Results
In this study, 1492 women were enrolled. The
mean maternal age was 32.3 ± 5.3 years, while the
mean duration of infertility was 7.2 ± 5.07 years. Of
1492 women, 1172 (78.5%) individuals were with
primary infertility, while 320 (21.5%) individuals
were with secondary infertility. Overall, 59.8% of
patients had previous treatment for infertility, and
we also found a significant reduction of pregnancy
rate in the group with previously failed ICSI attempts.
The general characteristics of all participants
undergoing ICSI, divided into pregnant and
non-pregnant groups,are provided in table 1.
Our findings confirmed that the pregnancy
rate reduced when the woman’s age increased
(OR=0.93, 95% CI=0.91-0.95). In addition, our
result revealed that pregnancy rate were lower in
primary infertility than secondary infertility, but it
is n’t significant. Our results also showed no significant
effect of body mass index (BMI) on pregnancy
rate ( Table 1 ).
Characteristics of women undergoing ICSI in two groups of pregnant and non-pregnant
*; OR=Odds ratio, CI=Confidence interval, **; Values are mean ± SD, ***; Reference category, a; Independent sample t test
and b; Chi-square test.
Table 2 indicates the different causes of infertility
and their likelihood of occurrence, like
ovulatory factor (7.4%), tuboperitoneal factor
(5.2%), unexplained factor (10%), male factor
(59.1%), recurrent abortion (2.1%), uterine factor
(0.4%), Mix (14%), and others (impotency,
vaginismus, genetic disorder, etc) (1.7%). Furthermore,
table 2 shows outcome of ICSI cycles
in different causes of infertility, where as
there was no statistically significant difference
between groups.
Cycle characteristics are depicted in table 3.
We found total dose of gonadotropin of nonpregnant
group to be significantly higher than
that of pregnant group (p<0.0001). Table 3 reveals
that there was statistically significant difference
between the pregnant and non-pregnant
groups in endometrial thickness (p<0.05). The
number of retrieved metaphase II (MII) oocytes
was significantly higher in pregnant group than
that in non-pregnant group. There was no significant
difference between two groups in the
mean serum concentrations on day 3 after application
of the following hormones: FSH (7.04 ±
3.43 IU/ml), LH (5.51 ± 4.06 IU/ml), TSH (2.35
± 1.81 IU/ml), metoclopramide-stimulated prolactin
(PRL) (163.40 ± 264.82 IU/ml) ( Table 3 ).
Success rate of ICSI outcome in infertile couples with different cause of infertility
*; Impotency, vaginismus, genetic disorder and a; Chi-square test.
Table 3: Cycle parameters of the patients undergo ICSI
* ; OR=Odds ratio, CI=Confidence interval, **; Values are mean ± SD and a; Chi-square test.
However, there was statistically significant
difference in the mean serum level on day 3 after
application of LH between the pregnant and
the non-pregnant groups. There were no statistically
significant differences between groups
in number of MII oocytes, embryo transfer and
number of good embryo (grade A, B, AB) ( Table 3 ). No significant difference was also observed
between the pregnant and non-pregnant
groups in the number of metaphase I (MI) (OR=
0.97, CI=0.85-1.1; p=0.68). Fertilization rate
in the pregnant and non-pregnant groups was
71 and 68%, respectively (OR=1.31, CI=0.92-
1.89; p=0.13) ( Table 3 ).
Finally, in order to build a prediction model
and find the most important factors that affect
pregnancy rate, we used a logistics regression
model in a backward manner. Table 4 shows
the result of fitting logistic regression model
to the data.
Age, menstrual duration, number of previous
cycle, endometrial thickness, number of embryo
transfer, and embryo quality in the logistic regression
model were significantly associated with
pregnancy outcome. Age and number of previous
cycle were negatively associated with pregnancy
outcome, while menstrual duration, endometrial
thickness, embryo quality and number of embryos
transferred were positively associated with pregnancy
outcome ( Table 4 ).
Table 4: Result of logistic regression analysis
* OR; Odds ratio and CI; Confidence interval.
AUC shows the discriminative performance of
the logistic model. The AUC of 0.5 shows no discriminative
performance, while AUC of 1.0 indicates
perfect discrimination. The AUC for the fitted
logistic model was 0.681 (95% CI=0.653-0.709)
that shows good predictive performance ( Fig 1 ).
Figure 2 indicates the calibration of the prediction
model for pregnancy after ICSI. The predictive
performance of the model is acceptable because the
95% confidence intervals of the observed pregnancy
rates overlap with the predicted pregnancy rates.
ROC curve for assessment discrimimative preformance
of logistic regression.
Calibration plot, showing the relationship between
predicted and observed rate of pregnancy after ICSI.
Discussion
Although ICSI is originally developed to treat
male infertility, it has been used for infertile couples
with different causes of infertility ( 1 ). We
evaluated the relation between ICSI outcome and
different causes of infertility, while our obtained
data illustrated the different success rate of ICSI
in various causes of infertility ( Table 2 ). Our data
also supported maternal age as an important predictor
for having a successful outcome in ICSI,
which is found to bein agreement with results of
some studies ( 16 - 20 ), while contradicts to a study
of Spandorfer et al. in which they have found no
impact of paternal age on ICSI success rates ( 21 ).
In the present study, endometrial thickness was
regarded as prognostic parameters for successful
pregnancy in ICSI, which was in agreement with
several studies showing endometrial thickness was
greater in cycles resulting in pregnancy than in cycles
not resulting in pregnancy ( 16 , 19 , 20 , 22 , 23 ).
In addition, other studies have showed increased
endometrial thickness is not associated with decreased
pregnancy rates in ART treatment ( 24 , 25 ).
In our study, no significant difference was
found in BMI between pregnant and not-pregnant
groups. Usoniene et al. reported the same results
of pregnancy rate for different BMI groups ( 19 ).
The other studies indicated that when BMI was
higher than 25 kg/m 2 , the pregnancy rate was significantly
lower ( 26 , 27 ). Non-PCOS patients undergoing
IVF/ICSI showed an increase in BMI independently
of age, LH, FSH, as well as duration
and type of infertility, whereas these factors affect
pregnancy rate, significantly ( 28 ).
In our study, mean LH serum concentration in
pregnant group were significantly higher than
that in non-pregnant group (OR=1.02, CI=1-1.05;
p=0.04). At the beginning of stimulation, high LH
concentration can lead to increased endometrial
maturation at oocyte pick-up ( 29 ). Balasch et al.
found LH is not necessary for follicular growth, but
externally administered LH possibly shows a primary
role in complete maturity of the oocyte and follicle
( 30 ). LH is required for normal folliculogenesis,
while low LH concentrations on day 3 could lead to
a poor ovarian response ( 31 ). However, basal LH
and E2 levels are not considered as proper factors in
order to distinguish the infertile patients responding
differently to ovarian stimulation ( 32 ).
History of menstrual cycle length (MCL) will be
used as a simple sign of ovarian reserve, which is
primarily determined by the growth rates and quality
of ovarian follicles. Our result showed women
with menstrual duration more than 6 days had more
chance of pregnancy than those with cycles less
than 6 days (OR=1.12, CI=1.04-1.21; p=0.002).
Shortening of MCL causes an abbreviated follicular
phase, but in general, luteal phase length is preserved
( 33 ). The shorter follicular phase is associated
with a decrease in inhibin B and an increase
in FSH, which could be due to smaller number of
antral follicles ( 33 ).
Tomas et al. found the influence of embryo
quality in pregnancy prediction ( 34 ). Our result
showed higher pregnancy rate in the best quality
of embryo transferred. Different reports have also
revealed that ICSI may be performed successfully
incases with a history of fertilization failure ( 35 ).
We also found that women with repeated fertilization
failure were at higher risk of pregnancy loss
(Tables 2 , 4 ).
Esinler et al. showed that larger doses of gonadotropin
are required for overweight and obese
women ( 36 ). Our findings also revealed the significant
effects of total dose of gonadotropin and
endometrial thickness on outcome of pregnancies
conceived by ICSI.
It is evident that various factors may influence
the outcome of ICSI. Kovacs et al. showed, women
who became pregnant after ART showed thicker
endometrium, better quality of embryo, as well
as more follicles, oocytes and embryos ( 25 ) as we
observed in our study. In this study, we examined
variable parameters in patients with different causes
of infertility and predicted pregnancy success
rates following ICSI. In addition, patient characteristics,
total dose of gonadotropin, endometrial
thickness, number of previous cycle and quality
of embryo transferred were evaluated as predictors
of success rates following ICSI. Our findings
confirmed that larger doses of gonadotropin, a decrease
in endometrial thickness and in appropriate
embryo quality reduced significantly pregnancy
success rate. Our results also indicated that ICSI
in an effective option in couples with different
causes of infertility. We did not find an association
between cause of infertility and clinical outcomes.
The overall pregnancy rate in our study was 33.9%
(n=1492).
Undoubtedly, this database was not large enough
to allow definite conclusion, and needed further
supports to continue the follow-up of pregnancy
outcome after ICSI.
Our models can be used reliably as a guide for
making decisions for fertility management in infertile
patients. The effects of using these models
in patient care need further experimental investigation.
Conclusions
ICSI is an important treatment option for various
indications of infertility. The present study
showed that pregnancy rate affected by the number
of previous cycle, total dose gonadotropin,
endometrial thickness, number of previous cycle,
quality of embryo transferred and menstrual duration.
It is required that each infertility center gather
enough information about the causes of infertility
in order to provide more information and better
assistance to patients. Therefore, we suggest that
physician sprepare adequate training and required
information regarding these procedures for infertile
couples in order to improve their knowledge.
Introduction
Intracytoplasmic Sperm injection (ICSI) brings
an operative technology in the fields of assisted
reproduction technology (ART) ( 1 ). Nowadays,
this way becomes one of the most important and
efficient treatment approaches which is used by
infertility clinics. One of problems in infertility
centers is low rate of pregnancy in ICSI cycles
( 2 ). There is still an ongoing debate among reproductive
embryologists and endocrinologists
about using ICSI for the treatment of the infertile
couples. There is a general agreement that
ICSI has become a gold standard technique for
the treatment of male factor infertility ( 3 , 4 ),
but many physicians recommend ICSI or invitro
fertilization (IVF) to patients with tubal
factor infertility ( 5 ). However, there is controversy
about the replacement of ICSI with IVF in
women with sever tubal factor infertility ( 5 , 6 ).
It could be helpful in planning strategies for the
treatment of infertile couples with unexplained
infertility ( 7 , 8 ). Although ICSI has been applied
for the male factor infertility more than
tubal factor infertility and endometriosis, it may
be a useful technique to overcome these types
of fertilization defect in women ( 9 , 10 ).
Multiple studies have also showed a higher
risk of congenital abnormalities, cardiovascular,
musculoskeletal defect, low birth weight, preterm
delivery and increase perinatal mortality
in IVF/ ICSI offspring ( 11 - 15 ). Nevertheless,
there is an imperfect image of the risk factors
associated with the application of ICSI about
offspring. Although this technique is accepted
as a standard routine for couples with different
causes of infertility ( 11 ). There are no data to
suggest that ICSI is a proper method in order to
apply for all ART cases. Since ICSI has a great
cost to both couple and the health care system,
it is necessary to assess its efficacy ( 3 ).
Different success rate of ICSI has also been observed
in various causes of infertility. Our prediction
model has been developed in reproductive
medicine to help gynecologists in assessing the
chances of pregnancy following ICSI. With these
models, gynecologists can calculate the probability
of a treatment pregnancy as well as the probability
of pregnancy success with ICSI. In this study,
we evaluated the relation between ICSI outcome and special cause of infertility. We also aimed to
examine parameters that might predict pregnancy
success rate following ICSI.
Materials|Methods
This cross sectional study included 1492 infertile
women referred to Infertility Center of Royan
Institute between 2010 and 2011.We assigned
two groups including pregnant (n=504) and nonpregnant
(n=988), while all participants underwent
ICSI cycles.
Information about age, menstrual duration,
number of previous cycle, endometrial thickness,
number of embryo transfer, embryo quality,
duration of infertility, type of infertility, cause of
infertility (ovulatory factor, unexplained factor,
male factor...) were obtained from patient’s file,
then the collected data were analyzed and compared
between the two groups. Inclusion criteria
were as follows: male infertility, ovarian infertility
(including polycystic ovary syndrome (PCOS)
and diminished ovarian reserve), tubal infertility,
unexplained infertility, recurrent abortion, and endometriosis.
The couples with testicular atrophy, anatomical
abnormalities, infection, uterine fibroids,
systemic disease and history of ICSI/IVF failure
more than three times were excluded from the
study. In all participants, serum follicle-stimulating
hormone (FSH; Pishtaz-Tab, Tehran,
Iran) and luteinizing hormone (LH; Pishtaz-
Tab, Tehran, Iran) were measured on day 3 of
the cycle preceding ovarian stimulation. The
ovarian stimulation protocol for all patients
was performed according to the standard long
protocol. Both groups started with Bucereline
acetate (Superfact; Aventis Pharma Deutshlan,
Frankfurt, Germany) 500 μg on day 21 of the
previous cycle and continued daily until the day
of hCG administration. After ovarian stimulation,
injection of 10000 IU of human chorionic
gonadotropin (hCG; Choriomon; IBSA, Switzerland)
was given when at least two follicles
≥18 mm were detected. Transvaginal follicular
aspiration was performed under ultrasound
guidance, 34-36 hours after the administration
of hCG. Afterwards, ICSI cycle was completed.
All patients received luteal phase support
through daily administration of 100 mg natural
progesterone (sterop Laboratories, Brussls, Belgium) and progesterone up to 8 week of gestation.
A clinical pregnancy was confirmed by
the observation of gestational sac in ultrasonography.
This study was approved by the Royan
Ethics Committee.
In addition, all subjects agreed to participate in
the study were required to sign a consent form approved
by the Royan Ethics Committee.
In order to build a prediction model, we used
backward logistic regression analysis, in which
a p-value of 0.15 was used as an entry criterion,
whereas a p-value of 0.10 was the threshold for
a variable to stay in the model. The performance
of the model was calculated as the area under the
receiver operating characteristic (ROC) area under
roc curve (AUC). An AUC of 0.5 indicates no discriminative
performance, whereas an AUC of 1.0
indicates perfect discrimination.
Calibration of the model was assessed by
comparing the predicted probability of pregnancy
in a category of patients with the observed
percentage of pregnant woman in the same category.
We first categorized the predicted probabilities
of pregnancy in 10 groups, and then
we compared the mean predicted probability
of pregnancy within a group with the observed
probability of the same group.
All statistical analysis was performed by SPSS
program (Version 18; USA). Chi-square and t test
were used for analysis. Also, In order to predict
the result of ICSI, we used logistic regression. The
data were expressed as means ± standard deviation
(SD). Odds ratio (OR) and 95% confidence interval
(95% CI) were also calculated for each factor.
The value of p<0.05 was considered to be statistically
significant.
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