Title

The effect of day 5 blastocyst assessment timing on live birth prediction and development of a prediction algorithm

Document Type

Journal Article

Publication Title

Reproductive BioMedicine Online

Volume

44

Issue

4

First Page

609

Last Page

616

PubMed ID

35279376

Publisher

Elsevier

School

School of Nursing and Midwifery

RAS ID

52278

Comments

Liu, Y., Ong, K., Korman, I., Turner, R., Shaker, D., Zander-Fox, D., & Rombauts, L. (2022). The effect of day 5 blastocyst assessment timing on live birth prediction and development of a prediction algorithm. Reproductive BioMedicine Online, 44(4), 609-616. https://doi.org/10.1016/j.rbmo.2022.01.017

Abstract

Research question: Does variation in day 5 assessment timing confound live birth prediction using snapshot blastocyst morphology and is it possible to develop a numerical prediction algorithm? Design: Retrospective multicentre cohort study including 4851 autologous oocyte single day 5 fresh embryo transfers performed at 11 Monash IVF clinics between 2016 and 2020. Repeat cycles of the same patients were excluded to avoid clustering effects in regression analysis. Results: Hours post insemination (HPI) at day 5 assessment (115.9 ± 2.6 h) significantly correlated with blastocyst developmental stage (r = 0.118, P < 0.001). Independent association (expressed as adjusted odds ratio [aOR] and 95% confidence interval [CI]) was identified between live birth and HPI (aOR 0.950, 95% CI 0.925–0.976, P < 0.001) after accounting for blastocyst morphology and a range of patient/cycle characteristics. Algorithms were constructed using four significant live birth predictors: HPI at day 5 assessment, blastocyst developmental stage (aOR 1.347, 95% CI 1.217–1.491, P < 0.001), morphological grade (aOR 1.314, 95% 1.197–1.443, P < 0.001) and maternal age (aOR 0.922, 95% CI 0.907–0.936, P < 0.001). Receiver operating characteristic (ROC) analysis showed consistent predicting performance of algorithms via five-fold cross-validation, with similar area under the ROC curve (AUC 0.718, 0.715, 0.720, 0.712, 0.726, P < 0.001, respectively, in development subsets; and AUC 0.718, 0.731, 0.709, 0.741, 0.684, P < 0.001, respectively, in validation subsets). A score (ranging from 0.1 to 4.7) calculator based on the final algorithm was subsequently created. Conclusions: Day 5 assessment timing is a confounding factor for live birth prediction using snapshot blastocyst morphology. A numerical algorithm incorporating day 5 assessment HPI, blastocyst morphology and maternal age can be developed for live birth prediction.

DOI

10.1016/j.rbmo.2022.01.017

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