060-9.782, P=0.039) and progesterone level on human chorionic gonadotropin (HCG) day (OR 0.231, 95% CI 0.056-0.949, P=0.042) remained significant in the multivariate model. The area under the curve (AUC) of the predictive nomogram was 0.729 (95% CI 0.632-0.826) with an acceptable calibration. Moreover, decision curve analyses illustrated the superior overall net benefit of models that included the GVBD rate in clinical decisions within a wide range of threshold probabilities.

CONCLUSION

In conclusion, GVBD rate and progesterone level on HCG day may be associated with pregnancy outcomes in infertile couples during the regular ICSI procedure. An elevated GVBD rate within 24 h may greatly increase the likelihood of pregnancy in infertile couples during ICSI. This preliminary study may optimize clinical pregnancy prediction, which provides support in decision-making in clinical practice.

Supernumerary embryos, do they show the cycle success in a fresh embryo transfer? A retrospective analysis

OBJECTIVE

To determine the predictive value of cryopreserved embryos during single fresh blastocyst transfer.

METHODS

This retrospective cohort study was conducted at a tertiary university hospital ART center. Patients who underwent a single fresh blastocyst transfer were selected from the electronic database. Patients with diminished ovarian reserve, uterine pathology, advanced age (>40 years) were excluded from the study. Patients were divided into two groups. Group A consisted of patients with only one available embryo for the fresh transfer. Group B consisted of patients with cryopreserved embryos apart from the fresh transferred embryo. Demographic and embryology parameters, pregnancy results were compared.

RESULTS

Demographic values, ovarian reserve parameters were comparable between groups. The number of the picked-up oocyte, metaphase-2 oocyte, and two-pronucleus embryo was lower in Group A. Positive pregnancy rates were two-fold higher in Group B (23.4% vs. 50.9% p < .01). Pregnancy results did not change depending on the number of cryopreserved embryos in Group B.

CONCLUSION

According to our results, the presence of cryopreserved embryos results in higher pregnancy rates in patients with fresh blastocyst embryo transfer independent from the woman's age and ovarian reserve. Thus, these results may help us to predict the implantation rate before embryo transfer.

Stress, anxiety, and depression in infertile couples are not associated with a first IVF or ICSI treatment outcome

BACKGROUND

Psychological distress may exert a negative influence on reproductive function of couples at reproductive age. Couples seeking assisted reproductive technology (ART) treatment may have a higher prevalence of psychological distress than fertile couples. However, whether psychological distress is associated with the outcome of ART treatment remains unknown. We aimed to investigate the association of pre-treatment psychological distress and clinical pregnancy rate among infertility couples undergoing in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) treatment.

METHODS

This nested case-control study was conducted based on women who underwent their first fresh IVF or ICSI cycle in the Jiangsu Birth Cohort Study (JBC) between November 2015 and January 2019. A total of 150 women who did not obtain clinical pregnancy after first IVF or ICSI fresh embryo transfer were identified as cases, and a total of 300 age matched women who obtained clinical pregnancy were identified as controls. Conditional logistic regression analyses were used to investigate the association between psychological distress and the outcome of first IVF or ICSI treatment, adjusting for multiple potential confounders.

RESULTS

No statistically significant association was observed between score of maternal symptoms of psychological distress and clinical pregnancy. Adjusted ORs of logistic regression were 1.00 (95% CI 0.97-1.03) for anxiety, 0.98 (95% CI 0.95-1.02) for depression, and 0.98 (95% CI 0.95-1.01) for perceived stress, respectively. When treat depression and anxiety as categorical variables, 62 (13.8%) were classified as clinical depression, 11 (2.4%) were classified as clinical anxiety, among 450 women in the present study. Psychological distress symptoms were also not associated with clinical pregnancy rate. Adjusted ORs of logistic regression were 0.27 (95% CI 0.03-2.33) for anxiety, 0.88 (95% CI 0.46-1.68) for depression, respectively.

CONCLUSIONS

Our findings firstly indicated that psychological distress experienced prior to IVF/ICSI treatment was not associated with clinical pregnancy.

Controlled Ovarian Hyperstimulation Protocol in Infertile Patients During the COVID-19 Pandemic

Objectives: To explore the appropriate controlled ovarian hyperstimulation (COH) protocols in infertility patients who received the in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) treatments during the COVID-19 pandemic.

Materials and Methods: This retrospective cohort study evaluated the efficiency of the early follicular-phase long-acting GnRH-agonist long (EFLL) protocol (a new protocol developed by Chinese clinicians), prolonged pituitary down-regulation of EFLL protocol (Pro-EFLL), and the GnRH-ant protocol for couples meeting the study criteria between February 2020 and June 2020 who were treated by the First Affiliated Hospital of Zhengzhou University during the COVID-19 pandemic, and compared the pregnancy rates and miscarriage rates per fresh transfer cycle, number of retrieved oocytes, endometrial thickness on the day of hCG injection and the number of fertilized oocytes, mature oocytes, fertilized oocytes, and transferable embryos among the three protocols.

Results: We found that the prolonged pituitary down-regulation during the COVID-19 pandemic by utilizing a full-dose of GnRH-a administrated in infertility patients were no differences in clinical outcomes than other protocols, The prolonged pituitary down-regulation protocol and EFLL protocol were associated with a higher Endometrial thickness on the day of hCG injection (12.67 ± 2.21 vs. 12.09 ± 2.35 vs. 10.79 ± 2.38, P < 0.001), retrieved oocytes (14.49 ± 6.30 vs. 15.02 ± 7.93 vs. 10.06 ± 7.63, P < 0.001), mature oocytes (11.60 ± 5.71 vs. 11.96 ± 6.00 vs. 7.63 ± 6.50, P < 0.001), fertilized oocytes (9.14 ± 5.43 vs. 8.44 ± 5.34 vs. 5.42 ± 5.20, P < 0.001), and transferable embryos (4.87 ± 2.96 vs. 6.47 ± 5.12 vs. 3.00 ± 3.28 vs. P < 0.001) in the GnRH-antagonist protocol.

Conclusion: We recommend that patients start Gn injections 33–42 days after a pituitary downregulated full dose (3.75 mg) of gonadotropin-releasing hormone agonist during the COVID-19 pandemic, even a delay of 2–4 weeks does not affect the implantation rate. The study can provide a more detailed estimate and clinical management strategies for infertile couples during the COVID-19 pandemic.

Factors associated with livebirth in couples undergoing their first in vitro fertilization cycle: An internally validated prediction model

Objective:

The aim of the study is to create a new model to predict successful outcome in assisted reproductive techniques.

Materials and Methods:

A retrospective cohort study was conducted in tertiary fertility center between 2010 and 2017. Nulliparous women younger than 45 years-old undergoing in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) for the first time were included; frozen embryo transfers, canceled induction cycles, freeze-all cycles were excluded. Two prediction models were built using multivariate logistic regression with a subset of the dataset and then were internally validated using bootstrapping methods.

Results:

Four hundred eighty eight women were included with 136 (27.9%) live births. The basal model was built using variable age, antral follicle count (AFC), and basal luteinizing hormone (LH) levels. Age over 37 years [odds ratio (OR): 0.07, 95% confidence interval (CI): 0.00-0.36] and AFC below 5 (OR: 0.15, 95% CI: 0.02-0.53) was associated with poorer outcomes whereas an LH level above 6 mIU/mL (OR: 2.24, 95% CI: 1.27-3.94) was associated with better outcomes. Optimism adjusted area under the curve (AUC) of this model was 0.68 (95% CI: 0.62-0.74). Combined model in addition to basal model variables included the length of induction cycle, the endometrial thickness at the day of transfer, grade and count of the transferred embryo. Cycles lasting more than ten days (OR: 2.23, 95% CI: 1.17-4.42), an endometrial thickness greater than 9 mm (OR: 2.07, 95% CI: 1.00-4.53) were associated with better outcomes. Optimism adjusted AUC of this model was 0.76 (95% CI: 0.70-0.81). Calibration of both models was good according to Hosmer Lemeshow test (p=0.979 and p=0.848, respectively).

Conclusion:

This internally validated prediction model has good calibration and can be used predicting outcomes in first time IVF/ICSI cycles with modest sensitivity.

Solution NMR in human embryo culture media as an option for assessment of embryo implantation potential

NMR offers the potential to holistically screen hundreds of metabolites and has already proved to be a powerful technique able to provide a global picture of metabolic changes in a wide range of biological systems underlying complex and multifactorial matrixes. This review covers the literature until May 2020 centered on the early prediction of the viability of in vitro developed embryos using several analytical techniques, including NMR. Nowadays, the predominant non-invasive technique for selecting viable embryos is based on morphology, where variables associated with the rate of cleavage and blastocyst formation are evaluated by the embryologist following standardized criteria that are somewhat subjective. This morphological approach is therefore inadequate for the prediction of embryo quality, and several studies have focused on developing new non-invasive methods using molecular approaches based particularly on metabolomics. This review outlines the potential of NMR as one of these non-invasive in vitro methods based on the analysis of spent embryo culture media.

Prediction of pregnancy outcome in fresh in vitro fertilization/intracytoplasmic sperm injection treatment in patients with poor ovarian reserve

We retrospectively analyzed the clinical data from 39,185 cycles who undergoing in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) in the First People's Hospital of Shangqiu, these poor ovarian reserve patients were further categorized into the "unexpected" group (n=3337) and the "expected" group (n=2667) based on POSEIDON classification. In "expected" group, logistic regression analysis showed that female age (OR 0.920; 95% C.I 0.902~0.939; P < 0.001), treatment cycles (OR 0.693; 95% C.I 0.560~0.859; P = 0.001), duration of Gn administered (OR 1.077; 95% C.I 1.027~1.129; P = 0.002) and transferable embryos (OR 1.377; 95% C.I 1.319~1.437; P < 0.001) is independent predictive factors of live birth. In "expected" group, logistic regression analysis showed that female age (OR 0.874; 95% C.I 0.848~0.900; P < 0.001), AFC (OR 1.285; 95% C.I 1.131~1.461; P < 0.001), total dosage of Gn administered (OR 1.001; 95% C.I 1.000~1.002; P < 0.001), duration of Gn administered (OR 0.784; 95% C.I 0.639~0.961; P = 0.019), MII number (OR 0.841; 95% C.I 0.717~0.986; P = 0.032) and transferable embryos (OR 2.057; 95% C.I 1.762~2.400; P < 0.001) is independent predictive factors of live birth. We also established a smooth curve fit to predict the probability of live birth among the POSEIDON "unexpected" and "expected" group. These independent predictive factors on the pregnancy outcome of IVF/ICSI and the successful establishment of smooth curve fit can provide valuable reference for treats poor ovarian reserve patients in clinical work.

Multivariate analysis of the factors associated with live births during in vitro fertilisation in Southeast Asia: a cross-sectional study of 104,015 in vitro fertilisation records in Taiwan

PURPOSE

To investigate the factors associated with live births and the interaction between age and the number of embryos transferred after in vitro fertilisation (IVF) treatment.

METHODS

This study analyses data from a population-based-assisted reproductive database of all registered artificial reproduction institutions (n = 80) from 2010 to 2016 in Taiwan. The probability of a live birth in correlation with the treatment parameters was measured with multivariate logistic regression analyses using the generalised additive model (GAM) and Pearson's chi-square exact test.

RESULTS

A total of 104,015 IVF treatments performed between 2010 and 2016 were included in our analysis. From these treatments, 31,467 (30.3%) were successfully delivered, and 40,565 test-tube babies were born. Pearson's chi-square exact test indicated that parents' age, cause of infertility, type of ovarian stimulation, additional assisted reproductive technology techniques, donated egg or sperm, fresh or frozen embryo, presence or absence of ovarian hyperstimulation syndrome, and day of embryo transfer were significantly associated with live births after an IVF cycle (p < 0.05). Multiple logistic regression analysis with the GAM revealed that the odds of a live birth with IVF treatment in patients < 34 years of age were 2.55 times higher than that in patients ≥ 45 years of age (odds ratio = 2.55, 95% confidence interval = 1.69-2.90) for patients who underwent a single-embryo transfer (SET); a similar pattern was observed when two or more embryos were transferred. Egg donation, the assisted hatching technique, oral ovarian stimulation agents, and implantation of frozen embryos during SET were shown to improve the chance of a live birth by 29-90%. Implantation of the embryo after the 5th day of culture yielded the highest odds of a live birth. The interaction plot revealed that maternal age, especially < 40 years, was associated with the probability of a live birth. SET and double-embryo transfer showed similar associations with the probability of a live birth across age groups. Transferring more than two embryos might reduce the probability of a live birth during IVF treatment for women ≥ 40 years of age.

CONCLUSIONS

Implanting a greater number of embryos did not improve the age-related decrease in fertility for patients undergoing IVF. Therefore, we suggested that ≤ 2 blastocysts could be transferred during IVF treatments for women ≥ 40 years. Transferring a blastocyst on day 5 of culture was associated with a significant increase in the odds of a live birth resulting from IVF.