Fig. 36.1
Percent of zygotes entering syngamy at 25 hpi for donor oocytes (42 cycles/462 zygotes), standard IVF patient <38 (94 cycles/864 zygotes), advanced maternal age >38 (76 cycles/479 zygotes), and recurrent implantation failure patients (62 cycles/484 zygotes)
For the purposes of this chapter, we will use entry into syngamy as a measure of oocyte quality.
36.6 Embryo Quality
While the maxim stated at the beginning of this chapter that only good quality oocytes can make good quality embryos is true, it is easily derailed and that we can make poor quality embryos from good quality oocytes using inappropriate conditions.
What defines a “good” embryo? There are as many embryo scoring and grading systems as there are IVF units, and some of the most commonly used criteria of fragmentation and overall morphology are currently being reexamined in the light of several observations, originally based on specific observation times and, more recently, the advent of time lapse recording systems [3]. Even with the most stringent scoring systems, the “best” embryos have only a 50 % chance of implantation. This suggests that the use of such systems is limited as to its efficacy. More recently, the term “on time, appropriate development,” as defined by the Alpha/ESHRE consensus, has proved to be at least as effective as the more complex methods. Again, time lapse measurements of early development are adding more precise information to appropriate development [11].
On time, appropriate development and the effect on implantation rates are illustrated in Fig. 36.2, where the same dataset used for Fig. 36.1 was used. It is quite clear from this graph that the embryos from the poorer prognosis groups develop at a slower rate, and these differences increase with extended culture.
Fig. 36.2
The percentage of zygotes from each group meeting their developmental milestones. These milestones were 4-cell embryos at 43 h post insemination (hpi) on day 2, >7 cells at 67 hpi for day 3, and blastocoel formation at 115 hpi for day 5
The differences between the groups are further illustrated in Fig. 36.3, where the ratio of blastocysts forming on day 5 was greatest for the “good” prognosis groups (donor and first cycle patients) compared with the “poor” prognosis groups (advanced maternal age and RIF patients). The overall utilization rates (defined as the percent of zygotes that were either transferred or frozen) and implantation rates per embryos transferred fresh follow the same trends. The apparent decrease in miscarriage rates suggests that “good” prognosis embryos are less liable to fail in pregnancy maintenance.
Fig. 36.3
The ratio of blastocysts forming on day compared with day 6 (d5:d6), the percent of zygotes that were transferred or frozen (utilized, ut), the implantation rate (measured as a fetal heart) per embryo that was transferred fresh (Ir), and the miscarriage rate after fetal heart detection
Using the “on time, appropriate development” methods should now give us more quantitative methods to look at the effect of stimulation regimes on embryonic development. However, can we make the contention that if only “good” oocytes make “good” embryos, will the measurement of zygote syngamy be sufficient by itself to investigate differences in stimulation regimens?
36.7 Evidence
There are three main areas of ovarian stimulation which can potentially affect the quality of oocytes and embryos. These are suppression of pituitary functions using GNRH agonists and antagonists, stimulation of follicular development with FSH, and the “trigger” used to initiate oocyte maturation and release. Various adjuvants have also been used to attempt to mediate all of these processes.
36.7.1 Pituitary Suppression
Data for agonist and antagonist pituitary suppression have been extensively studied, and the data is consistent with little or no difference between their outcomes when using relatively non-quantitative outcome measures such as live births [12, 13]. We have used syngamy and early embryonic development to compare agonist and antagonist for a substantial number of cycles in several IVF units, both in Australia and other countries. The results are summarized in Table 36.1. No statistical difference could be found with the agonist versus antagonist using non-inferiority testing with a statistical power of 95 % (>4000 zygotes in each arm). The data adds further evidence that, under normal “standard” protocols, there are no statistical differences between agonist and antagonist pituitary suppression.
Table 36.1
Comparison of early development events between agonist and antagonist pituitary suppression
Stage | Hours post insemination (hpi ± 1) | Agonist (4534 zygotes) (% of zygotes) | Antagonist (4823 zygotes) (% of zygotes) |
---|---|---|---|
Syngamy | 25 | 58 % | 59 % |
>3 cell d2 | 43 | 68 % | 66 % |
>7 cell d3 | 67 | 50 % | 54 % |
36.7.2 Follicular Stimulation
Stimulation of follicles is usually achieved using FSH either recombinant (rFSH), extracted from urine (uFSH) or a mix of both. Again the literature is rife with reports as to the benefit of one regimen over another. It is very interesting to analyze two Cochrane reviews, the first [14] suggesting a small increase in live take-home baby rate with rFSH and the second suggesting no difference [15]. I think this underlines one of the problems using pregnancy and live birth data, as outlined above, the data having inadequate resolving power with too many confounders.
In Australia, we have not been able to use urinary-derived FSH until recently, so we have not been able to derive a comparison between urinary and recombinant products. The comparison we have been able to make is between antagonist and rFSH and antagonist and a mix of rFSH and uFSH (from an associated clinic not in Australia). The results are shown in Table 36.2. While the differences are significant (p = 0.0066), the dataset needs deriving under more stringent conditions.
Table 36.2
Comparison of early development events using either rFSH alone or using a combination of rFSH and uFSH
Stage | Hours post insemination (hpi ± 1) | rFSH (876 zygotes) | rFSH and uFSH (642 zygotes) |
---|---|---|---|
Syngamy | 25 | 56 % | 64 % |
>3 cell d2 | 43 | 65 % | 70 % |
>7 cell d3
Stay updated, free articles. Join our Telegram channelFull access? Get Clinical TreeGet Clinical Tree app for offline access |