Amy Barrie1, Roy Homburg2, Garry McDowell3, Jeremy Brown4, Charles Kingsland2, Stephen Troup2. 1. Hewitt Fertility Centre, Liverpool Women's NHS Foundation Trust, Liverpool, United Kingdom. Electronic address: amy.barrie@lwh.nhs.uk. 2. Hewitt Fertility Centre, Liverpool Women's NHS Foundation Trust, Liverpool, United Kingdom. 3. Manchester Metropolitan University, Manchester, United Kingdom. 4. Edge Hill University, Ormskirk, United Kingdom.
Abstract
OBJECTIVE: To study the efficacy of six embryo-selection algorithms (ESAs) when applied to a large, exclusive set of known implantation embryos. DESIGN: Retrospective, observational analysis. SETTING: Fertility treatment center. PATIENT(S): Women undergoing a total of 884 in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) treatment cycles (977 embryos) between September 2014 and September 2015 with embryos cultured using G-TL (Vitrolife) at 5% O2, 89% N2, 6% CO2, at 37°C in EmbryoScope instruments. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Efficacy of each ESA to predict implantation defined using specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV), area under the receiver operating characteristic curve (AUC), and likelihood ratio (LR), with differences in implantation rates (IR) in the categories outlined by each ESA statistically analyzed (Fisher's exact and Kruskal-Wallis tests). RESULT(S): When applied to an exclusive cohort of known implantation embryos, the PPVs of each ESA were 42.57%, 41.52%, 44.28%, 38.91%, 38.29%, and 40.45%. The NPVs were 62.12%, 68.26%, 71.35%, 76.19%, 61.10%, and 64.14%. The sensitivity was 16.70%, 75.33%, 72.94%, 98.67%, 51.19%, and 62.33% and the specificity was 85.83%, 33.33%, 42.33%, 2.67%, 48.17%, and 42.33%, The AUC were 0.584, 0.558, 0.573, 0.612, 0.543, and 0.629. Two of the ESAs resulted in statistically significant differences in the embryo classifications in terms of IR. CONCLUSION(S): These results highlight the need for the development of in-house ESAs that are specific to the patient, treatment, and environment. These data suggest that currently available ESAs may not be clinically applicable and lose their diagnostic value when externally applied.
OBJECTIVE: To study the efficacy of six embryo-selection algorithms (ESAs) when applied to a large, exclusive set of known implantation embryos. DESIGN: Retrospective, observational analysis. SETTING: Fertility treatment center. PATIENT(S): Women undergoing a total of 884 in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) treatment cycles (977 embryos) between September 2014 and September 2015 with embryos cultured using G-TL (Vitrolife) at 5% O2, 89% N2, 6% CO2, at 37°C in EmbryoScope instruments. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Efficacy of each ESA to predict implantation defined using specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV), area under the receiver operating characteristic curve (AUC), and likelihood ratio (LR), with differences in implantation rates (IR) in the categories outlined by each ESA statistically analyzed (Fisher's exact and Kruskal-Wallis tests). RESULT(S): When applied to an exclusive cohort of known implantation embryos, the PPVs of each ESA were 42.57%, 41.52%, 44.28%, 38.91%, 38.29%, and 40.45%. The NPVs were 62.12%, 68.26%, 71.35%, 76.19%, 61.10%, and 64.14%. The sensitivity was 16.70%, 75.33%, 72.94%, 98.67%, 51.19%, and 62.33% and the specificity was 85.83%, 33.33%, 42.33%, 2.67%, 48.17%, and 42.33%, The AUC were 0.584, 0.558, 0.573, 0.612, 0.543, and 0.629. Two of the ESAs resulted in statistically significant differences in the embryo classifications in terms of IR. CONCLUSION(S): These results highlight the need for the development of in-house ESAs that are specific to the patient, treatment, and environment. These data suggest that currently available ESAs may not be clinically applicable and lose their diagnostic value when externally applied.
Authors: N Zaninovic; M Nohales; Q Zhan; Z M J de Los Santos; J Sierra; Z Rosenwaks; M Meseguer Journal: J Assist Reprod Genet Date: 2019-01-22 Impact factor: 3.412
Authors: Liubin Yang; Mary Peavey; Khalied Kaskar; Neil Chappell; Lynn Zhu; Darius Devlin; Cecilia Valdes; Amy Schutt; Terri Woodard; Paul Zarutskie; Richard Cochran; William E Gibbons Journal: F S Rep Date: 2022-04-15