An interpretable machine learning model for individualized gonadotrophin starting dose selection during ovarian stimulation.

Research Question: Can we develop an interpretable machine learning model that optimizes starting gonadotrophin dose selection in terms of mature oocytes (metaphase II [MII]), fertilized oocytes (2 pronuclear [2PN]) and usable blastocysts?

Design: This was a retrospective study of patients undergoing autologous IVF cycles from 2014 to 2020 (n = 18,591) in three assisted reproductive technology centres in the USA. For each patient cycle, an individual dose-response curve was generated from the 100 most similar patients identified using a K-nearest neighbours model. Patients were labelled as dose-responsive if their dose-response curve showed a region that maximized MII oocytes, and flat-responsive otherwise.

An interpretable machine learning model for predicting the optimal day of trigger during ovarian stimulation.

Objective: To develop an interpretable machine learning model for optimizing the day of trigger in terms of mature oocytes (MII), fertilized oocytes (2PNs), and usable blastocysts.

Design: Retrospective study.

Setting: A group of three assisted reproductive technology centers in the United States.

Correction: Clinical experience with carrier screening in a general population: support for a comprehensive pan-ethnic approach.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Clinical experience with carrier screening in a general population: support for a comprehensive pan-ethnic approach.

Purpose: To present results from a large cohort of individuals receiving expanded carrier screening (CS) in the United States.

Methods: Single-gene disorder carrier status for 381,014 individuals was determined using next-generation sequencing (NGS) based CS for up to 274 genes. Detection rates were compared with literature-reported values derived from disease prevalence and carrier frequencies.

High gonadotropin dosage does not affect euploidy and pregnancy rates in IVF PGS cycles with single embryo transfer.

Study Question: Does high gonadotropin dosage affect euploidy and pregnancy rates in PGS cycles with single embryo transfer?

Summary Answer: High gonadotropin dosage does NOT affect euploidy and pregnancy rates in PGS cycles with single embryo transfer.

What Is Known Already: PGS has been proven to be the most effective and reliable method for embryo selection in IVF cycles. Euploidy and blastulation rates decrease significantly with advancing maternal age.

Association between growth dynamics, morphological parameters, the chromosomal status of the blastocysts, and clinical outcomes in IVF PGS cycles with single embryo transfer.

Purpose: The purpose of the present study is to examine interconnection between speed of embryo development, the genetic status of the blastocysts, and clinical outcomes in IVF preimplantation genetic screening (PGS) cycles with single embryo transfer (SET).

Methods: The retrospective comparative study has been performed between January 2013 and January 2016. Seven hundred thirty-seven cycles of IVF treatment with PGS, followed by 503 SETs, were included in the study.