Impaired implantation in endometriosis compared with couples with male subfertility after transfer of equal quality embryos: a matched cohort study.

RESEARCH QUESTION: Is implantation impaired in patients with endometriosis undergoing IVF and intracytoplasmatic sperm injection (ICSI) cycles? DESIGN: A retrospective matched cohort study was carried out on IVF/ICSI cycles with fresh single embryo transfer at the Department of Assisted Reproductive Medicine, Ghent University Hospital, Belgium, between July 2015 and August 2017 (n = 1053). A total of 118 endometriosis cases were matched 1:1 to 118 couples diagnosed with male subfertility and stratified by embryo quality (identical ALPHA grading categories), female age (±1 year) and parity (±1 delivery). Transvaginal ultrasound, magnetic resonance imaging or laparoscopy was used to diagnosed endometriosis, and the revised American Society for Reproductive Medicine score was used to classify the endometriosis into grade I/II versus grade III/IV. Male subfertility was defined in accordance with World Health Organization criteria (fifth edition). RESULTS: Compared with endometriosis cases, control couples with male subfertility had significantly higher rates of positive HCG test on day 16 (P = 0.047, OR 2.077, CI 1.009 to 4.276), ongoing implantation (defined as a positive fetal heart rate on transvaginal ultrasound at a gestational age of at least 6.5-7 weeks) (P = 0.038, OR 2.265, CI 1.048 to 4.893), ongoing pregnancy (defined by a vital pregnancy at 11 weeks) (P = 0.046, OR 2.292, CI 1.016 to 5.173) and live birth (P = 0.043, OR 2.502, CI 1.029 to 6.087). CONCLUSIONS: After matching for embryo quality, woman's age and parity, rates of positive HCG tests, ongoing implantation, ongoing pregnancy and live birth were more than twice as high in the control group compared with the endometriosis group.

Prediction of implantation after blastocyst transfer in in vitro fertilization: a machine-learning perspective.

OBJECTIVE: To develop a random forest model (RFM) to predict implantation potential of a transferred embryo and compare it with a multivariate logistic regression model (MvLRM), based on data from a large cohort including in vitro fertilization (IVF) patients treated with the use of single-embryo transfer (SET) of blastocyst-stage embryos. DESIGN: Retrospective study of a 2-year single-center cohort of women undergoing IVF or intracytoplasmatic sperm injection (ICSI). SETTING: Academic hospital. PATIENT(S): Data from 1,052 women who underwent fresh SET in IVF or ICSI cycles were included. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): The performance of both RFM and MvLRM to predict pregnancy was quantified in terms of the area under the receiver operating characteristic (ROC) curve (AUC), classification accuracy, specificity, and sensitivity. RESULT(S): ROC analysis resulted in an AUC of 0.74 ± 0.03 for the proposed RFM and 0.66 ± 0.05 for the MvLRM for the prediction of ongoing pregnancies of ≥11 weeks. This RFM approach and the MvLRM yielded, respectively, sensitivities of 0.84 ± 0.07 and 0.66 ± 0.08 and specificities of 0.48 ± 0.07 and 0.58 ± 0.08. CONCLUSION(S): The performance to predict ongoing implantation will significantly improve with the use of an RFM approach compared with MvLRM.