Skip to main content
NCBI home page
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease logoLink to Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
. 2025 Apr 10;14(8):e038798. doi: 10.1161/JAHA.124.038798

Congenital Heart Defects and Apgar Score at Birth, a Nationwide Study

Briyanth Ravichandran 1,2,✉, Tine B Henriksen 1,3, Vibeke E Hjortdal 4,5, John R Ostergaard 6, Niels B Matthiesen 1,3
PMCID: PMC12132839  PMID: 40207504

Abstract

Background

Low Apgar scores have been associated with an increased risk of brain injury and neurodevelopmental disorders in newborns with congenital heart defects (CHDs). However, the relation between CHD subtypes and low Apgar scores remains unknown. This study aimed to assess the association between major subtypes of CHD and low (<7) Apgar scores at 5 minutes.

Methods and Results

This population‐based study included 1 040 474 liveborn singletons in Denmark from 1997 to 2013. The association between CHD and low Apgar scores was estimated by confounder‐adjusted, multivariable logistic regression. In mediation analyses, the underlying mechanisms were examined. Low Apgar scores were present in 3.0% of newborns with CHD and in 0.7% of newborns without CHD. Overall, CHD was associated with an increased risk of a low Apgar score (adjusted odds ratio, 2.5 [95% CI, 2.1–3.0]). CHD subtypes associated with the highest risks were anomalous pulmonary venous return (adjusted odds ratio, 5.7 [95% CI, 2.2–14.9]), hypoplastic left heart syndrome (adjusted odds ratio, 5.1 [95% CI, 2.2–11.8]), and transposition of the great arteries (adjusted odds ratio, 3.5 [95% CI, 1.7–7.4]). In mediation analyses, preterm birth explained 25.2% (95% CI, 11.8–38.6) of the association between CHD and low Apgar scores.

Conclusions

Nearly all CHD subtypes were associated with an increased risk of a low Apgar score. The association was most pronounced in severe and potentially cyanotic types of CHD. These findings suggest that CHD is associated with a complicated fetal‐to‐neonatal transition and highlight the potential for improvements of this process in infants with CHD.

Keywords: Apgar score, congenital heart disease, neonatology, pediatric cardiology

Subject Categories: Pediatrics, Risk Factors, Congenital Heart Disease

Nonstandard Abbreviations and Acronyms

GA

gestational age

Clinical Perspective.

What Is New?

  • Only a few studies have assessed the association between congenital heart defects (CHDs) and a low (<7) Apgar score after birth.

  • This nationwide population‐based study evaluates the association between specific subtypes of CHD and a low Apgar score 5 minutes after birth.

  • The present study is the first study to perform mediation analyses on the association between CHD and a low Apgar score 5 minutes after birth.

What Are the Clinical Implications?

  • The present study indicated that close to all subtypes of CHD were associated with an increased risk of a low Apgar score 5 minutes after birth, and the association increased by severity of CHD.

  • Preterm birth explained 25% of the association between CHD and a low Apgar score 5 minutes after birth; however, head circumference, birth weight, or placental weight did not mediate any part of the association.

  • The present study raises the possibility that optimizing the neonatal transition in children with CHD may hold the potential to improve perinatal, neonatal, and long‐term neurodevelopment in this patient group.

Congenital heart defects (CHDs) remain the largest group of major congenital anomalies with a prevalence of approximately 6 infants per 1000 live births. 1 The number of deaths related to CHD has decreased in recent years due to improved clinical practice, 2 and approximately 50% of infants with CHD are diagnosed prenatally. 3 Despite early diagnosis and surgery, CHD continues to be a common cause of childhood morbidity, including neurodevelopmental disorders and death. 4 , 5 , 6 , 7 In fact, up to half of the children with CHD have been reported to exhibit signs of neurologic impairments. 8 , 9 , 10 , 11

The Apgar score is an internationally recognized scoring system for a structured clinical assessment of the physical condition of the newborn during the fetal‐to‐neonatal transition and evaluates 5 physiological characteristics including appearance (color), pulse (heart rate), grimace (reflex irritability), activity (muscle tone), and respiration (respiratory effort). Three of these are measures of neurology (tone, reflexes, respiration), and 2 are related to the circulation (heart rate, color). Each characteristic is routinely assigned a score of 0 to 2 after 1, 5, and 10 minutes (Table 1). 12 A total score at or above 7 is considered normal at 5 minutes. 13 Whereas the Apgar score is known to have a suboptimal predictive value for the subsequent development of neurologic outcomes at the individual level, a low Apgar of <7 at 5 minutes has been linked to low IQ scores; poor school performances; and an increased risk of cerebral palsy, epilepsy, and intellectual disability in children. 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 The Apgar score is the most common and widely available measure of the fetal‐to‐neonatal transition.

Table 1.

Overview of the Apgar Scoring System

Score 0 1 2
Appearance Pale Cyanosis Pink
Pulse 0 <100 ≥100
Reflexes No response Grimace Coughs, sneezes, or cries with stimulation
Activity Flaccid Some flexing of extremities Active
Respiration Apneic Irregular, shallow breathing Strong cry
Open in a new tab

The Apgar score is based on 5 parameters: appearance, pulse, reflexes, activity, and respiration. In each category, the newborn is given a score from 0 to 2 after 1, 5, and 10 min. The range of the total score is 0 to 10. The variables appearance and pulse reflect the circulatory status of the newborn, while reflexes, activity, and respiration reflect the neurologic condition of the newborn. 12

Previous studies have documented that fetuses and newborns with CHD exhibit signs of delayed brain maturation, which may render the children more susceptible to brain injury from influences during birth and the neonatal transition. 22 , 23 In line with this, a few studies have indicated associations between a low Apgar score after 5 minutes, brain injury, and neurodevelopmental disorders in this large group of children. 24 , 25 Moreover, CHD has been associated with numerous other factors associated with low Apgar scores, including preeclampsia; preterm birth; and impaired fetal, placental, and prenatal cerebral growth. 26 , 27 , 28 , 29 However, the relation between specific subtypes of CHD and a low Apgar score remains unknown. The identification of subtypes of CHD at risk for complicated fetal‐to‐neonatal transition holds the potential to improve both perinatal and neonatal care as well as long‐term neurodevelopment in this patient group.

This study aims to estimate the association between the major subtypes of CHD and the risk of low Apgar score 5 minutes after birth in a Danish nationwide sample. We hypothesize that infants with CHD have an increased risk of low Apgar scores at birth compared with newborns without CHD. Moreover, we hypothesize that newborns with the most severe and potentially cyanotic types of CHD, including hypoplastic left heart syndrome, other single‐ventricle defects, tetralogy of Fallot, and transposition of the great arteries will be associated with the highest risk of low Apgar scores. Furthermore, through mediation analyses, we aimed to assess the mechanisms underlying a potential association between CHD and low Apgar score 5 minutes after birth.

Methods

Due to data protection policies at Statistics Denmark, the data from the present study cannot be made available to third parties. Analytic methods, including Stata code, are available from the last author upon reasonable request.

The population used in this study was identified in the Danish Medical Birth Registry. 30 All singleton, liveborn infants with a gestational age (GA) at birth of 22 to 45 weeks born in Denmark from January 1, 1997, to December 31, 2013, were included.

At birth, all Danish citizens are given a personal identification number. This enables storage and linkage of individual‐level data in several nationwide Danish registries. The infants and parents were linked to the following Danish registries: the Civil Registration System, the Danish Central Cytogenetic Registry, the Danish National Patient Registry, the Danish National Prescription Registry, the Danish Medical Birth Registry, and the population and educational registries at Statistics Denmark 30 , 31 , 32 , 33 , 34 (please refer to Table S1 for a description of the data sources).

The diagnoses of CHD were identified in the Danish National Patient Registry. The codes Q20 to 26 from the International Classification of Diseases, Tenth Revision (ICD‐10) were included, while the following specific codes were excluded: bicuspid aortic valve, patent ductus arteriosus, and persistent foramen ovale, as well as nonspecific codes of CHD. 35 , 36 Infants born with a low Apgar score may be more likely to be subject to detailed diagnostic investigations and are thus more likely to be diagnosed with small atrial septal defects or ventricular septal defects of no clinical or hemodynamic importance. 1 Thus, to minimize the risk of surveillance bias, newborns diagnosed with small atrial septal defects or ventricular septal defects without the need for a surgical or catheter‐based intervention at a later stage were not included in the CHD population. Only the diagnoses assigned at the highest level of diagnostic accuracy were accepted. Consequently, the diagnoses were arranged into 3 groups of descending diagnostic accuracy. The first group consisted of diagnoses from surgical contacts at a tertiary center; the second group consisted of diagnoses from admissions to a tertiary center with no surgery performed; and the third group consisted of diagnoses from other university hospital departments of pediatric cardiology. The third group also included a small number of individuals who died before transfer to a department of pediatric cardiology. In accordance with previous work, CHD was divided into 3 primary groups of severity (high, moderate, low) adapted from the European Surveillance of Congenital Anomalies. 37 Moreover, the diagnoses were divided into 13 mutually exclusive subtypes (Table S2). Only diagnoses from the highest group of severity, assigned at the highest level of diagnostic accuracy, were accepted for each individual. Moreover, if an individual was assigned ≥2 diagnoses of a similar severity, the CHD was categorized into the group of “other severe defects” or “other mild defects” and was not considered an isolated CHD.

The Apgar score and GA at birth were retrieved from the Danish Medical Birth Registry. All variables are recorded after birth by trained health care professionals and reported to the Danish Medical Birth Registry. GA has been based on obstetric ultrasound measurements since 2004. 38 In Denmark, only the Apgar scores at 5 minutes are reported to the registry. Improbable combinations of GA and birth weight were found using a recent US algorithm, and these values were set to missing. 39

Additional covariates were collected in accordance with previous work. 27 Child sex, year of birth, maternal age at delivery, parity, prepregnancy body mass index (BMI), and smoking during pregnancy were acquired from the Danish Medical Birth Registry. 27 , 30 Maternal preeclampsia was identified in the Danish National Patient Registry, 32 and prepregnancy diabetes was identified using a combination of information from the Danish National Patient Registry and the Danish National Prescription Registry. 27 , 32 , 33 Information regarding extracardiac malformations and congenital syndromes (Down syndrome, 22q11.2 deletion syndrome, teratogenic syndromes, and other genetic/chromosomal syndromes) were obtained from the Danish National Patient Registry and the Danish Central Cytogenetic Registry. 27 , 32 , 40 Information regarding parental education and origin was acquired from the registries administered by Statistics Denmark and the Danish Civil Registration System, respectively. 31 , 34 Table S3 provides an overview of the definitions of variables applied in the study.

Statistical Analysis

The association between CHD, subtypes of CHD, and a low Apgar score (defined as an Apgar score <7 at 5 minutes) was analyzed by multivariable logistic regression. Odds ratios (ORs) and adjusted ORs were computed. In all analyses, clustering within families was accounted for using robust SEs. The analyses were performed in Stata 17 (StataCorp LP, College Station, TX). Potential confounders were selected a priori on the basis of directed acyclic graphs (Figure S1). 41 , 42 The potential confounders included in the main analysis were maternal age (continuous), maternal prepregnancy diabetes (yes/no), maternal smoking during pregnancy (yes/no), primiparity (yes/no), preeclampsia (yes/no), parental education (3 groups), maternal BMI (continuous, available only from 2004), non‐Western origin (yes/no), sex of the newborn (boy/girl), birth year (continuous), extracardiac malformations (yes/no), and congenital syndromes (any, yes/no).

According to statistical recommendations, missing data were handled using multiple imputation under the assumption that information was missing at random. 43 Twenty data sets exceeding the percentage of observations with any missing value (4.3%) 44 were imputed. The imputation model included all variables in the final model as well as a number of additional variables predictive of missing values (see section on Multiple Imputation in Data S1). 44

To shed light on the mechanisms that may underlie a potential association between CHD and low Apgar score at birth, mediation analyses were performed using the Stata package Med4way. This Stata package computes controlled effects rather than average effects. 45 , 46 In these analyses, we estimated the effect of several prespecified potential mediating variables. We considered the following variables to be potential mediators between CHD and low Apgar score at birth: head circumference Z score, birth weight Z score, and placental weight Z score, as well as preterm birth. 27 , 28 , 29 In the analyses, we estimated the overall proportion of the association between CHD and low Apgar score that could be explained after accounting for each mediating variable separately. In these analyses, only the group of all heart defects was considered, and all of the confounding variables accounted for in the primary analysis, including congenital syndromes and extracardiac malformations, were also included in these analyses. Owing to a lack of statistical power, it was not possible to investigate subgroups of CHD in the mediation analyses.

To test the robustness of the estimates from the primary analysis, several sensitivity analyses were performed. To assess the potential influence of residual confounding from congenital syndromes, all infants with a registered syndrome were excluded. Since the nature of the association between CHD and preeclampsia is not well understood, we repeated the analyses without adjustment for preeclampsia. To assess the potential effect of stillbirth, we redid the primary analysis, including stillbirths categorized as infants with a low Apgar score. Moreover, to assess the influence of maternal BMI, we estimated whether additional adjustment for this variable changed the results of the primary analysis during the period when BMI was available. To visualize potential time trends, including the potential influence of universal prenatal ultrasound screening and prenatal diagnostics, we modeled the risk of a low Apgar score as a function of calendar time using restricted cubic splines, separately for children with and without CHD.

This study was authorized by the Danish Data Protection Agency and The Danish Health Data Authority. Informed consent is not required for Danish register‐based research. The last author had full access to the data and takes responsibility for the data integrity and data analysis.

Results

From January 1, 1997, to December 31, 2013, a total of 1 092 740 births were reported. The total number of births was 1 040 474 after exclusions (47 646 multiple pregnancies, 359 not clearly identified, 4130 stillbirths, and 313 with GA <22 weeks). After exclusions the total number of newborns with CHD was 5098 (0.49%) and the number of newborns without CHD was 1 035 376. Table 2 depicts newborn and parental characteristics according to the presence of CHD (for further details see Tables S3 and S4). The number of newborns in the CHD subgroups is depicted in Figure 1.

Table 2.

Characteristics of Mothers and Newborns in 1 040 474 Live Births Based on the Occurrence of CHD in Denmark From 1997 to 2013

Characteristics CHD (n=5098) Population (n=1 035 376)
Maternal age at delivery, y, mean±SD 30.4±5.1 30.4±4.9
Maternal diabetes before pregnancy,* n (%) 198 (3.9) 23 646 (2.3)
Maternal cigarette smoking during pregnancy, n (%) 833 (16.3) 152 000 (14.7)
Maternal BMI before pregnancy, kg/m2, median (IQR) 24.6 (21.0–26.8) 24.3 (20.9–26.4)
Maternal preeclampsia, n (%) 261 (5.1) 35 860 (3.5)
Maternal nulliparity, n (%) 2199 (43.1) 448 132 (43.3)

Parental education

Low,* n (%)

 2279 (44.7) 410 909 (39.7)
Medium,* n (%) 1856 (36.4) 397 288 (38.4)
High,* n (%) 963 (18.9) 227 179 (21.9)
Non‐Western origin,* n (%) 806 (15.9) 149 841 (14.5)
Sex of the newborn, male, n (%) 2675 (52.3) 530 960 (51.3)
Newborn year of birth, median (IQR) 2004 (2000–2008) 2005 (2001–2009)
Gestational age, wks, median (IQR) 39.6 (38.1–40.7) 40 (39.0–41.0)
Birth weight Z score,* mean±SD −0.29±1.16 0.0±1.0
Placenta weight Z score,* mean±SD −0.15±1.14 0.0±1.0
Head circumference Z score,* mean±SD −0.20±1.06 0.0±1.0
Extracardiac malformations, 27 n (%) 900 (17.7) 29 981 (2.9)
Genetic, chromosomal, or teratogenic syndrome,† n (%) 871 (17.1) 5371 (0.5)
Open in a new tab

BMI indicates body mass index; CHD, congenital heart disease; and IQR, interquartile range.

*

See Table S3 for further details.

†

Down syndrome, 22q11.2 deletion syndrome, teratogenic syndromes, or other genetic or chromosomal syndromes 27 (see Table S4 for further details).

Due to overlapping study populations, some of the statistics are identical to previous work. 27 Please refer to Figure S2 for a graphical overview of the Apgar score distribution in children with and without CHD.

Figure 1. Number of participants in each CHD group, and the association between subtypes of CHD and the risk of a low Apgar score (<7).

Figure 1

Open in a new tab

Unadjusted odds ratios (unadjusted) and adjusted odds ratios are provided for the association between groups of CHD and the risk of low Apgar score. The subgroups of CHD were divided into 3 groups of severity adapted from the EUROCAT classification. 27 , 28 , 29 , 37 Adjustments were made for maternal age, maternal prepregnancy diabetes, maternal smoking during pregnancy, nulliparity, preeclampsia, parental education, non‐Western origin, sex of the newborn, birth year, extracardiac malformations, and congenital syndromes. The number of outcomes in the subgroups is not reported due to data protection policies at Statistics Denmark. aOR indicates adjusted odds ratio; CHD, congenital heart disease; and EUROCAT, European Network of Population‐Based Registries for the Epidemiological Surveillance of Congenital Anomalies.

Any missing value was present in 44 276 observations (4.3%). The number of missing Apgar scores was 17 940 (1.7%), and the number of observations with missing information on maternal smoking was 37 006 (3.6%). In newborns with CHD, 3% (150) had low Apgar scores at 5 minutes, and in newborns without CHD, 0.7% (7587) had a low Apgar score. In newborns with a CHD of high severity, 3.7% had a low Apgar, and in newborns with CHD of moderate and low severity, the proportions were 3.3% and 2.7%, respectively (Figure 1). Figure S2 shows the distribution of Apgar scores in children with and without CHD.

In comparison with the general population, CHD was associated with an increased risk of a low Apgar score at 5 minutes, adjusted OR 2.5 (95% CI, 2.1–3.0). Additionally, the risk of a low Apgar score increased with the severity of CHD. The adjusted OR of a low Apgar score was 3.8 (95% CI, 2.1–7.1) in the high‐severity group, 2.6 (95% CI, 2.0–3.4) in the moderate severity group, and 2.3 (95% CI, 1.8–3.0) in the low‐severity group (Figure 1).

Most subgroups of CHD had an increased risk of a low Apgar score (Figure 1). The subgroups of CHD with the highest risk of a low Apgar score were anomalous pulmonary venous return, hypoplastic left heart syndrome, transposition of the great arteries, other severe heart defects, pulmonary stenosis in combination with any septal defect, tetralogy of Fallot, other mild defects, and other single‐ventricle defects (Figure 1).

In the mediation analyses, accounting for preterm birth explained 25.2% (95% CI, 11.8–38.6) of the overall association between CHD and low Apgar score. On the other hand, we found no evidence that head circumference Z score, birth weight Z score, or placental weight Z score mediated any part of the association.

In the sensitivity analyses, the results were similar when all infants with a registered syndrome were excluded, when preeclampsia was not adjusted for in the primary analysis, and when stillbirths were categorized as infants with a low Apgar score. Moreover, additional adjustment for BMI did not substantially change the results, and no major time trends were observed in the risk of a low Apgar score in children with or without CHD (Figure 2). Finally, the results of the complete case analyses were also similar to the results based on analyses including multiple imputation of missing variables.

Figure 2. Time trends in the risk of a low Apgar score (<7) in children with and without CHD in Denmark from 1997 to 2013.

Figure 2

Open in a new tab

The association between calendar‐time (January 1, 1997, to December 31, 2013) and the risk of a low Apgar score after 5 min was modeled separately in newborns with CHD (blue) and without CHD (red) using restricted cubic splines (7 knots). CHD indicates congenital heart disease.

Discussion

The present study provides nationwide population‐based estimates regarding the association between the major subtypes of CHD and the risk of a low Apgar score at birth. It is the first study to perform mediation analyses on the studied association. The absolute proportions of low Apgar scores were low in both newborns with and newborns without CHD. However, newborns with CHD had a 2.5 times increased risk of a low Apgar score at birth. As expected, the risk of a low Apgar score was even higher in the severe and potentially cyanotic types of CHD. Hypoplastic left heart syndrome was associated with a 5 times increased risk of a low Apgar score. Anomalous pulmonary venous return, other single‐ventricle defects, tetralogy of Fallot, and transposition of the great arteries were associated with a 2.7 to 5.7 times increased risk of a low Apgar score. None of the associations mentioned above could be explained by maternal factors or extracardiac malformations. However, as expected, after accounting for a number of potential confounding factors, the results were attenuated (overall in CHD: unadjusted OR, 4.3 versus adjusted OR, 2.5). Whereas some subgroups did not reach statistical significance, large ventricular septal defects were the only subgroup that was not associated with a point estimate indicating an increased risk of a low Apgar score. In the mediation analyses, preterm birth explained 25.2% of the overall association between CHD and a low Apgar score at 5 minutes. Head circumference, birth weight, or placental weight did not mediate any part of the association.

One previous study by Cedergren and Källén assessed the association between 2 groups of CHD (mild or severe) and a low Apgar score 47 ; however, the Apgar score was a secondary outcome in the study. The study was a Swedish population‐based cohort study, and similar to the present study, information about the population was gathered through personal identification numbers and national registries. Unlike the present study, CHD was only categorized into 2 groups, and consequently the study did not assess the association between specific subtypes of CHD and the risk of a low Apgar score. Nevertheless, the findings in the present study are similar to the findings of Cedergren et al reporting a 2 times increased risk of a low Apgar score overall in newborns with any type of CHD. Similarly, without reporting specific estimates or subcategorizing the CHD into severity, Weissmann‐Brenner et al described an association between CHD and a low Apgar score. 48

The Apgar score is a combined measure of both the circulatory and neurologic states of the newborn.

Accordingly, otherwise healthy prenatally diagnosed children with CHD, with no neurologic impairments or circulatory failure (including cyanosis), are likely to obtain normal Apgar scores at 5 minutes. Indeed, this was the case for most newborns with CHD in the present study. However, children with more pronounced neurologic impairments or circulatory failure are unlikely to obtain normal Apgar scores at 5 minutes.

In accordance with this, the association was especially pronounced in the severe and potentially cyanotic subtypes of CHD likely to influence the color, heart rate, and respiration of the newborn through the neonatal circulation. Moreover, subtypes of CHD such as hypoplastic left heart syndrome and transposition of the great arteries have also been associated with an increased risk of preoperative brain injury 48 that in turn may directly influence reflex irritability, muscle tone, and respiration of the newborn. Of note, newborns and fetuses with severe and potentially cyanotic CHD exhibit signs of delayed brain maturation, 22 , 23 , 49 which may make newborns with CHD more susceptible to brain injury resulting from a complicated neonatal transition. In line with this, a low Apgar score at birth is associated with signs of neonatal brain injury and neurodevelopmental disorders in infants with CHD. 24 , 25 Whereas the Apgar score is not an optimal tool to assess the risk of neurologic impairments, 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 the results of previous studies coupled with the findings from the present study suggest that optimizing the neonatal transition in children with CHD may hold the potential to improve childhood neurodevelopment in this group of children.

The present study has several limitations common to other types of observational research. Whereas the main analyses rely on the assumption that confounders of the association between CHD and low Apgar scores are accounted for, the mediation analyses additionally rely on the strong assumptions that confounders of the exposure–mediator and mediator–outcome associations are all accounted for. 45 , 46 Common sources of confounding include unknown, unmeasured/unrecorded, or imperfectly measured/recorded confounding variables. Although several important potential confounders were accounted for, there may still be unidentified confounders or imperfectly recorded confounders, which may result in residual confounding. However, considering the large number of important potential confounders included in the present study, confounding seems an unlikely explanation of the results in this study.

Common sources of selection bias include baseline selection, loss to follow‐up, and missing data.

Baseline selection is not considered an issue in nationwide registry‐based studies. Stillbirths may be considered loss to follow‐up; however, when stillbirths were included as low Apgar scores, the results were not substantially changed compared with the primary analyses. In accordance with methodological recommendations, missing data were handled using multiple imputations under the assumption of missing at random. 43 , 44 Consequently, it seems unlikely that the result of the study can be explained by selection bias.

Common sources of information bias include differential misclassification of the exposure or the outcome. Major misclassification of the CHD diagnoses registered in the Danish university hospitals is unlikely, since a previous study has confirmed the validity of the recording of CHD. 50 Moreover, we took several precautions to improve the diagnostic accuracy of the CHD recordings and the comparability within the CHD subgroups. Nevertheless, some degree of anatomic variation is likely to be present within the subgroups of CHD. Additionally, CHD may have gone undiagnosed in some individuals, including the small number of stillbirths and children with low Apgar scores who died before cardiac investigation. This may potentially have attenuated the association in the present study. Regarding the outcome, the CHD status of the newborn has been unknown for most of the midwives responsible for scoring and registering the Apgar score. However, knowledge of the CHD status before birth may theoretically have affected the recording of the Apgar score. Nevertheless, this was not the case in previous studies. 51 , 52 Finally, the results of the present study were similar before and after the introduction of universal ultrasound screening. Small atrial septal defects and ventricular septal defects, without the need for a surgical or catheter‐based intervention, may represent incidental findings with low Apgar scores. Consequently, to minimize the risk of surveillance bias, these minor defects were not included in the CHD population. Summing up, information bias is considered an unlikely explanation for the results of the present study.

Another limitation of the present study is the lack of information on prenatal diagnoses. Unfortunately, prenatal diagnoses have not been recorded consistently in the available registries. However, despite the introduction of universal ultrasound screening in 2004, no clear time trends were present in the occurrence of low Apgar scores in children with CHD (Figure 2).

The Apgar score has several limitations. The use of the scoring system in predicting neurologic outcomes and asphyxia at the individual level has been widely criticized. 53 Conversely, other studies have shown the Apgar score to be a predictor of neurologic outcomes during childhood, 16 , 18 , 21 and 2 previous studies found the Apgar score to be predictive of signs of brain injury and neurodevelopment in children with CHD. 24 , 25 Another shortcoming of the present study is that the nationwide registry data are limited to Apgar score at 5 minutes. Inclusion of the Apgar score at 1, 5, and 10 minutes would have enabled us to follow the development in Apgar score and the neonatal transition over time. Moreover, the specific scores within each component of the Apgar would have been a great addition to the present study to differentiate neurologic impairment from circulatory impairment. Unfortunately, the scores within each component are not recorded in the registry.

To summarize, the present study found an increased risk of a low Apgar score at birth in newborns with CHD. The groups with the highest risk of a low Apgar were anomalous pulmonary venous return, hypoplastic left heart syndrome, transposition of the great arteries, and pulmonary stenosis in combination with a septal defect. These findings suggest that newborns with CHD are more likely to experience a complicated fetal‐to‐neonatal transition. The present study raises the possibility that optimizing the neonatal transition in children with CHD may hold the potential to improve perinatal, neonatal, and long‐term neurodevelopment in this patient group.

Sources of Funding

None.

Disclosures

None.

Supporting information

Methods S1

Tables S1–S4

Figures S1–S2

References 30–32, 54–59

JAH3-14-e038798-s001.pdf (321.9KB, pdf)

Acknowledgments

We acknowledge the Danish Children's Heart Foundation for the support of our previous work, which also enabled the present work.

This manuscript was sent to John L. Jefferies, MD, MPH, Guest Editor, for review by expert referees, editorial decision, and final disposition.

For Sources of Funding and Disclosures, see page 8.

References

  • 1. Hoffman JI, Kaplan S. The incidence of congenital heart disease. J Am Coll Cardiol. 2002;39:1890–1900. doi: 10.1016/s0735-1097(02)01886-7 [DOI] [PubMed] [Google Scholar]
  • 2. Khairy P, Ionescu‐Ittu R, Mackie AS, Abrahamowicz M, Pilote L, Marelli AJ. Changing mortality in congenital heart disease. J Am Coll Cardiol. 2010;56:1149–1157. doi: 10.1016/j.jacc.2010.03.085 [DOI] [PubMed] [Google Scholar]
  • 3. Bakker MK, Bergman JEH, Krikov S, Amar E, Cocchi G, Cragan J, de Walle HEK, Gatt M, Groisman B, Liu S, et al. Prenatal diagnosis and prevalence of critical congenital heart defects: an international retrospective cohort study. BMJ Open. 2019;9:e028139. doi: 10.1136/bmjopen-2018-028139 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Hövels‐Gürich HH, Seghaye M‐C, Däbritz S, Messmer BJ, von Bernuth G. Cognitive and motor development in preschool and school‐aged children after neonatal arterial switch operation. J Thorac Cardiovasc Surg. 1997;114:578–585. doi: 10.1016/S0022-5223(97)70047-3 [DOI] [PubMed] [Google Scholar]
  • 5. Bellinger DC, Wypij D, duPlessis AJ, Rappaport LA, Jonas RA, Wernovsky G, Newburger JW. Neurodevelopmental status at eight years in children with dextro‐transposition of the great arteries: The Boston Circulatory Arrest Trial. J Thorac Cardiovasc Surg. 2003;126:1385–1396. doi: 10.1016/S0022-5223(03)00711-6 [DOI] [PubMed] [Google Scholar]
  • 6. Derridj N, Guedj R, Calderon J, Houyel L, Lelong N, Bertille N, Goffinet F, Bonnet D, Khoshnood B. Long‐term neurodevelopmental outcomes of children with congenital heart defects. J Pediatr. 2021;237:109–114. doi: 10.1016/j.jpeds.2021.06.032 [DOI] [PubMed] [Google Scholar]
  • 7. Omann C, Kristensen R, Tabor A, Gaynor JW, Hjortdal VE, Nyboe C. School performance is impaired in children with both simple and complex congenital heart disease. Front Pediatr. 2023;11:1073046. doi: 10.3389/fped.2023.1073046 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Limperopoulos C, Majnemer A, Shevell MI, Rosenblatt B, Rohlicek C, Tchervenkov C. Neurodevelopmental status of newborns and infants with congenital heart defects before and after open heart surgery. J Pediatr. 2000;137:638–645. doi: 10.1067/mpd.2000.109152 [DOI] [PubMed] [Google Scholar]
  • 9. Majnemer A, Limperopoulos C, Shevell M, Rosenblatt B, Rohlicek C, Tchervenkov C. Long‐term neuromotor outcome at school entry of infants with congenital heart defects requiring open‐heart surgery. J Pediatr. 2006;148:72–77. doi: 10.1016/j.jpeds.2005.08.036 [DOI] [PubMed] [Google Scholar]
  • 10. McQuillen PS, Barkovich AJ, Hamrick SE, Perez M, Ward P, Glidden DV, Azakie A, Karl T, Miller SP. Temporal and anatomic risk profile of brain injury with neonatal repair of congenital heart defects. Stroke. 2007;38:736–741. doi: 10.1161/01.Str.0000247941.41234.90 [DOI] [PubMed] [Google Scholar]
  • 11. Mahle WT, Clancy RR, Moss EM, Gerdes M, Jobes DR, Wernovsky G. Neurodevelopmental outcome and lifestyle assessment in school‐aged and adolescent children with hypoplastic left heart syndrome. Pediatrics. 2000;105:1082–1089. doi: 10.1542/peds.105.5.1082 [DOI] [PubMed] [Google Scholar]
  • 12. Apgar V. A proposal for a new method of evaluation of the newborn infant. Anesth Analg. 2015;120:1056–1059. doi: 10.1213/ANE.0b013e31829bdc5c [DOI] [PubMed] [Google Scholar]
  • 13. Pediatrics AAo , Fetus Co , Newborn , Obstetricians ACo , Gynecologists , Practice CoO . The Apgar score. Pediatrics. 2006;117:1444–1447. doi: 10.1542/peds.2006-0325 [DOI] [PubMed] [Google Scholar]
  • 14. Odd DE, Rasmussen F, Gunnell D, Lewis G, Whitelaw A. A cohort study of low Apgar scores and cognitive outcomes. Arch Dis Child Fetal Neonatal Ed. 2008;93:F115–F120. doi: 10.1136/adc.2007.123745 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Stuart A, Otterblad Olausson P, Källen K. Apgar scores at 5 minutes after birth in relation to school performance at 16 years of age. Obstet Gynecol. 2011;118:201–208. doi: 10.1097/AOG.0b013e31822200eb [DOI] [PubMed] [Google Scholar]
  • 16. Leinonen E, Gissler M, Haataja L, Rahkonen P, Andersson S, Metsäranta M, Rahkonen L. Low Apgar scores at both one and five minutes are associated with long‐term neurological morbidity. Acta Paediatr. 2018;107:942–951. doi: 10.1111/apa.14234 [DOI] [PubMed] [Google Scholar]
  • 17. Moster D, Lie RT, Irgens LM, Bjerkedal T, Markestad T. The association of Apgar score with subsequent death and cerebral palsy: a population‐based study in term infants. J Pediatr. 2001;138:798–803. doi: 10.1067/mpd.2001.114694 [DOI] [PubMed] [Google Scholar]
  • 18. Thorngren‐Jerneck K, Herbst A. Low 5‐minute Apgar score: a population‐based register study of 1 million term births. Obstet Gynecol. 2001;98:65–70. doi: 10.1016/S0029-7844(01)01370-9 [DOI] [PubMed] [Google Scholar]
  • 19. Sun Y, Vestergaard M, Pedersen CB, Christensen J, Olsen J. Apgar scores and long‐term risk of epilepsy. Epidemiology. 2006;17:296–301. doi: 10.1097/01.ede.0000208478.47401.b6 [DOI] [PubMed] [Google Scholar]
  • 20. Iliodromiti S, Mackay DF, Smith GC, Pell JP, Nelson SM. Apgar score and the risk of cause‐specific infant mortality: a population‐based cohort study. Lancet. 2014;384:1749–1755. doi: 10.1016/s0140-6736(14)61135-1 [DOI] [PubMed] [Google Scholar]
  • 21. Persson M, Razaz N, Tedroff K, Joseph KS, Cnattingius S. Five and 10 minute Apgar scores and risks of cerebral palsy and epilepsy: population based cohort study in Sweden. BMJ. 2018;360:k207. doi: 10.1136/bmj.k207 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Licht DJ, Shera DM, Clancy RR, Wernovsky G, Montenegro LM, Nicolson SC, Zimmerman RA, Spray TL, Gaynor JW, Vossough A. Brain maturation is delayed in infants with complex congenital heart defects. J Thorac Cardiovasc Surg. 2009;137:529–537. doi: 10.1016/j.jtcvs.2008.10.025 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Limperopoulos C, Tworetzky W, McElhinney DB, Newburger JW, Brown DW, Robertson RL Jr, Guizard N, McGrath E, Geva J, Annese D, et al. Brain volume and metabolism in fetuses with congenital heart disease: evaluation with quantitative magnetic resonance imaging and spectroscopy. Circulation. 2010;121:26–33. doi: 10.1161/circulationaha.109.865568 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Bonthrone AF, Stegeman R, Feldmann M, Claessens NHP, Nijman M, Jansen NJG, Nijman J, Groenendaal F, de Vries LS, Benders M, et al. Risk factors for perioperative brain lesions in infants with congenital heart disease: a European collaboration. Stroke. 2022;53:3652–3661. doi: 10.1161/strokeaha.122.039492 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Gaynor JW, Wernovsky G, Jarvik GP, Bernbaum J, Gerdes M, Zackai E, Nord AS, Clancy RR, Nicolson SC, Spray TL. Patient characteristics are important determinants of neurodevelopmental outcome at one year of age after neonatal and infant cardiac surgery. J Thorac Cardiovasc Surg. 2007;133:1344–1353. doi: 10.1016/j.jtcvs.2006.10.087 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Auger N, Fraser WD, Healy‐Profitós J, Arbour L. Association between preeclampsia and congenital heart defects. JAMA. 2015;314:1588–1598. doi: 10.1001/jama.2015.12505 [DOI] [PubMed] [Google Scholar]
  • 27. Matthiesen NB, Østergaard JR, Hjortdal VE, Henriksen TB. Congenital heart defects and the risk of spontaneous preterm birth. J Pediatr. 2021;229:168–174. doi: 10.1016/j.jpeds.2020.09.059 [DOI] [PubMed] [Google Scholar]
  • 28. Matthiesen NB, Henriksen TB, Gaynor JW, Agergaard P, Bach CC, Hjortdal VE, Østergaard JR. Congenital heart defects and indices of fetal cerebral growth in a nationwide cohort of 924 422 Liveborn infants. Circulation. 2016;133:566–575. doi: 10.1161/circulationaha.115.019089 [DOI] [PubMed] [Google Scholar]
  • 29. Matthiesen NB, Henriksen TB, Agergaard P, Gaynor JW, Bach CC, Hjortdal VE, Østergaard JR. Congenital heart defects and indices of placental and fetal growth in a nationwide study of 924 422 liveborn infants. Circulation. 2016;134:1546–1556. doi: 10.1161/circulationaha.116.021793 [DOI] [PubMed] [Google Scholar]
  • 30. Bliddal M, Broe A, Pottegård A, Olsen J, Langhoff‐Roos J. The Danish medical birth register. Eur J Epidemiol. 2018;33:27–36. doi: 10.1007/s10654-018-0356-1 [DOI] [PubMed] [Google Scholar]
  • 31. Schmidt M, Pedersen L, Sørensen HT. The Danish Civil Registration System as a tool in epidemiology. Eur J Epidemiol. 2014;29:541–549. doi: 10.1007/s10654-014-9930-3 [DOI] [PubMed] [Google Scholar]
  • 32. Lynge E, Sandegaard JL, Rebolj M. The Danish national patient register. Scand J Public Health. 2011;39:30–33. doi: 10.1177/1403494811401482 [DOI] [PubMed] [Google Scholar]
  • 33. Kildemoes HW, Sorensen HT, Hallas J. The Danish national prescription registry. Scand J Public Health. 2011;39:38–41. doi: 10.1177/1403494810394717 [DOI] [PubMed] [Google Scholar]
  • 34. Jensen VM, Rasmussen AW. Danish education registers. Scand J Public Health. 2011;39:91–94. doi: 10.1177/1403494810394715 [DOI] [PubMed] [Google Scholar]
  • 35. EUROCAT . EUROCAT Guide 1.5: Instruction for the Registration of Congenital Anomalies. EUROCAT Central Registry, University of Ulster; 2013. Accessed April. https://eu‐rd‐platform.jrc.ec.europa.eu/eurocat/data‐collection/guidelines‐for‐data‐registration_en#inline‐nav‐2 [Google Scholar]
  • 36. Olsen M, Sørensen HT, Hjortdal VE, Christensen TD, Pedersen L. Congenital heart defects and developmental and other psychiatric disorders. Circulation. 2011;124:1706–1712. doi: 10.1161/CIRCULATIONAHA.110.002832 [DOI] [PubMed] [Google Scholar]
  • 37. Dolk H, Loane M, Garne E; European Surveillance of Congenital Anomalies Working G . Congenital heart defects in Europe: prevalence and perinatal mortality, 2000 to 2005. Circulation. 2011;123:841–849. doi: 10.1161/CIRCULATIONAHA.110.958405 [DOI] [PubMed] [Google Scholar]
  • 38. DNBH . Retningslinjer for fosterdiagnostik—prænatal information, risikovurdering, rådgivning og diagnostik (Guidelines for fetal diagnostics—prenatal information, risk assessment, counseling, and diagnostics). Danish National Board of Health; 2017. https://www.sst.dk/‐/media/Udgivelser/2020/Fosterdiagnostik/Retningslinjer‐for‐fosterdiagnostik.ashx [Google Scholar]
  • 39. Talge NM, Mudd LM, Sikorskii A, Basso O. United States birth weight reference corrected for implausible gestational age estimates. Pediatrics. 2014;133:844–853. doi: 10.1542/peds.2013-3285 [DOI] [PubMed] [Google Scholar]
  • 40. Agergaard P, Olesen C, Ostergaard JR, Christiansen M, Sorensen KM. The prevalence of chromosome 22q11.2 deletions in 2,478 children with cardiovascular malformations. A population‐based study. Am J Med Genet A. 2012;158:498–508. doi: 10.1002/ajmg.a.34250 [DOI] [PubMed] [Google Scholar]
  • 41. Textor J, van der Zander B, Gilthorpe MS, Liśkiewicz M, Ellison GT. Robust causal inference using directed acyclic graphs: the R package ‘dagitty’. Int J Epidemiol. 2017;45:1887–1894. doi: 10.1093/ije/dyw341 [DOI] [PubMed] [Google Scholar]
  • 42. Williams TC, Bach CC, Matthiesen NB, Henriksen TB, Gagliardi L. Directed acyclic graphs: a tool for causal studies in paediatrics. Pediatr Res. 2018;84:487–493. doi: 10.1038/s41390-018-0071-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43. Sterne JA, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, Wood AM, Carpenter JR. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009;338:b2393. doi: 10.1136/bmj.b2393 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. White IR, Royston P, Wood AM. Multiple imputation using chained equations: issues and guidance for practice. Stat Med. 2011;30:377–399. doi: 10.1002/sim.4067 [DOI] [PubMed] [Google Scholar]
  • 45. Discacciati A, Bellavia A, Lee JJ, Mazumdar M, Valeri L. Med4way: a Stata command to investigate mediating and interactive mechanisms using the four‐way effect decomposition. Int J Epidemiol. 2018;48:15–20. doi: 10.1093/ije/dyy236 [DOI] [PubMed] [Google Scholar]
  • 46. van der Weele TJ. A unification of mediation and interaction: a 4‐way decomposition. Epidemiology. 2014;25:749–761. doi: 10.1097/ede.0000000000000121 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47. Cedergren MI, Källén BAJ. Obstetric outcome of 6346 pregnancies with infants affected by congenital heart defects. Eur J Obstet Gynecol Reprod Biol. 2006;125:211–216. doi: 10.1016/j.ejogrb.2005.07.006 [DOI] [PubMed] [Google Scholar]
  • 48. Khalil A, Suff N, Thilaganathan B, Hurrell A, Cooper D, Carvalho JS. Brain abnormalities and neurodevelopmental delay in congenital heart disease: systematic review and meta‐analysis: brainabnormalities and neurodevelopmental delay in CHD. Ultrasound Obstet Gynecol. 2013;43:14–24. doi: 10.1002/uog.12526 [DOI] [PubMed] [Google Scholar]
  • 49. Donofrio MT, Bremer YA, Schieken RM, Gennings C, Morton LD, Eidem BW, Cetta F, Falkensammer CB, Huhta JC, Kleinman CS. Autoregulation of cerebral blood flow in fetuses with congenital heart disease: the brain sparing effect. Pediatr Cardiol. 2003;24:436–443. doi: 10.1007/s00246-002-0404-0 [DOI] [PubMed] [Google Scholar]
  • 50. Agergaard P, Hebert A, Bjerre J, Sorensen KM, Olesen C, Ostergaard JR. Children diagnosed with congenital cardiac malformations at the national university departments of pediatric cardiology: positive predictive values of data in the Danish National Patient Registry. Clin Epidemiol. 2011;3:61–66. doi: 10.2147/CLEP.S15627 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51. Weissmann‐Brenner A, Domniz N, Meyer R, Weissbach T, Elkan T, Salem Y, Bart Y, Kassif E, Weisz B. Delivery outcome of fetuses with congenital heart disease—is it influenced by prenatal diagnosis? J Clin Med. 2022;11:4075. doi: 10.3390/jcm11144075 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52. Levey A, Glickstein JS, Kleinman CS, Levasseur SM, Chen J, Gersony WM, Williams IA. The impact of prenatal diagnosis of complex congenital heart disease on neonatal outcomes. Pediatr Cardiol. 2010;31:587–597. doi: 10.1007/s00246-010-9648-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53. American College of Obstetricians and Gynecologists , American Academy of Pediatrics . Committee opinion no. 644: the Apgar score. Obstet Gynecol. 2015;126:e52–e55. [DOI] [PubMed] [Google Scholar]
  • 54. World Health Organization (WHO) . International Classification of Diseases . 2015. Accessed July 18, 2019. http://apps.who.int/classifications/icd10/browse/2015/en#.
  • 55. The Nordic Medico‐Statistical Committee (NOMESCO) . Classification of Surgical Procedures Version 1.16 . 2012. Accessed July 18, 2019. http://www.nordclass.se/NCSP_1_16.pdf.
  • 56. Boyd HA, Basit S, Behrens I, Leirgul E, Bundgaard H, Wohlfahrt J, Melbye M, Øyen N. Association between fetal congenital heart defects and maternal risk of hypertensive disorders of pregnancy in the same pregnancy and across pregnancies. Circulation. 2017;136:39–48. doi: 10.1161/CIRCULATIONAHA.116.024600 [DOI] [PubMed] [Google Scholar]
  • 57. Molgaard‐Nielsen D, Pasternak B, Hviid A. Use of oral fluconazole during pregnancy and the risk of birth defects. N Engl J Med. 2013;369:830–839. doi: 10.1056/NEJMoa1301066 [DOI] [PubMed] [Google Scholar]
  • 58. Aagaard K, Bach CC, Henriksen TB, Larsen RT, Matthiesen NB. Head circumference at birth and childhood developmental disorders in a nationwide cohort in Denmark. Paediatr Perinat Epidemiol. 2018;32:458–466. doi: 10.1111/ppe.12479 [DOI] [PubMed] [Google Scholar]
  • 59. EUROCAT . European Surveillance of Congenital Anomalies. Guide 1.3: Instructions for the Registration and Surveillance of Congenital Anomalies . 2009. Accessed August 15, 2015. http://www.eurocat‐network.eu/content/EUROCAT‐Guide‐1.3.pdf.

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Methods S1

Tables S1–S4

Figures S1–S2

References 30–32, 54–59

JAH3-14-e038798-s001.pdf (321.9KB, pdf)

Articles from Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease are provided here courtesy of Wiley

RESOURCES