Jenna Friedenthal1,2, Carlos Hernandez-Nieto3, Rose Marie Roth3, Richard Slifkin3, Dmitry Gounko3, Joseph A Lee3, Taraneh Nazem4,3, Christine Briton-Jones3, Alan Copperman4,3. 1. Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, 1176 5th Ave, New York, NY, 10029, USA. jfriedenthal@rmaofny.com. 2. Reproductive Medicine Associates of New York, 635 Madison Ave, 9th Floor, New York, NY, 10022, USA. jfriedenthal@rmaofny.com. 3. Reproductive Medicine Associates of New York, 635 Madison Ave, 9th Floor, New York, NY, 10022, USA. 4. Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, 1176 5th Ave, New York, NY, 10029, USA.
Abstract
PURPOSE: To assess whether utilization of a mathematical ranking algorithm for assistance with embryo selection improves clinical outcomes compared with traditional embryo selection via morphologic grading in single vitrified warmed euploid embryo transfers (euploid SETs). METHODS: A retrospective cohort study in a single, academic center from September 2016 to February 2020 was performed. A total of 4320 euploid SETs met inclusion criteria and were included in the study. Controls included all euploid SETs in which embryo selection was performed by a senior embryologist based on modified Gardner grading (traditional approach). Cases included euploid SETs in which embryo selection was performed using an automated algorithm-based approach (algorithm-based approach). Our primary outcome was implantation rate. Secondary outcomes included ongoing pregnancy/live birth rate and clinical loss rate. RESULTS: The implantation rate and ongoing pregnancy/live birth rate were significantly higher when using the algorithm-based approach compared with the traditional approach (65.3% vs 57.8%, p<0.0001 and 54.7% vs 48.1%, p=0.0001, respectively). After adjusting for potential confounding variables, utilization of the algorithm remained significantly associated with improved odds of implantation (aOR 1.51, 95% CI 1.04, 2.18, p=0.03) ongoing pregnancy/live birth (aOR 1.99, 95% CI 1.38, 2.86, p=0.0002), and decreased odds of clinical loss (aOR 0.42, 95% CI 0.21, 0.84, p=0.01). CONCLUSIONS: Clinical implementation of an automated mathematical algorithm for embryo ranking and selection is significantly associated with improved implantation and ongoing pregnancy/live birth as compared with traditional embryo selection in euploid SETs.
PURPOSE: To assess whether utilization of a mathematical ranking algorithm for assistance with embryo selection improves clinical outcomes compared with traditional embryo selection via morphologic grading in single vitrified warmed euploid embryo transfers (euploid SETs). METHODS: A retrospective cohort study in a single, academic center from September 2016 to February 2020 was performed. A total of 4320 euploid SETs met inclusion criteria and were included in the study. Controls included all euploid SETs in which embryo selection was performed by a senior embryologist based on modified Gardner grading (traditional approach). Cases included euploid SETs in which embryo selection was performed using an automated algorithm-based approach (algorithm-based approach). Our primary outcome was implantation rate. Secondary outcomes included ongoing pregnancy/live birth rate and clinical loss rate. RESULTS: The implantation rate and ongoing pregnancy/live birth rate were significantly higher when using the algorithm-based approach compared with the traditional approach (65.3% vs 57.8%, p<0.0001 and 54.7% vs 48.1%, p=0.0001, respectively). After adjusting for potential confounding variables, utilization of the algorithm remained significantly associated with improved odds of implantation (aOR 1.51, 95% CI 1.04, 2.18, p=0.03) ongoing pregnancy/live birth (aOR 1.99, 95% CI 1.38, 2.86, p=0.0002), and decreased odds of clinical loss (aOR 0.42, 95% CI 0.21, 0.84, p=0.01). CONCLUSIONS: Clinical implementation of an automated mathematical algorithm for embryo ranking and selection is significantly associated with improved implantation and ongoing pregnancy/live birth as compared with traditional embryo selection in euploid SETs.
Authors: Taraneh Gharib Nazem; Lucky Sekhon; Joseph A Lee; Jessica Overbey; Stephanie Pan; Marlena Duke; Christine Briton-Jones; Michael Whitehouse; Alan B Copperman; Daniel E Stein Journal: Reprod Biomed Online Date: 2018-12-07 Impact factor: 3.828
Authors: Carlos Hernandez-Nieto; Joseph A Lee; Richard Slifkin; Benjamin Sandler; Alan B Copperman; Eric Flisser Journal: Hum Reprod Date: 2019-09-29 Impact factor: 6.918
Authors: Zev Rosenwaks; Olivier Elemento; Nikica Zaninovic; Iman Hajirasouliha; Pegah Khosravi; Ehsan Kazemi; Qiansheng Zhan; Jonas E Malmsten; Marco Toschi; Pantelis Zisimopoulos; Alexandros Sigaras; Stuart Lavery; Lee A D Cooper; Cristina Hickman; Marcos Meseguer Journal: NPJ Digit Med Date: 2019-04-04
Authors: M VerMilyea; J M M Hall; S M Diakiw; A Johnston; T Nguyen; D Perugini; A Miller; A Picou; A P Murphy; M Perugini Journal: Hum Reprod Date: 2020-04-28 Impact factor: 6.918