Department of Obstetrics and Gynecology, Rabin Medical Center (Golda Campus), 7 Kakal St, Petah Tikva 49372 and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
1 To whom correspondence should be addressed. e-mail: barhava{at}ccsg.tau.ac.il
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Abstract |
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Key words: assisted reproduction technology/fluctuations/IVF/pregnancy rate/seasonality
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Introduction |
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Seasonality has been demonstrated in related biological phenomena such as natural conception, birth, stillbirth and spontaneous abortion (Rojansky et al., 1992; Torrey et al., 1993
; Fleming et al., 1994
; Minaretzis et al., 1998
). Some investigators (Levine et al., 1990
; Gyllenborg et al., 1999
) postulated that sperm quality is lower in summer because of the higher temperatures. Since spermatogenesis takes 74 days, recovery would be expected in October, and indeed, a decrease in birth rate has been observed in spring. Other studies, however, from Norway (Odegard, 1977
) and Australia (Mathers and Harris, 1983
) reported that although the highest sperm counts are detected in spring, the peak in natural conception occurs in winter. Some authors suggested that while male fertility potential seems to be influenced by temperature, the female reproductive axis is probably influenced by light (Rojansky et al., 1992
; Brzezinski, 1997
). This assumption is based on the finding that melatonin, a hormone secreted during darkness, plays a role in the regulation of reproduction (Brzezinski, 1997
).
There is little information in the literature on the fluctuation in pregnancy rates associated with fertility treatments, and the few studies conducted so far have mostly been small and retrospective (Fleming et al., 1994; Stolwijk et al., 1994
; Chamoun et al., 1995
; Dunphy et al., 1995
; Minaretzis et al., 1998
; Ossenbuhn, 1998
; Rojansky et al., 2000
). The purpose of the present study was to examine pregnancy rate fluctuations in a large patient sample attending a homogeneous assisted reproduction technology unit and to determine whether they follow a seasonal or other pattern.
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Materials and methods |
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During the study period there were no changes in the sperm medium (MediCult, Denmark) or the technique of insemination. MediCult medium was utilized as the zygote culture medium during 1996 through most of 1998. Thereafter either Irvine P1 (Irvine Scientific, USA) or Cook (Australia) was used, depending on availability. The incubators (utilizing an ambient atmosphere of 5% CO2) were not changed throughout the study. In addition, no construction took place in the unit during the study periods, no new equipment was bought, and the filtration system was not changed.
The clinical data were collected prospectively on a computerized database and included the following variables: patient age, induction of ovulation protocol, number of gonadotrophin ampoules consumed, estrogen level on day of hCG administration, number of oocytes retrieved, percentage of mature oocytes (in ICSI cycles), number of fertilized zygotes, and number and quality of embryos transferred. The fertilization rate in standard IVF was defined as the number of zygotes divided by the number of oocytes retrieved. The fertilization rate in ICSI was defined as the number of zygotes divided by the number of mature oocytes. The embryos were left in culture until the transfer day. Embryo quality was graded before transfer. Embryos with equal-sized blastomeres, ideal cleavage rate (4 cells on day 2 or 8 cells on day 3), and <20% fragmentation were defined as grade A. The rate of good embryos was defined as the number of grade A embryos divided by the number of zygotes. Embryo transfers were performed gently to the lower uterine cavity with different soft-pass catheters (either Cook, Cook OB/GYN, USA; or Wallace, Simcare Ltd, UK), depending on availability within the unit. There were no periods in which we used only one type of catheter. Good quality spare embryos were frozen for future use.
Only clinical pregnancies were considered in the analysis. These were defined as the identification of one or more intrauterine gestational sacs by transvaginal sonography at 4 weeks after transfer.
Statistical analysis
SPSS software (version rel.10.0, 1999, SPSS Inc., USA) was used for the statistical analysis. Data in Figure 1 are given as means. Monthly rates and means were calculated for the different variables. Analysis of variance was used to compare the same months between consecutive years. Additional comparisons were made for the same months between the studied years controlling for the various age groups and the number of embryos transferred. Pearson correlation was used to evaluate the relationship between the various parameters. Evaluation of seasonal patterns was performed by comparing the expected and observed pregnancy rates for each season using 2-test.
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Results |
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Discussion |
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The present study did not identify any seasonality in assisted reproduction pregnancy rates in Israel. However, as mentioned above, we cannot rule out possible seasonality in cycle outcome results in assisted reproduction technology units located in areas with stronger seasonal variations in temperature and light.
Only a few studies have been conducted on seasonality in assisted reproduction technology in particular, and their findings were conflicting. Stolwijk et al. (1994) from the Netherlands, in an evaluation of 1154 IVF cycles, demonstrated some monthly differences in pregnancy rate, with a tendency for better results during NovemberFebruary. Chamoun et al. (1995
) evaluated 183 IVF cycles in women from Baltimore (eastern USA) and noted a lower pregnancy rate in the spring than in the other seasons. In a study done in Jerusalem, Rojansky et al. (2000
) found the highest fertilization and grade A embryo rates in spring and the lowest in autumn. Other researchers from Canada (Dunphy et al., 1995
) and the UK (Fleming et al., 1994
) were unable to demonstrate a seasonal variation in implantation rate.
In the present study, 3522 consecutive assisted reproduction cycles conducted over a 4 year period in a single assisted reproduction technology unit were evaluated. The findings demonstrate fluctuations (with no seasonal pattern) in pregnancy rates which, although impressive, can be explained by chance alone. Furthermore, other variables, such as estrogen level on day of hCG administration and fertilization rate, also fluctuated at random, with no correlation to each other.
It may be assumed that the outcome of assisted reproduction treatment cycles is influenced by various factors (physiological, endocrinological, environmental, social and psychological), both recognized and unrecognized, which could obscure or affect seasonal outcome. For example, economic and political issues can affect a couples desire to procreate in general or to undergo IVF in particular. Israel is well known for its political and economical instability, and we do not believe there is a good scientific way to address these issues.
So far, the only known seasonally influenced fertility-related hormone is melatonin. In some species, melatonin has an antigonadotrophic action. In humans, melatonin synthesis has been found to increase in darkness, and melatonin may be found in small amounts in follicular fluid. In addition, the granulosa cell membrane contains melatonin receptor. One study showed that people living in the Arctic have lower pituitarygonadal function and conception rates in the dark winter than in the summer (Brzezinski, 1997). However, the role of melatonin in assisted reproduction technology has not yet been investigated.
Whether the effect of seasonality on sperm quality is a factor in conception rates remains questionable. While some studies failed to find any seasonal pattern in sperm quality studies (Ossenbuhn, 1998; Centola and Eberly, 1999
), others reported that sperm volume, count and motility are better in winter than in summer (Levine et al., 1990
); one study reported that sperm quality peaked during springtime (Reinberg et al., 1988
).
Besides sperm quality, the success of assisted reproduction treatment depends on the quality of the ovum and the resulting embryo, on the culturing conditions as well as on endometrial receptivity. Since all of these factors are themselves influenced by multiple variables, the findings of the present study are not surprising.
A common clinical practice in many assisted reproduction units worldwide is to summarize the results of the previous month or two and to find out how things are progressing. The results of the present study stress that what might seem to be a significant deterioration in pregnancy rate in the last month or two may in fact be only a normal fluctuation, and no specific problem need be sought or solved.
In conclusion, fluctuations in pregnancy rates occur in a homogeneous assisted reproduction technology unit, but they do not follow any seasonal pattern. Most of the other clinical parameters that are known to influence pregnancy rates also demonstrate fluctuations, but these fluctuations do not correlate with the fluctuations in pregnancy rate. We were unable to identify any reason for these observed fluctuations and believe that they might be explained by chance alone. These findings should be borne in mind when studies are conducted in a specific time-period.
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Acknowledgements |
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References |
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Submitted on October 22, 2002; resubmitted on July 10, 2003; accepted on July 28, 2003.