Pregnancy rate fluctuations during routine work in an assisted reproduction technology unit

L. Gindes, R. Yoeli, R. Orvieto, M. Shelef, Z. Ben-Rafael and I. Bar-Hava1

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


    Abstract
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
BACKGROUND: Fluctuations in spontaneous pregnancy rates have been observed in the general population. The purpose of this study was to evaluate whether pregnancy rates fluctuate over time in a homogeneous assisted reproduction treatment unit. METHODS: The study sample consisted of 3522 consecutive assisted reproduction cycles conducted from January 1996 to December 1999. Only fresh cycles in women <41 years old were included. All pertinent clinical data were prospectively collected on a computerized database and analysed at the end of the study. RESULTS: Throughout the 4 years of the study, monthly pregnancy rates fluctuated between 10.5 and 34.1% (mean 21.4%) per cycle, and between 13.6 and 41% (mean 27.26%) per transfer. These fluctuations did not follow any specific seasonal pattern. CONCLUSION: During routine work in an assisted reproduction treatment unit, there are random fluctuations in the pregnancy rate. This factor should be considered in studies performed in a specific time-period.

Key words: assisted reproduction technology/fluctuations/IVF/pregnancy rate/seasonality


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Many specialists in assisted reproduction technology units worldwide adhere to the notion that pregnancy rates fluctuate throughout the year, with ‘good’ and ‘bad’ periods for success.

Seasonality has been demonstrated in related biological phenomena such as natural conception, birth, stillbirth and spontaneous abortion (Rojansky et al., 1992Go; Torrey et al., 1993Go; Fleming et al., 1994Go; Minaretzis et al., 1998Go). Some investigators (Levine et al., 1990Go; Gyllenborg et al., 1999Go) 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, 1977Go) and Australia (Mathers and Harris, 1983Go) 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., 1992Go; Brzezinski, 1997Go). This assumption is based on the finding that melatonin, a hormone secreted during darkness, plays a role in the regulation of reproduction (Brzezinski, 1997Go).

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., 1994Go; Stolwijk et al., 1994Go; Chamoun et al., 1995Go; Dunphy et al., 1995Go; Minaretzis et al., 1998Go; Ossenbuhn, 1998Go; Rojansky et al., 2000Go). 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.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Between January 1996 and December 1999, 4809 consecutive assisted reproduction cycles were performed in our unit. After excluding frozen–thawed cycles and women aged >41 years (to avoid the significant adverse effect of advanced age), 3522 cycles remained for analysis. The unit’s ovarian stimulation protocols, ultrasound and hormonal surveillance methods, timing of hCG administration, and oocyte retrieval and sperm processing techniques have been detailed elsewhere (Bar-Hava et al., 1997Go). Oocytes were fertilized conventionally or by ICSI. The staff team remained unchanged throughout the study period and consisted of four well-experienced specialists and two embryologists (8 and 11 years of experience). All four physicians managed the stimulation cycles and were involved in the follow-up. An internal quality control survey demonstrated no differences in pregnancy rate per transfer among the unit physicians (unpublished data).

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 {chi}2-test.



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Figure 1. Monthly pregnancy rates per cycle, 1996–1999.

 

    Results
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Throughout the 4 years of the study, monthly pregnancy rates fluctuated from 10.5 to 34.1% (mean 21.4%) per cycle (Figure 1), and from 13.6 to 41% (mean 27.3%) per embryo transfer. These fluctuations did not follow any specific seasonal pattern. Differences were found for the same calendar months in different years. Pregnancy rates did not tend to improve over the 4 years (Table I). Random monthly fluctuations were also noted for the following parameters: number of gonadotrophin ampoules consumed, peak estrogen level on day of hCG administration, and number of oocytes retrieved. The mean number of ampoules consumed per treatment cycle in the short stimulation protocols was 29.5 ± 4 (2212.5 ± 300 IU) (median 29.3; 2193.8 IU), and in the long protocols was 32.5 ± 4 (2437.5 ± 300 IU) (median 33; 2475 IU). The level of estrogen on the day of hCG administration ranged between 2200 and 5700 pmol/ml (mean 4316 ± 746 pmol/ml, median 4348 pmol/ml). The mean number of oocytes retrieved was 8.4 ± 0.9 (median 9.1).


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Table I. Monthly pregnancy rates per cycle, 1996–1999
 
For a meaningful evaluation of the fertilization rate and percentage of high quality embryos, we limited the analysis to cycles in which more than four oocytes were retrieved. The fertilization rate fluctuated from 40 to 60% in the IVF cycles (mean 50 ± 5%, median 50%), and from 45 to 77% in the ICSI cycles (mean 60 ± 7%, median 60%). The percentage of grade A embryos fluctuated from 5 to 55% (mean 20 ± 12%, median 16%). None of these fluctuations exhibited either seasonality or a correlation with the fluctuation in pregnancy rates. Similar results were obtained when the standard IVF and ICSI cycles were analysed separately (data not shown).


    Discussion
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
A seasonal distribution in human natural conception and birth rates has been demonstrated by several authors (Rojansky et al., 1992Go; Basso et al., 1995Go; Smith et al., 1998Go). In northern countries, which have strong seasonal contrasts, the activity of the anterior pituitary–ovarian axis, and accordingly, the conception rate, decreases during the dark winter. For areas without such a seasonal contrast, data are conflicting. Two studies investigated the seasonality in human fecundability in a population of 21 698 French-Canadian women who married for the first time in the 17th and 18th century (Stolwijk et al., 1996Go; Nonaka et al., 1998Go). They reported a minor seasonal pattern in time to pregnancy using the week of marriage as a reference. The highest proportion of women with a short interval from marriage to pregnancy was noted during December–January and June–July, indicating that these may be the most fecund periods. Smith et al. (1998Go), in a study from The Netherlands, found a trend toward higher fecundability during the first half of June and December. By contrast, Basso et al. (1995Go), in a study from Denmark, using their own data and data from the European Study of Infertility and Subfertility, which was based on representative random samples of women aged 25–44 years in different parts of Europe (total 4731 pregnancies), failed to detect any benefit from planning pregnancy according to season.

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. (1994Go) from the Netherlands, in an evaluation of 1154 IVF cycles, demonstrated some monthly differences in pregnancy rate, with a tendency for better results during November–February. Chamoun et al. (1995Go) 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. (2000Go) found the highest fertilization and grade A embryo rates in spring and the lowest in autumn. Other researchers from Canada (Dunphy et al., 1995Go) and the UK (Fleming et al., 1994Go) 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 couple’s 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 pituitary–gonadal function and conception rates in the dark winter than in the summer (Brzezinski, 1997Go). 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, 1998Go; Centola and Eberly, 1999Go), others reported that sperm volume, count and motility are better in winter than in summer (Levine et al., 1990Go); one study reported that sperm quality peaked during springtime (Reinberg et al., 1988Go).

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.


    Acknowledgements
 
We would like to thank Dorith Karsh, MSc of the Central Statistics Unit of Israeli Health Insurance System, Briut Clalit for the statistical analysis of the data, and Gloria Ginzach and Hanni Penn for their editorial and secretarial assistance.


    References
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
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Submitted on October 22, 2002; resubmitted on July 10, 2003; accepted on July 28, 2003.





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