Intro
Controlled ovarian hyperstimulation (COH) in
conjunction with intrauterine inseminations (IUI)
are commonly used to treat infertile couples ( 1 ).
The most important indications for IUI are male
subfertility, unexplained infertility, ovulatory dysfunction
and cervical factor infertility ( 2 ). Several
prognostic factors that determine IUI treatment
outcome have been identified and include the
woman’s age, duration of infertility, follicle number,
endometrial thickness, numbers of sperm inseminated,
sperm morphology, progressive motile
sperm count, and cause of infertility ( 3 - 5 ). Tomlinson
et al. ( 6 ) found no differences in age, duration
of infertility, number of follicles, body mass index
(BMI) and sperm quality in the pregnancy rates of patients undergoing IUI. Although IUI with or
without ovarian stimulation is widely used, its success
rate is lower than that of the assisted reproductive
technologies (ART) ( 7 ). Nevertheless, in
comparison to ART controlled ovarian hyperstimulation
combined with intrauterine (COH+IUI)
requires less frequent clinic visits, and is simple,
relatively less invasive and comparatively inexpensive
( 8 ). Regardless of the method of assisted
conception utilized, the couples always desire to
know their chances of success. Thus, identifying
the factors which are influential in the success rate
is highly crucial. The purpose of this study was to
identify the parameters which were most influential
in the success rate using COH+IUI treatment
modality. Using logistic regression, we were able
to devise a mathematical model to predict the success
rate in COH+IUI. The data presented, will
enable the healthcare providers to counsel their
patients about their chances of getting pregnant by
using COH+IUI.
Results
We studied a total of 994 IUI cycles in 803 couples.
Each couple underwent 1.23 ± 0.4 (mean ±
SD) COH+IUI cycles (range: 1-3). Causes for infertility
were: unexplained disorder (290, 29.2%),
male factor (395, 39.7%), combined causes (108,
10.9%), and ovulatory disorder (201, 20.2%). In
our study population, ovulatory disorders included
diminished ovarian reserve, 0.5% (n=1), PCOS,
93.5% (n=188) and hypothalamic amenorrhea, 6%
(n=12).
In our study combined cause including; ovulatory
disorder and male factor 83.3% (n=90), tub
peritoneal and male factor 6.5% (n=7), uterine factor
and ovulatory disorder 3.7% (n=4), uterine factor
and male factor 2.8% (n=3), male factor and
recurrent abortion 1.9% (n=2), ovulatory disorder
and recurrent abortion 0.9% (n=1), uterine factor
& recurrent abortion 0.9% (n=1).
Table 1 compares the demographic characteristics
between pregnant and nonpregnant women.
The pregnancy rate in younger women was significantly
higher than those of older women. In
addition, an infertility duration of ≤4years was
associated with a significantly higher pregnancy
rate (OR:1.5, CI:1.1-2.2, P=0.01). Infertility type
(primary or secondary) did not significantly affect
the outcome. With regards to the diagnosis
of infertility, the highest pregnancy rate (27.8%)
was achieved in couples with combined infertility,
whereas the lowest (13.4%) rate was observed in
couples who suffered from male factor infertility
(P<0.001, Table 1 ).
Characteristics of study patients who underwent IUI
IUI; Intrauterine insemination, OR; Odds ratio, CI; Confidence interval, BMI; Body mass index,†; Values are mean ± SD, §; Reference category
and *; P<0.05 was considered as statistically significant.
The pregnancy rates according to female characteristics
and sperm parameters (according to Strict
Criteria) are summarized in table 2 . Pregnancy
rate was not related to sperm count. There were no
significant differences in total sperm concentration
among the pregnant and nonpregnant study population.
Sperm parameters did not significantly affect
the outcome of COH+IUI treatment. Seminal
volume did not significantly affect the success of
COH+IUI. The total dose of gonadotropin in nonpregnant
women was significantly lower than that
of the pregnant women (P=0.03, Table 2 ).
No significant difference was found between
the two groups in different types of gonadotropins
(data not shown).
Pregnancy outcome, in our study included, there
were 3 (1.8%) ectopic pregnancies, 9 spontaneous
miscarriages of which 5 (3%) occurred during the
first trimester and 4 (2.4%) during the second trimester;
8 (4.8%) cases of blighted ovum, and 145
(87.9%) live births. This corresponded to an ongoing
pregnancy rate of 14.9% (149/994) per IUI
cycle. Of the 165 clinical pregnancies (ongoing
pregnancies and early pregnancy loss), 22 were
twin pregnancies (13.3%). There were 7 (4.2%)
triplet pregnancies, of which one ended with a late
abortion and another terminated at 24 weeks from
which no fetus survived. Of the remaining triplet
pregnancies, two mothers gave birth at 32 and 34
weeks (two healthy sets of one girl and two boys)
and 3 triplet pregnancies were reduced to twins.
The mean birth weight was 1488 ± 395 g and mean
gestational age at delivery was estimated to be 32
weeks for the triplet pregnancies that reduced to
twins. Of these, all neonates were well and healthy.
The mean birth weight of singletons was 3000 ±
525.7 g, twins weighed 2081 ± 557.4 g and triplets
weighed 1588.3 ± 549.1 g. All singletons ended at
28-40 weeks and twins at 30-38 weeks.
We used linear-by-linear test for calculation, the
correlation between age of women and clinical,
ongoing and multiple pregnancies rate. When one
of the variables is ordinal and the other variable is
ordinal or nominal with 2 level, this trend test can
be used ( 12 ).
The proportion of clinical, ongoing and multiple
pregnancies, decreased with age (P=0.041,
P=0.044 and P=0.046, respectively, Table 3 ).
Cycle parameters of the patients who underwent IUI
IUI; Intrauterine insemination, OR; Odds ratio, CI; Confidence interval, FSH; Follicle-stimulating hormone , LH; Luteinizing hormone , †; Values are mean ± SD, §; Reference category,*; Significant statistical differences between the two groups.
Clinical and ongoing pregnancy rates per couple and the frequency of multiple pregnancies for women according to age group
*; Significant statistical differences between the groups.
Of the 145 (87.8%) live births, 139 resulted in
live deliveries at term, 123 (88.5%) patients underwent
caesarean sections and 16 (11.5%) had
normal vaginal deliveries. There were no major
congenital anomalies reported. The live birth rate/
cycle was 14.5% (145/994).
The clinical pregnancy rate per couple was
20.5% (165/803) with an ongoing pregnancy rate
per couple of 18.5% (149/803). Pregnancy rates
per cycle were as follows: first (21%), second
(19.4%) and third (15.3%).
Stepwise multiple linear regression analysis was
performed to compare the association between
dependent (total dose of gonadotropin) and independent
(age, BMI, menstrual irregularities, duration
of infertility, type of infertility, endometrial
thickness, number of dominant follicle, etiology
of infertility) variables. Age (P<0.001), menstrual
irregularities (P<0.001), and duration of infertility
(P=0.01) were the main variables that significantly
influenced the total dose of gonadotropin in couples
undergoing IUI ( Table 4 ).
Variables influencing total dose of gonadotropin in couples undergoing IUI
*; P value multiple regression, IUI; Intrauterine insemination and
SE; Standard error.
According to logistic regression, female age, duration
of infertility, menstrual irregularities, seminal
volume and total dose of gonadotropin were significantly
associated with pregnancy outcome. Higher
female age, prolonged duration of infertility and regular
menstruation showed a negative association with
pregnancy outcome, while seminal volume and total
dose of gonadotropin were positively associated with
pregnancy outcome ( Table 5 ).
Result of logistic regression analysis
OR; Odds ratio, CI; Confidence interval, §; Reference category, *;
Significant statistical differences and AUC; Area under curve.
The ROC curve was used to assess the discriminative
performance of the fitted logistic model ( Fig .1 ).
An AUC equal to 0.5 indicates no discriminative
power whereas an AUC of 1.0 shows a perfect discrimination.
In our study, the AUC for the fitted logistic
model was found to be 0.65 with the 95% CI of
0.60 - 0.70, indicative of a reasonable prognostic potency
for predicting pregnancy following COH+IUI.
With the data obtained, we were able to construct
a formula for calculation of the probability
of pregnancy following COH+IUI as carried out in
our study (see below).
In this formula, the duration of infertility is
the number year each couple has been attempting
to conceive without success. The menstrual
history is=1 if history of menstrual is irregular
and 0 if history of menstrual is regular. The performance
of the prediction model for pregnancy
following COH+IUI was calibrated as shown in
figure 2 . The predictive performance appears to
be acceptable because the 95% confidence intervals
of the observed pregnancy rates overlap
with the predicted pregnancy rate.
Probability of pregnancy after IUI = e ( -2.154 - 0.147 × Durationofinfertility + 0.865 × Menstrualhistory + 0.105 × Volume + 0.022 × ( Total dose of gonadotropin ) ) 1 + e ( -2.154 - 0.147 × Durationofinfertility + 0.865 × Menstrualhistory + 0.105 × Volume + 0.022 × ( Total dose of gonadotropin ) )
ROC curve for assessment of logistic regression discrimimative
preformance.
ROC; Receiver operating characteristic.
Calibration plot, showing the relationship between predicted
and observed rate of pregnancy after intrauterine insemination
(IUI).
Discussion
Among the various parameters that were studied,
female age, duration of infertility, menstrual
irregularities, semen volume, cause of infertility
and the dose of gonadotropin significantly affected
treatment success.
In the current study, we have shown a statistically
significant association between reduced
COH+IUI success rate and increased age. Several
studies have illustrated the decline in pregnancy
with advancing age, ( 13 - 15 ); however, Erdem et
al. ( 15 ) did not find female age to be a prognostic
factor in the prediction of a live birth in ovarian
stimulation and IUI cycles. The current study, IUI
was offered for women over the age of 40 years.
According to studies, woman over the age of 40
are not good candidates for IUI ( 16 , 17 ).
We observed a significant decrease in pregnancy
rate with increased duration of infertility
(OR: 0.8, CI: 0.8-0.9, P<0.001). This result was
also supported by the results observed in a study
by Kamath et al. ( 18 ). In another study ( 17 ), a significantly
higher pregnancy rate (14.2%) was observed
in couples with the duration of infertility of
less than 6 years compared to 6.1% rate for those
with the duration of more than 6 years. Merviel et
al. ( 14 ) did not observe this difference. However,
our findings indicate that the duration of infertility
must be considered when counselted patients on
their chances of a successful pregnancy.
Infertility type (primary or secondary) did not
significantly affect the outcome of COH+IUI the
result of which has been shown in some studies
( 14 , 15 ). Our study found a significant effect of the
total gonadotropin dose on outcome in pregnancies
conceived by COH+IUI (P=0.03). The data were
also evaluated to determine the variables which
may influence the total dose of gonadotropins. It
appears that women with higher age, those with
menstrual irregularities and low number of dominant
follicles as well as those with shorter duration
of infertility should not be given high doses of
gonadotropins. I argue with such a strong statement
based on the findings presented in table 4 . The data
presented are simple correlation data. The only
time you can make such a statement is when for
example you give the same doses of gonadotropins
to women of younger and older age and assess the
outcome.
A total of 17.5% of the recorded clinical pregnancies
after COH+IUI at our center were multiple
pregnancies; no case of hyperstimulation was
documented during the study period. Other studies
have reported an incidence of twins (20%) and
higher-order (39%) multiple pregnancies that were
the result of ovulation induction ( 19 , 20 ). Thus,
centers should choose appropriate stimulation protocols and attempt to achieve a balance between
the search for advanced success rate and suitable
multiple pregnancy rates. The present study, no
significant difference was found in endometrial
thickness between pregnant women and those who
did not become pregnant. This finding is similar to
the result of Kamath et al. ( 18 ).
The information available at present study indicates
that COH+IUI can be considered prior to
more expensive IVF in patients that have combined
(27.8% per cycle) and ovulatory disorder
(20.9% per cycle) infertilities. The success rate
was higher for ovulatory cases and for those who
suffered from more than one etiological factor. The
patients of this group have been diagnosed as the
combination of mild male infertility and PCOS.
Compared result has been reported regarding the
highest success rate in an ovulatory patient ( 13 , 15 ,
17 ). The clinical pregnancy rate was significantly
higher in patients who had irregular menstruation.
All of these patients were diagnosed with PCOS,
according to the cause of infertility as discussed,
the success rate was higher in an ovulatory patient.
When the effect of the infertility etiology was assessed,
there was a significantly lower pregnancy
rate observed in endometriosis patients compared
with women who had unexplained infertility ( 16 ).
Peterson et al. ( 21 ) have found the average pregnancy
rate for unexplained infertility to be 18%.
Our result showed a 13.8% average pregnancy rate
for unexplained infertility; however, Basirat and
Esmaeilzadeh ( 22 ) determined that the etiology of
infertility was not significantly different between
pregnant and nonpregnant women (P=0.63).
Predictive sperm parameters for successful IUI
have been controversial ( 23 , 24 ). Total motile
count (TMC) is a potential predictive factor for
a successful COH+IUI ( 15 ). The pregnancy rates
according to Kamath et al. ( 18 ) were as follows:
a significantly higher pregnancy rate (18.2%) was
observed when TMC was in the range of 10-20
million. TMC at a range of 5-10 million resulted
in a 5.6% pregnancy rate, whereas in cases where
TMC was <5 million, the rate was 2.7%. A TMC
of <1 million was associated with poor pregnancy
rates. When the TMC was <5 million, sperm
morphology appeared to play an important role. A
pregnancy rate of 18.4% was observed with a normal
morphology compared to a rate of <5.4% with
<30% morphology ( 18 ). In our study, although the
sperm analysis data was not recorded after processing,
the data prior to sperm processing was
available. Sperm parameters did not significantly
affect the success of COH+IUI. These results also
confirm the findings achieved by other researchers
( 16 , 25 ). In contrast, other studies have described
several semen parameters that correlated with IUI
outcome, such as the number of motile sperm ( 24 ,
26 ) and normal morphology ( 24 ). In the current
study there was a lower pregnancy rate when the
TMC was in the range of 10-20 million (9.5%).
The pregnancy rate was 17% when the TMC was
>20 million. The pregnancy rate increased when
there was higher normal morphology (OR=1.02,
95% CI:0.7-1.4, Table 2 ). Generally, published
studies have been inconsistent related to the association
between the morphology readings and the
success in IUI ( 21 , 22 ).
We observed four parameters that significantly
affected success: duration of infertility, menstrual
irregularities, seminal volume and total dose
of gonadotropin. In a previous study there were
four prognostic factors: etiology and duration of
infertility, number of treatment cycles, and number
of pre ovulatory follicles ( 16 ). Kamath et al.
( 18 ). found a significant effect of the duration of
infertility and TMC on outcome of pregnancies
conceived by IUI.
Our study was a retrospective, no documents
were available about the number of follicles and
there was a limitation to our study. On the other
hand, we did not have information about semen
quality after processing and it was another ristriction.
Conclusions
With the data obtained, we were able to construct
a formula for to calculate the probability
of pregnancy following COH+IUI as carried out
in the present study. These results suggested that
female age, duration of infertility, cause of infertility,
menstrual irregularities, ejaculatory volume
and total dose of gonadotropin be the most important
prognostic factors in predicting successful
outcome of IUI. A larger study population might
assist with the formulation of a better predictive
model for IUI success. Such information could be
used by couples and clinicians during counseling
participants to arrive at a decision with regards to
their treatment options.
Materials Methods
In this cross-sectional study, we included 994
IUI cycles in 803 couples who referred to the infertility
Institute between 2010-2012. This study
was approved by the Institutional Review Board
of the Royan Institute Research Center and the
Royan Ethics Committee according to the Helsinki
Declaration, signed informed written consent
was obtained from all participants. All couples had
attempted to conceive for at least one year prior
to undergoing COH+IUIs. The women completed
the self-administered questionnaire which was
used to collect data about demographic, menstrual
and obstetrical characteristics. A menstrual interval
shorter than 21 days and longer than 35 days
is defined as menstrual irregularities. Amount of
bleeding is varied ( 9 ).
The study population comprised of all couples
who were candidates for COH+IUI and had diagnoses
of subfertile male infertility, polycystic ovary
syndrome (PCOS), mild or minimal endometriosis
or unexplained infertility and various ovulatory
disorders. Ovulatory disorders included diminished
ovarian reserve, PCOS and hypothalamic amenorrhea.
Subfertile male infertility was defined as per
criteria outlined by Molinaro et al. ( 10 ).
The following evaluations were performed prior
to the initiation of COH+IUI. The women underwent
cycle day 3 hormone evaluation [folliclestimulating
hormone (FSH), luteinizing hormone
(LH), estradiol (E 2 ), thyroid-stimulating hormone
(TSH) and prolactin] and assessment of tubal patency
by using hysterosalpingogram (HSG) and/
or laparoscopy. Tubal patency of at least one tube
was mandatory. In case of either a tubal abnormality
in HSG or dysmenorrhea and dyspareunia, a
laparoscopy was performed.
Inclusion criteria were: male factor, combined
causes, Ovulatory disorder (Pco, diminished ovarian
reserve, and hypothalamic amenorrhea), unexplained
disorder, and all patients with normal TSH
and prolactin levels. The couples with testicular
atrophy, hydrosalpinx, anatomical abnormalities,
infection, uterine fibroids, and systemic disease
were excluded from participation.
All IUI cycles were performed with ovarian
stimulation and included either clomiphene citrate
(Iran Hormone Pharmaceutical Company,
Iran), gonadotropin only, or letrozol (Femara,
Novartis Pharma AG, Switzerland) or the combination
of either clomiphene citrate or letrozol
with gonadotropin. On days 11-12 of the menstrual
cycle, we assessed follicular development
and endometrial thickness by transvaginal
ultrasound. If the endometrial thickness was <7
mm, 4 mg/per day E 2 was administered (2 mg,
Aburaihan Co., Iran) and continued during the
luteal phase. Once a leading follicle of ≥18 mm
was identified, human chorionic gonadotropin
(5,000 IU IM, Pregnyl ® , Darou Pakhsh Pharmaceutical,
Iran) was administored to induce
the final stage of oocyte maturation and a single
IUI was planned 36-38 hours later. If more than
five follicles ≥18 mm in size developed, the cycle
was cancelled.
Semen samples were obtained from patients
who attended the unit for infertility treatments.
Semen samples (n=994) were collected following
3-7 days of sexual abstinence. They were allowed
to liquefy at (add room temperature or 37˚C) for
15-30 minutes and each was subject to an analysis
according to the 2010 World health Organization
(WHO) guidelines ( 11 ). After analysis, samples
were prepared for IUI using to discontinuous density
gradient centrifugation (DGC). For this purpose,
we prepared a two layer gradient consisted of solutions of 100 and 50% Allgrade ® (LifeGobal,
Belgium). The 50% concentration was made by
diluting 100% Allgrade ® with Ham’s F10 (Sigma,
USA) medium. The density gradients were performed
by layering 2 mL of each concentration
into a conical tube (15 mL, Falcon, Becton Dickinson,
NJ, USA). These tubes were pre-incubated for
at least 2 hours in a 37˚C incubator. After semen
liquefaction, 2 mL of ejaculation was layered on
the top of the Allgrade ® gradient and centrifuged
for 30 minutes at 300 x g. After centrifugation, the
sperm was collected at the bottom of the tube by
a clean Pasteur pipette and transferred to a 5 mL
clean tube (Falcon), and washed twice with Ham’s
F10 medium by using centrifugation at 300 x g for
5 minutes. The pellet was resuspended in 1 mL of
Ham’s F10 medium, then the sperm concentration
and motility were evaluated. In our study the sperm
analysis data haven’t been recorded after processing
and sperm analysis data before processing was
available.
Intrauterine inseminations was performed
by a soft catheter (INDOVASIVE, Biorad, India)
with an insemination volume of 0.6 mL.
The IUI catheter was passed gently through the
cervical canal until the tip passed the internal
os. Then, the sperm suspension was deposited
slowly through the uterine cavity. All patients
were provided with luteal support by using cyclogest
according to the treatment physician’s
preference. Clinical pregnancy was defined as
a positive pregnancy test followed by the presence
of a gestational sac visualized by transvaginal
sonography 4weeks after IUI.
In order to build a prediction model, we used
stepwise 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. We check the
performance of the model by the area under the
receiver operating characteristic (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 and the observed percentage
of pregnant woman in that category. We first categorized
the predicted probabilities of pregnancy
in 10 groups, then we compared the mean predicted
probability of pregnancy in that particular category
with the observed probability, i.e. pregnancy
rate in that category.
All statistical analyses were done by using
SPSS software (version 20, USA). Chi-square
and t tests were used for analyses. We performed
univariate logistic regression for each
factor and reported the odds ratio (OR) and 95%
confidence interval (CI). In order to predict the
IUI result, we used multiple logistic regression
analyses. Data were expressed as mean ± standard
deviation (SD). A Pvalue of <0.05 was considered
to be statistically significant.
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