Department of Obstetrics and Gynaecology, Sahlgrenska University Hospital, Göteborg, Sweden
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Abstract |
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Key words: in-vitro fertilization/multiple births/single embryo transfer
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Introduction |
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An alternative to consistent one-embryo transfer would be an individualized embryo transfer policy, as previously discussed (Coetsier and Dhont, 1998). A theoretical model was developed in which multiple pregnancies were reduced from 28% to 15% and pregnancy rates from 30% to 26% if one-embryo transfer was applied in selected patients. A Finnish study has also demonstrated satisfactory pregnancy rates (29.7%) after one-embryo transfers in selected groups of patients (Vilska et al., 1999
).
The aim of the present study was to identify cycles at increased risk of multiple births and to calculate the effects on the overall birth and multiple birth rates in routine cycles if a one-embryo transfer policy was applied to the high risk group.
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Materials and methods |
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The mean maternal age was 32.7 years (SD 3.7, range 2240). The primary indications for IVF treatment were tubal disease (29%), endometriosis (9%), male factors (33%), unexplained infertility (16%), hormonal factors (2%) and mixed causes (11%). During the study period, 61.4% of the women underwent one cycle, 31.8% underwent two, 6.4% underwent three and 0.4% underwent four stimulated transfer cycles, although our IVF programme offers routinely only three stimulated cycles. Among the 2107 cycles, first cycles constituted 49.3%, second cycles 32.0%, third cycles 13.6% and fourth or higher rank cycles 2.0%.
Definitions
Embryo quality was assessed by considering the number of blastomeres, day of transfer and degree of fragmentation. Embryos with a normal cleavage rate (34 cells on day 2 and 68 cells on day 3) and <20% fragmentation were defined as good quality embryos. Embryos with >50% fragmentation and/or cleavage arrest were not transferred.
Birth and multiple birth were analysed as primary outcomes. Implantation was defined as an implanted embryo resulting in birth. Calculations of birth rates after theoretical one-embryo transfers were made as if the same implantation rates were present regardless of the number of embryos transferred.
Embryo reduction of triplets to single pregnancies was performed in two cases. Their data were recorded as if they had a triplet pregnancy reaching delivery. No more triplet pregnancies occurred.
Analysed variables
The factors for inclusion were chosen because they were either known to be an important predictor of outcome or there was a theoretical rationale for the factor to be predictive (Templeton et al., 1996; Croucher et al., 1998
). The following factors were analysed as possible predictors of birth and multiple birth: the woman's age, previous pregnancy and previous childbirth (spontaneous and as a result of previous IVF), previous IVF attempts, the indication for IVF, FSH dosage and duration, number of retrieved oocytes, fertilization method (conventional IVF or ICSI), number of fertilized oocytes, proportion of fertilized oocytes (number of fertilized oocytes divided by the number of retrieved oocytes), number of good quality embryos available for transfer, day of transfer (day 2 or 3 after oocyte retrieval), number of good quality embryos transferred and number of embryos suitable for freezing.
Statistical analysis
Each of the above-listed variables was included in a primary logistic regression analysis, with adjustment only for number of previous IVF cycles, with the dependent variables birth and multiple birth. A P value < 0.10 was chosen for inclusion of predictors in the secondary analysis. For both of the dependent variables, those predictors were included in a multivariate forward step-wise logistic regression analysis. Adjustment of the variance of the ß-coefficients was made, in order to allow for each individual to contribute with more than one cycle. No bias of the ß-coefficients is introduced when a patient is included more than once in the logistic regression analysis and the order of the IVF cycle is used as a variable. However, the dependence will imply an underestimation of the variance of the ß-coefficients and thus influence the P values and the confidence intervals. An adjusted variance was achieved by multiplying the variance with n2/n1, where n1 denotes the number of patients and n2 the number of cycles. This conservative method was applied for calculation of P values and confidence intervals. A P value < 0.05 was considered to be significant.
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Results |
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Analyses of correlation between the predictors and the outcome variables
The results of the correlation analysis are shown in Table I. Each variable is adjusted for number of previous IVF cycles. Age, tubal infertility, FSH dosage expressed as negative correlation and number of good quality embryos transferred showed a positive correlation to both birth and multiple birth. In addition, number of retrieved oocytes, number of fertilized oocytes, number of good quality embryos available for transfer and number suitable for freezing were all positively correlated with birth.
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The number of good quality embryos transferred and female age were independently predictive of both birth and multiple birth. In addition, tubal indication and number of previous IVF cycles were negatively predictive of birth. These results are further presented in Table II as odds ratios and 95% confidence intervals for each level of variables that were independently predictive of birth and multiple birth.
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Discussion |
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The present study analysed predictors of both birth and multiple birth, with the intention of identifying patients suitable for one-embryo transfer. The study population has the advantage of being very homogeneous concerning stimulation protocols and transfer policies, since all cycles were performed at the same centre.
We identified age and quality of embryos as the two most important predictive variables of birth and multiple birth. The odds ratios for all variables were generally close to 1.0, indicating that the impact of each variable was very low, demonstrating the difficulties in finding individual variables of substantial importance. The very close connection between factors influencing birth and multiple birth was demonstrated by the possibility of using both models, predicting birth and multiple birth with similar results.
One reason to analyse multiple pregnancy in addition to multiple birth is that a multiple pregnancy can be considered for fetal reduction. In a study with a similar design and size as ours, although with a higher rate of multiple gestation, the predictive variables for multiple gestation were identified as: female age, cycle number, number of embryos available for transfer and number of transferred embryos of good quality (Coetsier and Dhont, 1997).
Tubal infertility as a negative predictor for multiple birth did not reach statistical significance, but was considered to be a clinically important factor for predicting birth. Well known factors, such as the presence of hydrosalpinges (Strandell et al., 1999), may contribute to the negative influence of tubal infertility, but also severe tubal damage, regardless of hydrosalpinges, is associated with poor IVF outcome (Csemiscky et al., 1996). Patients with hydrosalpinges accounted for <10% of tubal infertility in the present study. The model was improved by the inclusion of the variable tubal factor, thus allowing for lower age limits in the recommendation of one-embryo transfer to tubal infertility patients.
It has to be emphasized that our calculations on birth rates after one-embryo transfers are theoretical and based on the assumption that implantation rates will be the same whether one or two embryos are transferred. However, only implantations resulting in a birth are included and since a one-embryo transfer always includes the highest quality embryo, birth rates are likely to be even higher than calculated. In the near future, when one-embryo transfers will be performed more often, we will have unique opportunities to gain knowledge about embryo characteristics and their importance to implantation.
Our initial aim is to reduce the multiple birth rate by half. This scenario includes a reduction of the total birth rate from 29% to 25% if no additional cycles are performed. It should be possible to reach the original birth rate by performing additional frozenthawed cycles. Based on the data in Table III and an estimated implantation (resulting in birth) rate of 15% at frozenthawed one-embryo transfer, one freeze cycle has to be performed in three out of four patients in the high risk group (269 births if two embryo transfers 179 births if one embryo transfers = 90 missing births, 90/0.15 = 600 needed freeze cycles, 600/786 women in the high risk group = 76%). Assuming a 50% survival rate of frozenthawed embryos, there is a minimum demand for at least three good quality embryos from the stimulated cycle. Consequently, we should be able to reach the same birth rate by transferring one embryo in a fresh cycle to the identified high risk group and one embryo in a freeze cycle to the three quarters of the high risk group that did not have a term pregnancy from the fresh transfer. A prerequisite, though, is a successful high quality freezing programme. This scenario would increase the work load and the initial cost at the IVF centre, but undoubtedly decrease the rate of multiple birth substantially and consequently reduce the costs of neonatal and handicap care for society.
In a similar theoretical analysis, costs of sick leave and hospitalization during pregnancy, delivery, neonatal intensive care and handicap care were considered after transfer of one or two embryos. Although more treatments were needed to achieve the same take-home baby rate, the one-embryo transfer policy was more cost-efficient (Wølner-Hanssen and Rydström, 1998).
Based on the results of the present study, a prospective randomized multicentre study in Sweden has been initiated. It should provide us with guidelines and support us in our effort to reduce the rate of multiple births.
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Acknowledgments |
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Notes |
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References |
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Submitted on June 18, 2000; accepted on September 12, 2000.