Abstract
Study question
Does variation in day 5 observation timing confound embryo-morphology-based live birth prediction, and is it possible to develop a robust comprehensive numerical prediction model.
Summary answer
Day 5 observation timing confounds embryo-morphology-based live birth prediction. A robust comprehensive numerical prediction model can be developed after considering a number of contributing variables.
What is known already
Embryo development is a dynamic process, and therefore the widely used static observations potentially lead to biased prediction of live birth outcomes. So far, little is known in regard to potential confounding impact of day 5 assessment timing on the static-morphology-based live birth prediction. In addition, the inter-observer variation in morphology-based embryo assessment requires a more robust system to improve consistency of selection.
Study design, size, duration
This retrospective multi-center cohort study included 8866 autologous oocyte in vitro fertilisation treatment cycles performed at 14 associated clinics within the same network during 2012–2018. Only fresh cycles with single day 5 embryo transfers were included for analysis with all pregnancies followed up until birth. Repeat cycles of same patients were excluded to avoid clustering effect in statistical analysis.
Participants/materials, setting, methods
Dataset was randomly split into two subsets at 60:40 ratio, with one (n = 5274) used for regression analysis and model development and the other (n = 3592) used for model testing. Multiple logistic regression was performed to evaluate live birth predicting power of several potential contributors, expressed by odds ratio (OR) and 95% confidence interval (CI). A comprehensive prediction model was subsequently developed based on calculated weights of contributing factors, then tested via receiver operating characteristics (ROC) analysis.
Main results and the role of chance
The timings of day 5 observation of 8866 included embryos, measured by hours post insemination (HPI), distributed in a bell shape ranging from 112.0 to 120.0 h (mean±SD 115.7±1.7 h). After taking into account female age at egg collection (grouped as < 30 yr, 30–34 yr, 35–39 yr, 40–44 yr, and 45 yr or older), whether or not the first egg collection, number of eggs collected, embryo developmental stage (grouped as pre-blastocyst, early blastocyst, expanding blastocyst, expanded blastocyst, and hatching/hatched blastocyst) and morphology score(A/B/C/D); multivariate logistic regression analysis showed significant association (OR 1.096, 95% CI 1.020–1.177, P = 0.012) between HPI groups (112–113.9 h, 114–115.9 h, 116–117.9 , and 118–120 h) and subsequent live birth outcomes. A comprehensive numerical scoring system was developed based on the statistically significant predictors including female age (OR 1.465, 95% CI 1.364–1.574, P = 0.000), embryo developmental stage (OR 1.341, 95% CI 1.244–1.445, P = 0.000), morphology score (OR 1.520, 95% CI 1.392–1.661, P = 0.000) and HPI (OR mentioned above); with a formula of Score = (Female_age_group/5)*1.465 + (Developmental_stage/5)*1.341 + (Morpho_Score/4)*1.520 + (HPI_Group/4)*1.096. ROC analysis showed statistically significant predictive power of the resulting model as expressed by area under the ROC curve using both the development (0.690, 0.675–0.704, P = 0.000) and testing (0.685, 0.667–0.703, P = 0.000) subsets.
Limitations, reasons for caution
The retrospective design does not allow for controlling of unknown confounders. HPI was based on static observations in this study so future time-lapse study may bring more insights with more accurate observation and measurement.
Wider implications of the findings: The varying HPIs at day 5 observation were alarming as this could confound live birth prediction using embryology parameters. It is important to standardise the timing of embryo observations. The inclusion of HPI into a comprehensive numerical scoring system for live birth prediction may potentially improve its robustness
Trial registration number
Not applicable
Dynamic evolution of osseous structure in osteonecrosis of the femoral head and dynamic collapse risks: a preliminary CT image study
