Keywords
pregnancy - congenital anomaly - epidemiological risk factor - ultrasound - perinatal
outcome
Palavras-chave
gestação - anomalias congênitas - fatores epidemiológicos de risco - ultrassom - resultado
perinatal
Introduction
Congenital anomalies (CAs), fetal growth restriction and prematurity are the main
causes of morbidity and mortality during childhood.[1]
[2] The etiologies of many developmental disorders are poorly understood; however, some
risk factors have already been identified, such as environmental or occupational exposures,[3] medications,[4] smoking,[5] the use of illicit drugs[6] and alcohol[7]; maternal diseases, such as pregestational diabetes mellitus[8] and thyroid dysfunction;[9] and congenital infections.[10]
[11]
The European Surveillance of Congenital Anomalies (EUROCAT) recorded a total prevalence
of major CAs of 23.9 per 1,000 births for 2003–2007.[12] According to this network, 80% of those were livebirths, 2.0% were stillbirths or
fetal deaths from 20 weeks gestation, and 17.6% of all cases were terminations of
pregnancy. Among the live births with CAs, 2.5% died during the first week of life.
Congenital heart defects were the most common CA in euploid fetuses, followed by limb
defects, urinary tract malformations and central nervous system anomalies. A better
understanding of the possible risk factors associated with CAs is crucial for the
primary prevention, especially during the preconceptional period.[13] Furthermore, prenatal diagnosis of CAs is important for adequate perinatal management
in a tertiary healthcare service with a multidisciplinary team to decrease morbidity
and mortality rates,[14]
[15]
[16] mainly in countries where the termination of pregnancy is not allowed.[17]
The prenatal ultrasound accuracy to detect CAs ranges in different countries (31–61%),
which seems to be related to the health public policy regarding the prenatal ultrasound
screening programs.[18]
[19]
[20] Since CAs are highly prevalent and associated with adverse perinatal outcomes, an
adequate prenatal diagnosis is imperative for an appropriate perinatal management,
allowing the reduction of perinatal morbidity and mortality rates. Therefore, surveillance
networks of CAs able to point out weak points in prenatal screening policies could
contribute for implementing the required improvements and increase the detection rates
of fetal malformations.
Despite the fact that CAs are a highly reported topic in scientific literature, very
little information is available regarding the potential risk factors associated with
these anomalies and their perinatal outcomes. Thus, the objectives of the present
study were to identify the epidemiological risk factors for CAs and evaluate the impact
of these fetal defects on the perinatal outcome.
Methods
This prospective cohort study comprised 289 high-risk pregnant women whose fetuses
had CAs. All participants were recruited from the group of women admitted to the university
hospital of the Faculdade de Medicina de Ribeirão Preto, São Paulo, Brazil, from September
2011 to July 2013. This 34-bed unit is a Fetal Medicine reference center in Brazil
covering an area of 2 million inhabitants in the north of the State of São Paulo.
This tertiary healthcare service serves ∼ 1,800 high-risk pregnant women per year
within the Brazilian public health system. The aim and methodology of the study was
explained to all recruited women. Voluntary participation was requested, and informed
consent was obtained. This study was approved by the local Ethics Research Committee
(protocol number 6319/2011) in agreement with the current procedures and according
to the internationally acknowledged Strengthening the Reporting of Observational Studies
in Epidemiology (STROBE) criteria. The inclusion criteria were: 1) pregnant women
carrying fetuses with CAs diagnosed at any trimester of pregnancy; and 2) gestational
age determined by the last menstrual period and confirmed by ultrasound exam performed
until 13th week. Following the exclusion of subjects throughout the study, data from
275 pregnant women were used for the current analysis. Fourteen subjects were excluded
by the following reasons: failure to follow-up (n = 9) and inability to obtain all data from medical records (n = 5).
All recruited pregnant women were referred to our service from primary or secondary
public healthcare services after an ultrasound level I demonstrating CAs. After admission
to the institution, the pregnant women were submitted to an ultrasound level III to
properly diagnose the CA. All scans were transabdominal, using a 4–8 MHz probe (Voluson
730 Expert, GE Medical Systems, Milwaukee, WI, USA) operated by experienced sonographers
who had the appropriate Fetal Medicine Certificate of Competence in the fetal anomaly
assessment. During the prenatal follow-up, the pregnant women had genetic counselling,
psychological support, and additional appointments with a multidisciplinary team (neonatologists,
pediatric surgeons, neurosurgeons, cardiovascular surgeons, and anesthesiologists).
Termination of pregnancy was not performed, since it is not allowed by the country's
laws (except in the case of anencephaly). Maternal demographic characteristics and
ultrasonographic findings were recorded in a computer database. Details regarding
pregnancy and neonatal outcomes were added to the database as soon as they became
available.
Definitions and Outcomes
For data analysis, CAs were divided into seven groups according to type: 1) central
nervous system (CNS); 2) urinary tract (UT); 3) heart and great vessels (HGV); 4)
gastrointestinal tract/abdominal wall (GI); 5) musculoskeletal (ME); (6) isolated
fetal hydrops; and 7) others. This latter category comprised fetuses with multiple
malformations, congenital diaphragmatic hernia, and tumors.
The primary outcome was CA. The following maternal variables were considered as potential
risk factors for each group of CA: age (< 19 years, 20–35 and > 35 years); skin color
(white or non-white); level of education (≤ 8 years, > 8 years); professional activity
(with or without); body mass index (normal, overweight or obese); smoking; use of
medications with teratogenic potential; regular folic acid supplementation; parity
(primigravida, secundigravida, multigravida); history of previous miscarriage; and
chronic diseases.
Secondary outcomes included: fetal growth restriction (estimated fetal weight < 10th
percentile for the gestational age);[21] fetal distress followed by cesarean section; premature rupture of membranes; oligohydramnios
or polyhydramnios (single deepest pocket < 5th percentile or > 95th for the gestational
age);[22] preterm delivery (birth before 37 weeks of gestation); stillbirth (fetal death after
20 weeks of gestation); cesarean section; low birth weight (below 2,500 g); Apgar
score < 7 at the 1st and 5th minutes; need for assisted ventilation at birth; neonatal
infection; need for surgical treatment; and early neonatal death.
Statistical Analysis
A sample size of 250 fetuses (subjects) was estimated based on the prevalence of CAs
of 1.5% in the general population, and the detection rate of 3.0% in the high-risk
population, considering a significance level of 5% and power of 80%. However, considering
a 10% of failure to follow-up, a sample size of 275 would be enough to perform this
study.
Mean, standard deviation (SD), median, minimum and maximum were used to describe the
variable hospitalization time. Percentages were used to describe qualitative variables.
The Chi-square (χ2) test was applied to verify the association between the categorical variables and
CAs. Simple and multiple logistic regression analyses were used to determine the effects
of maternal characteristics on the incidence of CAs at birth and the influence of
types of CA on the perinatal outcomes.[23] The Kruskal-Wallis or Mann-Whitney tests were applied to verify the differences
in secondary outcomes among CA groups. All analyses were performed using the SAS software
version 9.0 (Cary, North Carolina, USA). A p < 0.05 was considered statistically significant.
Results
The general prevalence of CAs was of 2.4%. The following groups of birth defects were
identified: CNS (n = 78, 28.4%); UT (n = 59, 21.5%); HGV (n = 32, 11.6%); GI (n = 38, 13.8%); ME (n = 18, 6.6%); hydrops (n = 15, 54%); and others (n = 35, 12.7%). [Table 1] shows the maternal demographic variables taking into account different CA groups.
We observed a higher rate of pregnant women with higher levels of education (> 8 years)
in the HGV defects and hydrops groups (p = 0.041). Other maternal variables did not differ significantly among the CA groups;
however, some findings should be highlighted. There were more teenagers in the GI
and ME groups. The proportions of women who used medications were higher in the CNS
and UT groups. Furthermore, we noticed higher rates of pregnant women smokers in the
GI and ME groups. In addition, folic acid supplementation was less common in the GI
group; there was a higher rate of multigravida in the HGV group, and a higher rate
of women with previous miscarriages in the hydrops group.
Table 1
Maternal demographic variables taking into account different groups of congenital
anomalies
|
Type of congenital anomaly
|
p
|
|
Central nervous system (%)
|
Urinary tract (%)
|
Heart and great vessels (%)
|
Gastrointestinal/ abdominal wall (%)
|
Musculoskeletal (%)
|
Isolated hydrops (%)
|
Others (%)
|
|
Maternal age (mean ± SD)
|
25.55 ± 6.0
|
26.24 ± 6.6
|
27.23 ± 7.0
|
23.32 ± 7.8
|
24.50 ± 5.8
|
28.47 ± 5.1
|
28.07 ± 7.4
|
|
|
≤ 19 years
|
14.1
|
18.6
|
12.5
|
28.9
|
27.8
|
0.0
|
8.6
|
NS
|
|
20–35 years
|
78.2
|
69.5
|
68.7
|
63.2
|
66.7
|
93.3
|
71.4
|
|
> 35 years
|
7.7
|
11.9
|
18.8
|
7.9
|
5.5
|
6.7
|
20.0
|
|
Skin color
|
|
White
|
88.5
|
79.7
|
75.0
|
76.3
|
72.2
|
86.7
|
77.1
|
NS
|
|
Non-white
|
11.5
|
20.3
|
25.0
|
23.7
|
27.8
|
13.3
|
22.9
|
|
Level of education
|
|
≤ 8 years
|
44.9
|
61.0
|
34.4
|
60.5
|
55.6
|
26.7
|
40.0
|
0.041
|
|
> 8 years
|
55.1
|
39.0
|
65.6
|
39.5
|
44.4
|
73.3
|
60.0
|
|
Occupation
|
|
Without
|
53.8
|
67.8
|
43.7
|
65.8
|
72.2
|
40.0
|
51.4
|
NS
|
|
With
|
46.2
|
32.2
|
56.3
|
34.2
|
27.8
|
60.0
|
48.6
|
|
Chronic diseases
|
|
Yes
|
15.4
|
20.3
|
12.5
|
13.2
|
22.2
|
0.0
|
25.7
|
NS
|
|
No
|
84.6
|
79.7
|
87.5
|
86.8
|
77.8
|
100.0
|
74.3
|
|
Smoking
|
|
Yes
|
11.5
|
6.8
|
9.4
|
18.4
|
27.8
|
20.0
|
2.8
|
NS
|
|
No
|
88.5
|
93.2
|
90.6
|
81.6
|
72.2
|
80.0
|
97.2
|
|
Body mass index (kg/m2)
|
|
Normal
|
56.4
|
54.3
|
62.5
|
52.6
|
44.4
|
40.0
|
42.9
|
NS
|
|
Overweight
|
24.3
|
28.8
|
28.1
|
34.2
|
44.4
|
40.0
|
40.0
|
|
Obese
|
19.3
|
16.9
|
9.4
|
13.2
|
11.2
|
20.0
|
17.1
|
|
Medication use
|
|
Yes
|
14.1
|
8.5
|
9.4
|
10.5
|
5.6
|
6.7
|
14.3
|
NS
|
|
No
|
85.9
|
91.5
|
90.6
|
89.5
|
94.4
|
93.3
|
85.7
|
|
Folic acid supplementation
|
|
Yes
|
32.1
|
25.4
|
37.5
|
13.2
|
38.9
|
20.0
|
31.4
|
NS
|
|
No
|
67.9
|
74.6
|
62.5
|
86.8
|
61.1
|
80.0
|
68.6
|
|
Parity
|
|
Primigravida
|
46.2
|
35.6
|
31.2
|
42.1
|
38.9
|
33.3
|
37.1
|
NS
|
|
Secundigravida
|
28.2
|
28.8
|
21.9
|
23.7
|
22.2
|
46.7
|
31.4
|
|
Multigravida
|
25.6
|
35.6
|
48.9
|
34.2
|
38.9
|
20.0
|
31.5
|
|
Previous miscarriage
|
|
Yes
|
14.1
|
20.3
|
21.9
|
26.3
|
22.2
|
33.3
|
22.9
|
NS
|
|
No
|
85.9
|
79.7
|
78.1
|
73.7
|
77.8
|
66.7
|
77.1
|
Abbreviation: NS, non-significant; SD, standard deviation.
[Table 2] shows the concordance between the ultrasound levels I III performed by a Maternal-Fetal
Medicine specialist. The highest concordance occurred in the GI defect group (84.2%),
and the lowest concordance was detected in the HGV defect group (28.1%).
Table 2
Concordance between the ultrasound scan performed by non-specialists (level I) and
Maternal-Fetal Medicine specialists (level III)
|
Type of congenital anomaly
|
|
Central nervous system
|
Urinary tract
|
Heart and great vessels
|
Gastrointestinal/ abdominal wall
|
Musculoskeletal
|
Isolated hydrops
|
Others
|
|
Number of cases
|
78
|
59
|
32
|
38
|
18
|
17
|
35
|
|
Concordance (%)
|
70.5
|
59.3
|
28.1
|
84.2
|
38.9
|
66.7
|
68.6
|
|
Discordance (%)
|
29.5
|
40.7
|
71.9
|
15.8
|
61.1
|
33.3
|
31.4
|
Multiple logistic regression analyses were applied to determine the effects of maternal
parameters on the prevalence of a specific type of CA. Non-white skin color decreased
the risk of CNS anomalies by nearly 60% (OR: 0.43; 95%CI: 0.19–0.97; p = 0.04). High levels of education decreased the risk of UT defects by almost 50%
(OR: 0.52; 95%CI: 0.29–0.94; p = 0.03). Primigravida showed a reduced risk of having a newborn with HGV defects
(OR: 0.26; 95%CI: 0.08–0.80; p = 0.02). In addition, maternal age > 19 years and regular folic acid supplementation
were associated with decreased risk of GI malformations by nearly 60% (OR: 0.42; 95%CI:
0.19–0.95; p = 0.04) and 65% (OR: 0.34; 95%CI: 0.13–0.91; p = 0.03) respectively. Smoking increased the risk of ME anomalies by 3 times (OR:
3.28; 95%CI: 1.08–9.90; p = 0.04). Furthermore, history of previous miscarriage increased the risk of hydrops
by almost 8 times (OR: 7.65; 95%CI: 1.40–41.66; p = 0.02).
[Table 3] shows the perinatal outcomes considering different CA groups. The following perinatal
complications were associated with CAs: polyhydramnios; oligohydramnios; stillbirth;
preterm delivery; cesarean section; low birth weight; need for pressure support; neonatal
infection; need for surgical treatment; and early neonatal death. Polyhydramnios was
more common in the ME and hydrops groups specifically, with a prevalence of 38.9%
(OR: 4.46; 95%CI: 1.09–18.29) and 40% (OR: 4.67; 95%CI: 1.07–20.32) respectively.
On the other hand, oligohydramnios was more common in the UT malformation group (OR:
12.55; 95%CI: 1.58–99.38). The prevalence of stillbirth was high in all CA groups,
mainly in the hydrops (OR: 27.13; 95%CI: 2.90–253.47). Preterm delivery was very common
in all CA groups (18.7–86.7%), especially in the GI defects (OR: 5.96; 95%CI: 1.99–17.84)
and hydrops groups (OR: 28.16; 95%CI: 4.98–159.38). The prevalence of low birth weight
was high in all CA groups, mainly in the GI defects group (OR: 2.08; 95%CI: 1.08–27.83),
the ME anomalies group (OR: 3.34; 95%CI: 1.34–38.52) and in the others group (OR:
1.98; 95%CI: 1.05–7.25). Additionally, Apgar score < 7 at the 5th minute was high
in all types of CA, especially in the UT malformations group (OR: 5.44; 95%CI: 1.15–25.64),
the ME anomalies group (OR: 8.70; 95%CI: 1.51–50.28) and the hydrops group (OR: 14.50;
95%CI: 1.98–106.44). Infections were less prevalent in the CNS defects group (OR:
0.26; 95%CI: 0.11–0.65), as well as in the UT anomalies group (OR: 0.13; 95%CI: 0.04–0.39)
and in the others group (OR: 0.30; 95%CI: 0.10–0.89). Surgeries were less necessary
in the UT anomalies group (OR: 0.24; 95%CI: 0.09–0.60), in the ME group (OR: 0.21;
95%CI: 0.06–0.81), and in the others group (OR: 0.21; 95%CI: 0.07–0.62). In contrast,
it was more common in the GI group (OR: 6.74; 95%CI: 1.68–26.96). Early neonatal death
rate was high in all CA groups; however, it was significantly less common in the CNS
defects group (OR: 0.20; 95%CI: 0.07–0.55).
Table 3
Perinatal outcomes considering different groups of congenital anomalies
|
Type of congenital anomaly
|
p
|
|
Central nervous system
(%)
|
Urinary tract
(%)
|
Heart and great vessels
(%)
|
Gastrointestinal/ abdominal wall (%)
|
Musculoskeletal (%)
|
Isolated hydrops
(%)
|
Others
(%)
|
|
Fetal growth restriction
|
3.8
|
1.7
|
6.3
|
2.6
|
11.1
|
6.7
|
14.3
|
NS
|
|
Fetal distress
|
2.6
|
1.7
|
3.1
|
5.3
|
0
|
0
|
14.3
|
NS
|
|
Premature rupture of membranes
|
10.3
|
11.9
|
3.1
|
18.4
|
22.2
|
20.0
|
17.1
|
NS
|
|
Polyhydramnios
|
10.3
|
5.1
|
12.5
|
13.2
|
38.9
|
40.0
|
20.0
|
< 0.01
|
|
Oligohydramnios
|
3.8
|
28.8
|
3.1
|
13.2
|
5.6
|
13.3
|
11.4
|
< 0.01
|
|
Fetal death
|
9.0
|
6.8
|
3.1
|
7.9
|
11.1
|
46.7
|
8.6
|
< 0.01
|
|
Preterm delivery
|
23.1
|
33.9
|
18.7
|
57.9
|
33.3
|
86.7
|
31.4
|
< 0.01
|
|
Cesarean section
|
75.6
|
39.0
|
81.3
|
84.2
|
72.2
|
46.7
|
60.0
|
< 0.01
|
|
Low birth weight
|
24.4
|
20.3
|
21.9
|
42.1
|
66.7
|
40.0
|
42.9
|
< 0.01
|
|
Apgar < 7 at the 1st minute
|
35.2
|
34.5
|
29.0
|
40.0
|
68.7
|
62.5
|
43.7
|
NS
|
|
Apgar < 7 at the 5th minute
|
12.7
|
27.3
|
6.5
|
20.0
|
37.5
|
50.0
|
21.9
|
0.02
|
|
Need for assisted ventilation
|
43.7
|
47.3
|
38.7
|
71.4
|
68.7
|
62.5
|
56.3
|
NS
|
|
Neonatal infection
|
19.7
|
10.9
|
48.4
|
48.6
|
25.0
|
12.5
|
21.9
|
< 0.01
|
|
Need for surgical treatment
|
54.9
|
27.3
|
61.3
|
91.4
|
25.0
|
37.5
|
25.0
|
< 0.01
|
|
Early neonatal death
|
12.7
|
25.5
|
41.9
|
37.1
|
62.5
|
50.0
|
28.1
|
< 0.01
|
Abbreviation: NS, non-significant.
[Table 4] shows the hospitalization time of all CA groups. In general, the hospitalization
time was higher in the subgroups of GI anomalies and HGV defects (p < 0.01). Hospitalization time was also higher in the subgroups in which surgery was
required or had neonatal infection. On the other hand, hospitalization time was lower
in the subgroups with Apgar scores < 7 at the 5th minute, probably because of their
high mortality rate.
Table 4
Hospitalization time of live newborns according to the congenital anomaly group and
their perinatal outcomes
|
Hospitalization time (days)
|
p
|
|
n[*]
|
Mean
|
Standard deviation
|
Minimum
|
Median
|
Maximum
|
|
Congenital anomaly
|
|
Central nervous system
|
71
|
24.9
|
31.9
|
1.0
|
14.0
|
201.0
|
|
|
Heart and great vessels
|
31
|
28.3
|
35.5
|
1.0
|
12.0
|
130.0
|
< 0.01[§]
|
|
Gastrointestinal/ abdominal wall
|
35
|
34.5
|
36.2
|
1.0
|
26.0
|
160.0
|
|
Urinary tract
|
55
|
12.8
|
27.2
|
1.0
|
3.0
|
150.0
|
|
Isolated hydrops
|
8
|
9.9
|
12.6
|
1.0
|
5.0
|
36.0
|
|
Musculoskeletal
|
16
|
20.9
|
42.4
|
1.0
|
4.0
|
152.0
|
|
Others
|
32
|
24.8
|
51.1
|
1.0
|
9.0
|
274.0
|
|
Early neonatal death
|
|
No
|
176
|
28.0
|
37.5
|
1.0
|
14.0
|
274.0
|
< 0.01[ʃ]
|
|
Yes
|
72
|
11.6
|
27.9
|
1.0
|
1.0
|
160.0
|
|
Need for surgical treatment
|
|
No
|
128
|
10.1
|
26.5
|
1.0
|
4.0
|
274.0
|
< 0.01[ʃ]
|
|
Yes
|
120
|
37.3
|
38.9
|
1.0
|
24.0
|
201.0
|
|
Neonatal infection
|
|
No
|
184
|
14.3
|
23.7
|
1.0
|
6.0
|
150.0
|
< 0.01[ʃ]
|
|
Yes
|
64
|
49.0
|
49.7
|
1.0
|
33.5
|
274.0
|
|
Apgar score at the 5th minute
|
|
< 7
|
50
|
19.4
|
47.6
|
1.0
|
1.0
|
274.0
|
< 0.01[ʃ]
|
|
≥ 7
|
198
|
24.2
|
32.1
|
1.0
|
12.0
|
201.0
|
* Number of live newborns;
§ Kruskal-Wallis test;
ʃ Mann-Whitney test.
Discussion
In the present study, the prevalence of CAs was of 2.4%, considering ∼ 10 thousand
ultrasound scans performed at our institution between 2011 and 2013. This rate is
similar to the one from Dolk et al,[12] who described the prevalence of CAs in Europe. Central nervous system anomalies,
including open neural tube defects, were the most common CA detected in fetuses, a
finding similar to those reported on other studies. The majority of the CAs of the
fetal CNS is identified by the second-trimester ultrasound at 20–24 weeks of gestation,
which makes them the most common.[24] Furthermore, CNS defect was a CA group with high concordance (71%) between ultrasound
scans performed by non-specialists (level I) and Maternal-Fetal Medicine specialists
(level III).
Urinary tract malformation constitutes ∼ 20% of all CAs, which is coincident with
the data presented here.[18] However, the concordance between the diagnoses made by sonographers with different
levels of experience is lower than CNS anomalies. A possible explanation for this
result would be that up to 80% of UT malformations can be solved spontaneously during
fetal life, or worsened with advancing gestational age and impaired fetal renal function.[25] Multicystic dysplasia might not be identified in the second trimester scan; on the
other hand, renal agenesis and lower urinary tract obstruction can be identified early,
while milder obstructions are diagnosed later.[26]
In the present study, the prevalence of congenital heart disease was of 11.6%, which
is in agreement with the findings of studies conducted in tertiary reference centers.
However, the analysis of this CA group showed the lowest concordance (28.1%) between
ultrasound scans level I and III. This can be explained by the difficulty of non-specialist
sonographers in achieving a proper examination of the fetal heart and great vessels.
It is well known that the detection rates of HGV defects increase with the examiner's
ultrasound experience and training, and with the adoption of a systematic ultrasound
examination of the fetal heart.[27]
[28]
The prevalence of GI malformations was coincident with the data presented in other
studies (13.8%).[29] Furthermore, GI anomaly was the CA group with the highest concordance (84%) between
findings of ultrasound scans level I and III. The most common GI malformations were
abdominal wall defects, which can be easily identified by ultrasound scan performed
after 13 weeks of gestation. In addition, esophageal atresia and small bowel obstructions
are readily identified in the third trimester due to the presence of polyhydramnios.
Because of the multifactorial etiology of CAs, we proposed to assess the effect of
maternal demographic factors on their occurrence; however few factors showed to have
a positive correlation with CAs. This result is probably due to the small sample size.
Moreover, the appropriate process of gathering and measuring information on targeted
variables, such as skin color, smoking, use of medications and folic acid supplementation
is not very reliable because of two main reasons: the occurrence of a mixed population
in our country, and the low socioeconomic status of our patients.
According to our data, parity was a maternal risk factor for HGV defects. Multigravida
have a higher risk of having children affected by this type of CA compared with primigravida
or secundigravida. This finding is similar to the Csermely et al[30] study that assessed 21,494 fetuses with different isolated malformations, and compared
them to 34,311 normal controls. The authors showed that multiparity was a significant
risk factor for the following five types of HGV anomalies: ventricular septal defect;
ostium secundum atrial septal defect; persistence of arteriosus ductus; conotruncal
cardiac defect; and ventricular outflow tract obstructions.
Smoking was a risk factor for ME anomalies. Overall, the prevalence of CAs does not
seem to be increased among children of women who smoked during pregnancy. However,
Morales-Suárez-Varela et al[31] demonstrated that pregnant women who did not smoke but used nicotine patches had
the risk of having children with ME anomalies (95%CI: 1.53–4.52) increased by 2.6
times. The authors suggested that nicotine can interfere with the mechanism of genomic
"imprinting" and lead to this type of CA. Another finding of the present study was
the history of previous miscarriage as a risk factor for hydrops. It is well known
that a large proportion of miscarriages is caused by genetic abnormalities, and their
recurrence could be one of the causes of hydrops in the current pregnancy.[32]
There were two variables that provided protection against CAs. Maternal age > 19 years
and folic acid supplementation were associated with a decreased risk of GI malformations.
Eckmann-Scholz et al[33] found that teenagers have an increased risk of having newborns with GI malformations,
especially gastroschisis. This can be explained by the fact that pregnancy during
adolescence may be associated with several risk conditions for CAs, such as use of
illicit drugs, alcoholism, and nutritional deficiencies.[33] Many studies point out to the effective prevention of fetal CAs with the regular
folic acid supplementation mainly open neural tube defects.[12]
[34]
Changes of amniotic volume fluid were more frequent in fetuses with skeletal dysplasia
and isolated hydrops. In skeletal malformations, a small thorax causes increased intrathoracic
pressure and decreased fetal swallowing.[32] In hydropic fetuses, polyhydramnios may be a consequence of increased urine production.[32] In contrast, oligohydramnios was more common in the UT group, in which urine production
is impaired by the existence of dysplastic kidneys or distal obstructions of the UT.[26]
In the present study, fetal death rates were high for all types of CAs compared with
the general population due to the severity of malformations.[35] In addition, preterm delivery rates were very high mainly for the GI anomalies and
hydrops groups because of spontaneous labor caused by polyhydramnios or suspicion
of ischemic bowel and compromised fetal wellbeing respectively. As a consequence,
the elective cesarean section rates were also increased for those reasons, and also
to obtain a successful perinatal management of neonates through delivery planning
with a multi-professional team.
Neonatal adverse outcomes were extremely common in all CA groups. Hospitalization
time was increased for all of them as a result of preterm delivery, low birth weight,
Apgar score < 7 at the 5th minute, neonatal infection, and need for surgical treatment.
Neonatal death rates were significantly increased in all CA groups as a consequence
of all perinatal complications previously described. The causes behind the low Apgar
scores may be listed as difficult fetal extraction at the cesarean section or labor
dystocia in skeletal dysplasia and hydrops; respiratory distress due to pulmonary
hypoplasia, particularly in UT anomalies linked to oligohydramnios; and the presence
of a small thorax or a large pleural fluid collection possible in ME CAs and hydrops
respectively. Neonatal infections were more common among fetuses with HGS or GI anomalies
because they usually require surgical treatments, blood vessel catheterization for
parenteral nutrition, blood transfusions, and medications or fluid administration.
In summary, it was possible to identify several maternal risk factors for CAs. High
rates of adverse perinatal outcomes were presented in all CA groups, and may differ
according to the type of CA considered.
