Decision-making in women who considered planned oocyte cryopreservation: decision satisfaction or regret?

Research Question: Among women who considered planned oocyte cryopreservation, does decision regret differ between those who pursued planned oocyte cryopreservation and those who did not?

Design: A survey was e-mailed to all women who presented for an initial consultation for planned oocyte cryopreservation between January 2016 and December 2021 using a secure REDCap platform. The survey comprised questions on demographics, reproductive planning and the validated Decision Regret Scale (DRS). Univariable and multivariable models were fitted to compare decision regret in the group who had proceeded with planned oocyte cryopreservation with the group who had not.

Validation of a mail-in delayed semen analysis protocol developed for home collection.

Objective: To validate a mail-in delayed semen analysis service using deidentified remnant samples from a US fertility clinic.

Design: Double-blinded prospective validation of screening/diagnostic test.

Setting: Fertility clinic and clinical reference laboratory.

Looking into the future: a machine learning powered prediction model for oocyte return rates after cryopreservation.

Research Question: Could a predictive model, using data from all US fertility clinics reporting to the Society for Assisted Reproductive Technology, estimate the likelihood of patients using their stored oocytes?

Design: Multiple learner algorithms, including penalized regressions, random forests, gradient boosting machine, linear discriminant analysis and bootstrap aggregating decision trees were used. Data were split into training and test datasets. Patient demographics, medical and fertility diagnoses, partner information and geographic locations were analysed.

The 'golden fleece of embryology' eludes us once again: a recent RCT using artificial intelligence reveals again that blastocyst morphology remains the standard to beat.

Grading of blastocyst morphology is used routinely for embryo selection with good outcomes. A lot of effort has been placed in IVF to search for the prize of selecting the most viable embryo to transfer ('the golden fleece of embryology'). To improve on morphology alone, artificial intelligence (AI) has also become a tool of interest, with many retrospective studies being published with impressive prediction capabilities.

Do sperm factors influence embryonic aneuploidy? Long live the oocyte.

Study Question: What is the impact of male age- and sperm-related factors on embryonic aneuploidy?

Summary Answer: Using a 3-fold analysis framework encompassing patient-level, embryo-level, and matching analysis, we found no clinically significant interactions between male age and sperm quality with embryo ploidy.

What Is Known Already: While the effect of maternal age on embryo chromosomal aneuploidy is well-established, the impact of male age and sperm quality on ploidy is less well-defined.

Study Design, Size, Duration: This retrospective cohort study analyzed autologous preimplantation genetic testing for aneuploidy (PGT-A) and frozen embryo transfer cycles from December 2014 to June 2021.