�Syntax Literate : Jurnal Ilmiah Indonesia
p�ISSN: 2541-0849
�e-ISSN : 2548-1398
Vol.
7, Special Issue No. 1, Januari 2022
�
FACTORS AFFECTING THE
OUTCOME OF IN VITRO FERTILIZATION (IVF)
Fayka Putri Poempida, Jimmy Yanuar, Hamdani Lunardhi, Samsulhadi,
Relly Y. Primariawan
Medical Program, Faculty of Medicine, Airlangga University, Indonesia
Email: [email protected], [email protected],
[email protected], [email protected], [email protected]
Abstract
The high prevalence of infertility motivated
researchers to find a solution, henceforth In Vitro Fertilization was invented.
Factors that affect the outcome of IVF may include sperm analysis, maternal
Body Mass Index (BMI), maternal smoking habits, endometriosis, and maternal
age. However, there are ongoing debates about the role of said factors
regarding the outcome of IVF. The objective of this research is to analyze
those factors. This research is a Case-Control study with an analytical
observational design. Data were retrieved from patients� medical records
undergoing IVF in Graha Amerta
Fertility Clinic from January 2019-October 2020. First, the Chi-Square Test
revealed sperm abnormality (p=0.212), Maternal BMI (p=0.427), endometriosis
(p=0.067), meaning there was no connection with the outcome of IVF.
Simultaneously, maternal age (p=0.037) showed a connection with the outcome of
IVF. From the Binary Logistic Regression Test, maternal age 36-40 years old
(p=0.044) affects the outcome of IVF significantly. Concurrently maternal BMI,
endometriosis, and sperm abnormality have p value>0.05 meaning it is
insignificant to the outcome of IVF. This research concluded that sperm
abnormality, maternal BMI, and endometriosis do not affect the outcome of IVF.
There was no data about maternal smoking habits. Whilst maternal age affects
the outcome of IVF. Conclusion: This research concluded that sperm abnormality,
maternal BMI, and endometriosis do not affect the outcome of IVF. There was no
data about maternal smoking habits. Whilst maternal age affects the outcome of
IVF.
Keywords: in vitro
fertilization; good health and well-being; infertility
Introduction
It is estimated there are 15% of reproductive-aged
couples in the world who experienced difficulty when it comes to having
children (1). Infertility and its high prevalence have been the dread of
partners around the globe since the dawn of time. Infertility can be due to a
myriad of causes, be it from the maternal or paternal side. However, the
general public has long believed that infertility was caused solely by women,
causing an unbalanced social burden for women. It is contrary to evidence that
found men have a 20-30% chance of causing infertility, while women contributed
to 50% chance of causing infertility, combined factors are 20-30% (2).
Infertility in women is due to ovulatory disruption, tubal and pelvic disorder,
and uterine disorder. On top of that, the most common causes are ovulatory
disruption and tubal disorders (3). Whereas infertility in men is caused by
semen quality, endocrine disruption, erectile dysfunction, ejaculation
disorder, etc (4). To note, the most frequent causes
of infertility for men lies in semen quality, azoospermia, and faulty intercourse
method (4). Along with the development of technology, In Vitro Fertilization
(IVF) was deemed to be a suitable solution for infertility. The IVF procedure
consists of three crucial steps; ovulation induction, oocyte fertilization, and
embryo development after being transfered to the
uterus (5). Although it was considered a breakthrough, IVF has a high
percentage of failure. It was due to clinical variation in each individual and
couples who undergo IVF. If pregnancy does not happen, then it is considered a
cycle failure. Pregnancy itself is affirmed by measuring serum Beta-hCG level 15 days after ovum retrieval. A chemical
pregnancy is confirmed when serum Beta-hCG levels are
higher than 25 mIU/mL (6). There are a multitude of
factors that may affect the outcome of IVF. Aside from a disturbance during the
processes of IVF, there is the role of clinical variations that includes
maternal Body Mass Index (BMI), maternal smoking habits, endometriosis,
maternal age, and paternal sperm abnormality. Debates are still ongoing on
whether these factors affect the outcome of IVF. Weighing the emotional and
financial burden of a cycle cancellation for the couples, the urgency of
analyzing factors that affect the outcome of IVF is imperative.
Methods
1. Study Design
This research is an analytical
observational study. The purpose for using analytical design is to uncover why
and how a phenomenon occurs through a statistical analysis, such as risk factor
and its effect, and can be used to determine the weight of a risk factor�s
contribution towards its effect. This research�s design is a Case Control study
initiated between January 1, 2019, and October 31, 2020 at Graha
Amerta Fertility Clinic RSUD Dr, Soetomo
and was approved by the RSUD Dr. Soetomo Ethical
Committee. The sampling technique used in this research is total sampling. For
sperm analyses, patients were grouped according to the World Health
Organization (WHO) Semen Parameters Reference (7). Normal sperm analysis was
defined as patients who have none or one abnormal semen parameter, abnormal
sperm analysis has two or more abnormal semen parameters. The semen parameters
are categorized as asthenozoospermia if sperm
concentration is <15x106/mL, oligozoospermia if
sperm motility is <40%, and teratozoospermia if
sperm morphology is <4%. For Body Mass Index (BMI), patients were grouped
according to the World Health Organization (WHO) BMI Classification (8).
Underweight patients were defined as those having a BMI of <18.5 kg/m2,
normal-weight have a BMI of 18.5-24.9 kg/m2, pre-obese have a BMI of 25-29.9
kg/m2, and obese patients have a BMI of ≥30 kg/m2. For maternal smoking
habits, patients were grouped as non-smoker and smoker and/or passive smoker.
For endometriosis, patients were also divided into two groups, being history of
endometriosis and none. For maternal age, patients were divided into three age
groups, 25-35 years old, 36-40 years old, and >40 years old. All data were
collected from medical records at Graha Amerta Fertility Clinic.
2. Patients
The population for this study was 256
patients. Cases were patients who underwent IVF procedure at Graha Amerta Fertility Clinic
with a time period of January 1, 2019-October 31, 2020. This study required
medical records to be complete and within the time period. We excluded medical
records that are incomplete or missing and patients with drop out status. From
the initial total population of 256 patients, after thorough screening
according to the inclusion and exclusion criteria, a sample of 179 patients
were obtained. There were 58 incomplete medical records, and 19 patients with
dropout status. Datas that were collected from
medical records are as follows, sperm abnormality, maternal BMI, maternal
smoking habits, endometriosis, and maternal age. However, during data
collection we did not find any datas regarding maternal
smoking habits. Afterwards, data were categorized into two, successful IVF
procedure and failed IVF procedure.
3. Outcome
The main outcome of the study was a
successful IVF procedure indicated by chemical and clinical pregnancy. This was
achieved by calculating serum Beta-hCG levels at 15
days after ovum retrieval and through imaging with ultrasonography (USG).
Chemical pregnancy is defined when Beta-hCG levels
are >25mIU/mL and clinical pregnancy is defined when a gestational sac is
found during week 4-5 of pregnancy using USG (6).
4. Statistical Analyses
Outcome measures between groups were
distributed and then compared using univariate analysis and bivariate analysis
that is Chi-Square Test and Partial Test with Binary Logistic Regression
Method. Where p<0.05 was considered statistically significant
Result
Research on
factors that affect the outcome of In Vitro Fertilization (IVF) at Graha Amerta
Fertility Clinic of Dr. Soetomo Hospital Surabaya was conducted in February
2021. The data taken in the form of secondary data is the medical record of
patients undergoing IVF procedure at Graha Amerta Fertility Clinic of Dr.
Soetomo Hospital Surabaya period January 2019-October 2020. The population was
256 couples. After adjusting for the criteria of inclusion and exclusion, a
sample of 179 couples was obtained. The number of incomplete medical records is
58 and patients with Drop Out status amount to 19. From the sample obtained, there were 68
couples or 38% who successfully underwent IVF and achieved pregnancy, while
there were 111 couples or 62% who failed to undergo IVF and did not achieve
pregnancy. The data taken from medical records in the form of sperm
abnormalities, BMI of female patients, the habit of female patients smoking,
endometriosis disease in female patients, and the age of female patients.
However, medical records of data on the smoking habits of female patients were
not recorded. The data that has been obtained will be grouped into two
categories, namely IVF successful and IVF failed. From the sample obtained,
there were 68 couples or 38% who successfully underwent IVF and achieved
pregnancy, while there were 111 couples or 62% who failed to undergo IVF and
did not achieve pregnancy. The data taken from medical records in the form of
sperm abnormalities, BMI of female patients, the habit of female patients
smoking, endometriosis disease in female patients, and the age of female
patients. However, medical records of data on the smoking habits of female
patients were not recorded. The data that has been obtained will be grouped
into two categories, namely IVF successful and IVF failed. From the sample
obtained, there were 68 couples or 38% who successfully underwent IVF and
achieved pregnancy, while there were 111 couples or 62% who failed to undergo IVF
and did not achieve pregnancy. The data taken from medical records in the form
of sperm abnormalities, BMI of female patients, the habit of female patients
smoking, endometriosis disease in female patients, and the age of female patients.
However, medical records of data on the smoking habits of female patients were
not recorded. The data that has been obtained will be grouped into two
categories, namely IVF successful and IVF failed. The results of the analysis on the
influence between sperm abnormalities, Body Mass Index (BMI) of female
patients, endometriosis disease of female patients and the age of female
patients against the outcome of IVF at Graha Amerta Fertility Clinic dr.
Soetomo Hospital Surabaya Period 2019-2020 using Binary Logistic Regression
method can be explained as follows.
A. Characteristics of
Research Data
The proportion of each category on variables thought to
affect IVF output can be shown in Table 5.1 as follows.
Table 1
Proportion of Research Data
|
Variable |
n |
Marginal
Percentage |
|
Sperm Abnormalities |
|
|
|
��� Normal |
130 |
72,6% |
|
��� Abnormal |
49 |
27,4% |
|
Women's Body Mass Index |
|
|
|
��� Underweight |
10 |
5,6% |
|
��� Normal |
105 |
58,7% |
|
��� Pre-Obesity |
50 |
27,9% |
|
��� Obesity |
14 |
7,8% |
|
Penyakit
Endometriosis |
|
|
|
��� Existing |
27 |
15,1% |
|
��� None |
152 |
84,9% |
|
Women's Age |
|
|
|
��� 25-35 Years Old |
131 |
73,2% |
|
��� 36-40 Years Old |
36 |
20,1% |
|
��� >40 Years Old |
12 |
6,7% |
|
IVF |
|
|
|
��� Successful cycle |
68 |
38% |
|
��� Failed cycle |
111 |
62% |
Table 5.1 shows the number of patient samples in this study
there were 179 patients at Graha Amerta
Fertility Clinic of Dr. Soetomo Hospital Surabaya for
the period 2019-2020. The percentage of normal sperm abnormalities is 72.6% and
abnormal is 27.4%, meaning most patients have normal sperm analysis results.
The percentage of body mass index (BMI) of women consists of underweight as
much as 5.6%, normal 58.7%, pre-obesity 27.9% and obesity 7.8%. This suggests
that the majority of female patients have normal BMI and some are pre-obese.
The percentage of endometriosis in female patients is 15.1% and the absence of
endometriosis in female patients is 84.9%. This suggests that the majority of
female patients do not have endometriosis. The age of female patients in this
study was divided into 3 with the following percentage, 25-35 years by 73.2%,
36-40 years by 20.1% and >40 years by 6.7% so that the majority of patients
aged 25-35 years. Based on the exterior of IVF, it is known that 38% of
patients with IVF status succeeded and 62% of IVF patients failed.
B. Relationship Analysis
Characteristics of the IVF outcome data based on sperm
abnormalities, female BMI, endometriosis disease and the age of women using
cross tabulation are shown in Table 5.2 as follows.
Tabel 2
Cross Tabulation
|
Variable |
IVF exterior |
|
|||
|
IVF succeeds |
IVF Failed |
P |
|||
|
n |
% |
n |
% |
|
|
|
Sperm Abnormalities |
|
|
|
|
0,212 |
|
��� Normal |
53 |
40,8 |
77 |
59,2 |
|
|
��� Abnormal |
15 |
30,6 |
34 |
69,4 |
|
|
Women's Body Mass Index |
|
|
|
|
0,427 |
|
��� Underweight |
5 |
50,0 |
5 |
50,0 |
|
|
��� Normal |
35 |
33,3 |
70 |
66,7 |
|
|
��� Pre-Obesity |
21 |
42,0 |
29 |
58,0 |
|
|
��� Obesity |
7 |
50,0 |
7 |
50,0 |
|
|
Penyakit
Endometriosis |
|
|
|
|
0,067 |
|
��� Existing |
6 |
22,2 |
21 |
77,8 |
|
|
��� None |
62 |
40,8 |
90 |
59,2 |
|
|
Women's Age |
|
|
|
|
0,037 |
|
��� 25-35 years old |
57 |
43,5 |
74 |
56,5 |
|
|
��� 36-40 years old |
9 |
25,0 |
27 |
75,0 |
|
|
��� >40 years old |
2 |
16,7 |
10 |
83,3 |
|
Table 5.2 shows patients with normal sperm who had IVF
succeeded by 40.8% and IVF failed by 59.2%. Patients with abnormal sperm who
had IVF succeeded by 30.6% and IVF failed by 69.4%. This indicates that
patients with abnormal sperm experience more IVF failure.
Patients with an underweight BMI who experience successful IVF
and IVF fail are the same, both at 50%. Patients with normal BMI who
experienced IVF succeeded by 33.3% and IVF failed by 66.7%. Patients with
pre-obese BMI who had IVF succeeded by 42% and IVF failed by 58%. Patients with
an obese BMI who had a successful IVF cycle, and a failed IVF cycle were the
same, at 50% each. This suggests that women with normal BMI experience more IVF
failure.
Patients with endometriosis who successfully underwent IVF procedure
by 22.2% and failed to undergo IVF procedure by 77.8%. Patients without endometriosis
who had IVF succeeded by 40.8% and IVF failed by 59.2%. This suggests that
patients with endometriosis are more concerned about failing to undergo IVF.
Patients aged 25-35 years who experienced IVF succeeded by
43.5% and IVF failed by 56.5%. Patients aged 36-40 years who experience IVF
succeed 25% and IVF fail 75%. Patients aged >40 who had IVF managed 16.7%
and IVF failed 83.3%. This suggests that more >40-year-old patients who
experience IVF fail.
Analysis of relationships using the Chi Square-Test between
each independent variable and the dependent variable, i.e.
IVF outcome. The analysis used is the Chi Square value with a confidence
interval of 95%. If between an independent and dependent variable produces a p
value < 0.05 then there is a relationship between the independent variable
and the IVF outcome.
Table 5.2 shows that the results of statistical analysis on
variable sperm abnormalities (p=0.212), female BMI (p=0.427), endometriosis
disease (p-0.067) have a p>0.05 value which means there is no relationship
between sperm abnormalities, female BMI, endometriosis disease toward IVF
outcome. While the age of the woman (p = 0.037) has a value of p < 0.05
which means there is a relationship between the age of the woman and the outcome
of IVF.
C. Analysis of Factors
Affecting IVF Outcome (Partial Test)
The influence between independent variables on dependent
variables i.e. the outcome ity
of IVF procedures can be tested using the Binary Logistic Regression Method
with a confidence interval of 95%. If an independent variable produces a p
value < 0.05 then the variable becomes a significant factor in the IVF
output. Partial Test Results are shown in Table 5.3.
Tabel 3
Partial Test
|
Variable |
Pvalue |
OR |
OR
(CI 95%) |
Conclusion |
|
Sperm Abnormalities |
|
|
|
|
|
��� Sperm Abnormalities (Abnormal) |
0,157 |
1,699 |
0,815-3,542 |
Insignificant |
|
Female BMI |
|
|
|
|
|
��� Female BMI (Underweight) |
0,297 |
0,486 |
0,125-1,889 |
Insignificant |
|
Female BMI (Pre-Obesity) |
0,407 |
0,735 |
0,355-1,521 |
Insignificant |
|
Female BMI (Obesity) |
0,365 |
0,582 |
0,181-1,875 |
Insignificant |
|
Penyakit
Endometriosis |
|
|
|
|
|
��� Endometriosis (Existing) |
0,052 |
2,674 |
0,991-7,215 |
Insignificant |
|
Women's Age |
|
|
|
|
|
��� Women's Age (36-40 Years Old) |
0,044 |
2,397 |
1,025-5,605 |
Significant |
|
��� Women's Age (> 40 Years Old) |
0,053 |
4,827 |
0,980-23,777 |
Insignificant |
Note: The first category is used as a reference category
Table 5.3 shows the results of statistical analysis using
partial tests (testing each variable independent of a dependent variable
produces a diverse p value for each category on each variable. Variables that
have a significant effect on the outcome of IVF is the age of women 36-40 years
p (0.044) < p(0.05). This means that the age of
women has a significant role in the outcome of IVF. While variable sperm
abnormalities, female BMI and endometriosis have a p value of > 0.05 is not
significant to the outcome of IVF.
Odds Ratio (OR) analysis is a measure of the relationship of
exposure or risk factors to the occurrence of certain results, this is
calculated from the incidence of disease in the group exposed to risk factors
compared to the incidence of disease in the group that is not exposed to risk
factors. Odds Ratio analysis is used to determine the tendency of certain
categories to the outcome of IVF procedures. Sperm abnormalities (abnormal)
result in an OR value of 1,699 (0.815-3,542) compared to someone who has normal
sperm.
A woman's BMI (underweight) produces an OR value of 0.486
(0.125-1.889) compared to someone with a Normal BMI. A woman's BMI (Pre-Obesity)
produced an OR value of 0.735 (0.355-1.521) compared to someone with a Normal
BMI. A woman's BMI (Obesity) produced an OR value of 0.582 (0.181-1,875)
compared to someone with a Normal BMI. This shows that normal female BMI has
the highest OR number of all BMI groups.
Endometriosis (Existing) produced an OR value of 2,674
(0.991-7,215) compared to someone who did not have endometriosis.
Women (36-40 years old) produce an OR score of 2,397 (1,025-5,605) compared to someone aged 25-35 years. A woman's age (>40 years) produces an OR score of 4,827 (0.980-23,777) compared to someone aged 25-35 years. This means that women with >40 years of age have the highest OR number of all age groups.
Discussion
1.
Sperm Abnormality
Our data demonstrates that sperm abnormality does not have a relationship
with the outcome of IVF procedure, this was shown through the p value of 0.212
from the Chi-Square test. From the Binary Logistic Regression we obtained a p
value of 0.157, meaning it does not have any significant effect on the outcome
of IVF procedure. The Odds Ratio was 1.699 (0.815-3.524) which means there is a
1.699 higher chance of IVF failure in patients with sperm abnormality than
patients with a normal sperm analysis. The abnormality that is studied in this
research is when there are ≥2 abnormal parameters in the analysis result.
We hypothesize that sperm abnormality affects the outcome of IVF. However, from
here we can see that both statistical analyses are in accordance, sperm abnormality
is not related to and does not affect the outcome of IVF. This finding is
aligned with other studies that stated sperm morphology does not affect the
outcome of IVF, and sperm concentration does not affect the outcome of IVF,
this can be due to the ability of certain cell, including cumulus, oolemma, or
zona pellucida to do natural selection on which spermatozoo to fertilize the
egg. However this finding is not aligned with some studies, where the
fertilization rate is good in good sperm motility (>70%) and moderate
(40-70%) but not in poor motility (<40%). It should be taken into
consideration that sperm analysis parameters can vary significantly between
individuals and between samples from each individual. The difference can be due
to procedures on patients with abnormal sperm analysis, such as
Intracytoplasmic Sperm Injection that might alter the outcome of IVF. There is
also the role of the IVF process that is not studied in this research.
2.
Maternal Body Mass Index (BMI)
The Chi-Square test showed the p value�
of maternal BMI is 0.427, meaning there is no relationship between
maternal BMI and IVF outcome. Data from the Binary Logistic Regression also
showed a p value of 0.486 for underweight, 0.735 for pre-obese, and 0.582 for
obese. This means there are no significant effects on the outcome of IVF
procedure. The OR for underweight is 0.486 (0.125-1.889), meaning the risk of
IVF failure for underweight BMI are 0.486 times lower than normal BMI. For
pre-obese, the OR is 0.735 (0.355-1.521) which means there is a 0.735 lower
chance of IVF failure than normal BMI. And the OR for obese BMI is 0.582
(0.181-1.875), meaning the risk for IVF failure is 0.582 times lower than
normal BMI. This shows that normal BMI have the highest risk of IVF failure
than other categories, and what follows is pre-obese, obese, and underweight.
We initially hypothesize that maternal BMI affects IVF outcome. From this
finding, we infer that maternal� BMI is
not related to and does not affect the outcome of IVF. This is inconsistent with
other findings, that women who falls in the obese category have a negative
effect on conception and implantation through various cumulative degeneration
processes like ovulation, oocyte maturation, development of endometrium,
uterine receptivity, and an increase of conception time and spontaneous
abortion. It was established that in pre-obese and obese BMI, the ovarian
response is lower than in normal BMI who received the same stimulation. The
same was found in another study which stated BMI has a significant effect on
IVF outcome with a p value <0.001, and women with pre-obese BMI and obese
have a poor IVF outcome rather than normal BMI. In the same study, pre-obese
women were found to have a higher likelihood of cycle cancellation, whereas
pre-obese and underweight BMI have lesser embryo. A study also found a decline
in blastocyst formation rate in pre-obese and obese BMI, this leads to an
increased chance of embryonic arrest and causing IVF failure. The different
findings can be due to a limited sample size, and the assumption of the best
quality oocyte were used for fertilization in each BMI category. There are
other factors that are not studied including�
Polycistic Ovarian Syndrome (PCOS) and the role of IVF processes,
including the skills of experts in the laboratory and technology used.
3.
Maternal Smoking Habits
We were unable to obtain data regarding maternal smoking habits in the
patients medical records at Graha Amerta Fertility Clinic. Despite that, there
are some findings that should be taken into consideration. Maternal smoking habit
leads to a significant increase of serum FSH and decrease of total Antral
Follicle Count (AFC) than women who do not smoke.� From this, we can infer that smoking habit
affects ovarian reserve and IVF outcome. Other than that, smoking also shortens
the transition toward menopause and causes early menopause about 1-1.5 years
sooner. This is aligned with another study which stated smoking negatively
affects IVF outcome, that includes a decrease in amount and quality of oocyte,
implantation rate, clinical pregnancy rate, and live birth rate. It is also
shown that clinical pregnancy and live birth failure in smokers are 1.5 times
higher, while the risk of spontaneous abortion is twice higher, and the risk of
ectopic pregnancy is >15 times higher than non-smokers. However, there are
some studies that showed the opposite. There are 21.4% of women with cigarette
exposure in the population and no significant effect toward IVF outcome were
found. It was found there are an increase of oocyte quality that is inversely
proportional with smoking habit. The same was found in a study that stated
there are no significant differences in oocyte quality, fertilization rate,
embryo development rate, and pregnancy rate between smokers and non-smokers.
This difference can be due to the assumption of�
the best quality oocyte were used for fertilization in both smokers and
non-smokers. Hence, regarding the effect of maternal smoking habits on the
outcome of IVF should be further studied.
4.
Endometriosis
From the Chi-Square test, we obtained the p value 0.067 for endometriosis,
meaning there are no relationship between endometriosis and IVF outcome. We
also obtained the p value 0.052 of endometriosis from the Binary Logistic
Regression test, this means there are no significant effect of endometriosis
towards IVF outcome. The OR value for endometriosis is 2.674 (0.991-7.215),
meaning women with endometriosis have a 2.674 times higher risk of IVF failure.
Both statistical analysis are in line, endometriosis is not related to and does
not affect the outcome of IVF. This is similar with findings from other
studies, endometriosis is closely related to a decrease in live birth rate than
other infertility diagnosis, in particular with tubal factors. Albeit, we must
highlight the fact that both the relationship and effect of endometriosis on
IVF outcome is clouded with the presence of other infertility diagnosis. In the
previous study, the majority of participants with endometriosis have at least
one other infertility diagnosis, which complicates the assessment of
endometriosis� impact on IVF outcome. In another study, it was stated that
endometriosis does not affect IVF outcome, with the exception of participants
with significant Diminished Ovarian Reserve (DOR) and needs aggressive stimulation
that can affect the amount of oocyte and embryo. However, in another study,
endometriosis showed a negative impact on IVF, this can be inferred from the
total of clinical pregnancy per OPU cycle and by using AFC as an independent
predictor. The negative impact mentioned was mainly caused by Poor Ovarian
Reserve (POR) that is closely related to ovarian endometrioma. The difference
in findings are due to the different severity of the disease, the presence or
absence of endometrioma,� and different therapies
received. Other than that, there is a chance of the non-endometriosis samples
have the disease but undiagnosed. This research also does not study about the
IVF processes.
5.
Maternal Age
The Chi-Square test showed a p value of 0.037 meaning there is a relationship
between maternal age and IVF outcome. And for the Binary Logistic Regression
test, the p value is 0.044 for age group 36-40 years old. The OR results were
found as follows, women in the age group of 36-40 years old have a 2.397 times
higher risk of IVF failure than women aged 25-35 years old. For women aged
>40 years old, the risk increased 4.827 times than 25-35 year-olds.
Therefore, the highest risk of IVF failure for all age group is >40 years
old. The statistical analyses showed aligned results and we can infer that
maternal age have a relationship with and affects IVF outcome. The same is
found in other studies, maternal age have a significant effect on IVF outcome.
This is can be seen through the total cycle that reached embryo transfer stage
with a p value <0.001 and the total oocyte retrieved decreases along with
the increase of age group with a p value <0.001, while the highest amount is
found in age group <30 years old. The increase of age is directly proportional
with a decrease of fertilization rate and has a significant effect on clinical
pregnancy rate, live birth rate, and multiple pregnancies. The study concluded
out of all age groups, <30 year-olds have the best rate for IVF outcome.
Other studies also reported biochemical pregnancy rate, implantation rate,
clinical pregnancy, and live birth are all higher in age group <35 years
old, while in ≥35 year-olds there is an increase wof spontaneous abortion
rate and biochemical pregnancy failure. This phenomenon is explained in a study,
maternal age affects the fertilization rate and embryo development to
blastocyst, causing an increase of aneuploidy rate from 30% in <35 year-olds
to 90% in >44 year-olds. Along with the progressive decrease of ovarian reserve,
maternal age is related to a decrease in oocyte quality caused by damaged
physiological pathways including epigenetic regulation and metabolism.
Conclusion
This research concluded that
maternal age is the most significant factor that affects the outcome of IVF.
Regarding other variables, sperm abnormality, maternal BMI, and endometriosis
do not affect the outcome of IVF significantly. And the data for maternal
smoking habits are insufficient. However, the failure of IVF itself consists of
numerous other factors that include both sides of the couple, hence one-sided
blame should be avoided. Therefore, the failure outcome of IVF should be
evaluated holistically and psychological support for both sides should be
facilitated.
The following are things that should
be taken into consideration regarding this research�s conclusion. There are key
factors that are not studied in this research, which include the implementation
of each step of the procedure, along with the technique and technology used.
Other factors that might contribute, including polycystic ovarian syndrome
(PCOS), diminished ovarian reserve (DOR), and estradiol levels are also not
studied. And last, the limited sample size.
This research has brought about some
suggestions. We highly recommend shifting to digital medical records to
minimize insufficient data and misplacing. Data about maternal smoking habits
should be added progressively in medical records so that its effect can be
further analyzed. For the general public, it is highly discouraged to postpone
pregnancy plans considering the effect of maternal age. For the researcher
hereafter, research with a bigger sample size and a more detailed inclusion and
exclusion criteria must be conducted. We also hope that key factors that are
not studied in this research and the effect of maternal smoking habits can be
reviewed for further study.
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Copyright holder: Fayka Putri Poempida,
Jimmy Yanuar, Hamdani Lunardhi,
Samsulhadi, Relly Y. Primariawan (2022) |
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