Does ‘Dual Trigger’ Increase Oocyte Maturation Rate?

The aim of this study was to evaluate the oocyte maturation rate when GnRH-a and hCG (dual trigger) are co-administered, compared to the standard hCG trigger within the same patient. Included in the study were GnRH antagonist ICSI cycles performed in 137 patients who had a standard hCG trigger cycle and a dual trigger cycle between 1/1/2013 and 31/12/2017. The mean patient age (35.9 ± 5.6 and 35.2 ± 5.9; <0.001), FSH dose (4140 ± 2065 and 3585 ± 1858; <0.01), number of retrieved oocytes (10.3 ± 6.2 and 8.9 ± 6.1; 0.011) were higher in the dual trigger group compared to the hCG trigger group, oocyte maturation rate was identical. Maturation rate following dual trigger was significantly higher among 34 patients who had a maturation rate of <70% following hCG triggering and among 16 patients with a maturation rate <50% rate following hCG trigger (54% vs. 74%, p < .001 and 44% vs. 73%, p = .006; respectively). In conclusion, co-administration of GnRH agonist and hCG for final oocyte maturation substantially increased the oocyte maturation rate in patients with low oocyte maturation rate in their hCG triggered cycle, but not in an unselected population of patients.IMPACT STATEMENT What is already known on this subject? The co-administration of GnRH agonist and hCG for final oocyte maturation prior to oocyte retrieval may improve IVF outcome in patients with a high proportion of immature oocytes. The few studies on dual trigger in patients with a high proportion of immature oocytes or in normal responders have shown conflicting results. What do the results of this study add? We found that co-administration of GnRH agonist and hCG for final oocyte maturation substantially increased the oocyte maturation rate in patients with low oocyte maturation rate in their hCG triggered cycle, but not in an unselected population of patients. What are the implications of these findings for clinical practice and/or further research? The results of this study implicate that in selected population with low oocyte maturation rate, there is an advantage in using dual trigger. However, larger prospective trials are warranted to better assess oocyte response in dual trigger

An artificial intelligence algorithm for automated blastocyst morphometric parameters demonstrates a positive association with implantation potential

Abstract Blastocyst selection is primarily based on morphological scoring systems and morphokinetic data. These methods involve subjective grading and time-consuming techniques. Artificial intelligence allows for objective and quick blastocyst selection. In this study, 608 blastocysts were selected for transfer using morphokinetics and Gardner criteria. Retrospectively, morphometric parameters of blastocyst size, inner cell mass (ICM) size, ICM-to-blastocyst size ratio, and ICM shape were automatically measured by a semantic segmentation neural network model. The model was trained on 1506 videos with 102 videos for validation with no overlap between the ICM and trophectoderm models. Univariable logistic analysis found blastocyst size and ICM-to-blastocyst size ratio to be significantly associated with implantation potential. Multivariable regression analysis, adjusted for woman age, found blastocyst size to be significantly associated with implantation potential. The odds of implantation increased by 1.74 for embryos with a blastocyst size greater than the mean (147 ± 19.1 μm). The performance of the algorithm was represented by an area under the curve of 0.70 (p < 0.01). In conclusion, this study supports the association of a large blastocyst size with higher implantation potential and suggests that automatically measured blastocyst morphometrics can be used as a precise, consistent, and time-saving tool for improving blastocyst selection