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Prevalence, timing of diagnosis and mortality of newborns with congenital heart defects: a population-based study
  1. Babak Khoshnood1,
  2. Nathalie Lelong1,
  3. Lucile Houyel2,
  4. Anne-Claire Thieulin1,
  5. Jean-Marie Jouannic3,
  6. Suzel Magnier4,
  7. Anne-Lise Delezoide5,
  8. Jean-François Magny6,
  9. Caroline Rambaud7,
  10. Damien Bonnet8,
  11. François Goffinet1,9,
  12. on behalf of the EPICARD Study Group
  1. 1Inserm, UMR S953, Recherche épidémiologique sur la santé périnatale et la santé des femmes et des enfants, UPMC, Université Paris-6, Maternité de Port-Royal, Paris, France
  2. 2Service de chirurgie des cardiopathies congénitales, Hôpital Marie Lannelongue, Le Plessis Robinson, France
  3. 3Hôpital Trousseau, AP-HP, Centre pluridisciplinaire de diagnostic prénatal, UPMC, Paris, France
  4. 4Hôpital Robert Debré, AP-HP, Service de cardiologie, Paris, France
  5. 5Hôpital Robert Debré, AP-HP, Service de biologie du Développement, Université Paris-Diderot, Paris, France
  6. 6Institut de Puériculture et de périnatologie, Service de néonatologie, Paris, France
  7. 7Hôpital Raymond Poincarré, AP-HP, Service d'anatomie et cytologie pathologiques – Médecine légale, UVSQ, Garches, Paris, France
  8. 8Centre de référence M3C-Necker, Université Paris Descartes, Paris, France
  9. 9Maternité de Port-Royal, Groupe Hospitalier Cochin-Broca-Hôtel Dieu, Université Paris Descartes, Assistance Publique-Hôpitaux de Paris, Paris, France
  1. Correspondence to Dr Babak Khoshnood, INSERM U953, Maternité de Port-Royal, 6ème étage, 53 av. de l'Observatoire, 75014, Paris, France; babak.khoshnood{at}inserm.fr

Abstract

Objective To assess the prevalence, timing of diagnosis and infant mortality of congenital heart defects (CHD) with population-based data and using a classification that allows regrouping of the International Paediatric and Congenital Cardiac Code into a manageable number of categories based on anatomic and clinical criteria (ACC-CHD).

Design Population-based cohort study.

Setting Greater Paris.

Patients All cases (live births, terminations of pregnancy for foetal anomaly (TOPFA), foetal deaths) diagnosed prenatally, or up to 1 year of age in the birth cohorts, May 2005–April 2008, for women in Greater Paris (n=317 538 births). Diagnoses were confirmed in specialised centres and subsequently coded and classified into the categories of ACC-CHD by paediatric cardiologists in the study group.

Results The total number of CHD was 2867, including 2348 live births (82%), 466 TOPFA (16.2%) and 53 foetal deaths (1.8%). The total prevalence of CHD was 90 per 10 000. After exclusion of ventricular septal defects (VSD), 40% of ‘isolated’ CHD was diagnosed prenatally with about one half of the remaining diagnosed before 7 days of age. Nevertheless, one in five cases of these major CHD was diagnosed after the fourth week. Infant mortality of ‘isolated’ CHD-VSD excluded was 8.5% with 40% of deaths occurring after the fourth week of life. These outcomes varied substantially across categories of ACC-CHD.

Conclusions Timing of diagnosis, TOPFA, risk and timing of infant mortality were highly variable across the categories of CHD in ACC-CHD, suggesting that it may be a useful measure of severity, and hence, predictor of outcomes of CHD.

  • Congenital heart defects
  • population-based
  • cohort
  • prevalence
  • prenatal diagnosis
  • infant mortality
  • congenital heart disease
  • paediatric cardiology
  • quality of care and outcomes
  • epidemiology
  • imaging and diagnostics
  • echocardiography
  • fetal
  • williams syndrome
  • fetal cardiololgy
  • paediatrics
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Introduction

Congenital heart defects (CHD) are the most prevalent group of major congenital anomalies.1–4 Despite considerable progress in medical and surgical management of newborns with CHD,5–7 there is considerable mortality and morbidity associated with severe forms of CHD, which comprise the first cause of mortality by congenital anomalies.1 ,8–11 Moreover, survivors may have considerable short-term morbidity and long-term adverse neuro-developmental outcomes.12 ,13

There is substantial literature on various biological, clinical and epidemiological aspects of CHD. However, by far, most studies are based on data from a few specialised centres, and population-based studies remain relatively rare.1 ,5 ,7 ,14 ,15 This is the case for questions related to the prevalence, timing of diagnosis and, particularly, health outcomes of infants with CHD. The paucity of population-based data, in turn, limits the generalisability of available data for evaluation of the mortality, morbidity and long-term health outcomes of newborns with CHD.

CHD represent a wide spectrum of heterogeneous anomalies that show considerable variability in their prevalence, anatomy, developmental origin, severity, modalities of clinical and surgical management, short- and longer-term mortality, morbidity and neuro-developmental outcomes. Given this heterogeneity, coding and classification of CHD becomes a major and challenging question. Currently, the most widely used coding and classification for CHD is the 10th version of the International Classification of Disease (ICD10). However, it is increasingly recognised, particularly by paediatric cardiologists and cardiac surgeons, that ICD10 has important shortcomings for characterising CHD.16 ,17 In order to address these shortcomings, a comprehensive coding system, the International Paediatric and Congenital Cardiac Code (IPCCC) has been devised.16–19 The IPCCC has many advantages but has never been used in a population-based study, most likely due to its complexity requiring highly specialised coding. Moreover, given the number of codes in the IPCCC (the long list of IPCCC includes more than 10 000 individual codes), its use in most clinical and epidemiological studies requires regrouping of individual anomalies. A newly proposed classification, the Anatomic and Clinical Classification of CHD (ACC-CHD) accomplishes this regrouping based on anatomic and clinical criteria.20 However, the extent to which the categories of ACC-CHD categories may be associated with medical management and outcomes of infants with CHD has not been evaluated.

Our objective was to assess the total and live birth prevalence of CHD, timing of diagnosis (pre- and postnatal diagnosis) and infant mortality of newborns with CHD in a large population-based cohort study with CHD coded with the IPCCC for: (1) all cases of CHD, (2) CHD excluding those associated with other anomalies, (3) categories of CHD based on the ACC-CHD classification.20

Materials and methods

Data

The EPICARD (EPIdémiologie des CARDiopathies congénitales) study is a population-based, prospective cohort study with long-term follow-up of all children with a CHD born to women in the Greater Paris area (Paris and its surrounding suburbs). The principal objectives of the study are to use population-based data from a large cohort of patients with CHD to: (1) estimate the prevalence, timing of diagnosis and medical and surgical management of newborns with CHD, (2) evaluate their mortality, morbidity and neuro-developmental outcomes; and (3) identify the factors associated with their short- and long-term health outcomes, especially the impact of timing of diagnosis and the initial medical and surgical management of the infants with CHD, as well as, access to care and socioeconomic factors.

All cases (live births, Terminations of Pregnancy for Foetal Anomaly (TOPFA), foetal deaths) diagnosed in the prenatal period, or up to 1 year of age in the birth cohorts, between May 1st 2005 and April 30th 2008 born to women residing in Greater Paris, were eligible for inclusion. Diagnoses were confirmed in specialised paediatric cardiology departments, and for the majority of TOPFA and foetal deaths by a standardised pathology examination. When a pathology exam could not be done, the diagnoses were confirmed by a paediatric cardiologist (LH) and a specialist in echocardiography (JMJ) in the EPICARD study group, using the results of prenatal echocardiography examination.

Multiple sources of data, including all maternity units, paediatric cardiology and cardiac surgery centres, foetal and neonatal pathology departments, neonatal and paediatric intensive units, infant units and outpatient clinics in Greater Paris and a neighbouring tertiary care centre were regularly consulted to attain completeness of case registrations. Informed consent was obtained from study participants, and the study was approved by an ethics committee (French National Committee of Information and Liberty). The last cases included in the study were those in the 2008 birth cohort who were diagnosed in 2009. Follow-up of children in the EPICARD cohort is ongoing and will include assessment of children's health and neuro-developmental outcomes until at least 8 years of age.

Methods

Coding and classification of CHD

Details of coding and classification of cases for the EPICARD study are given elsewhere.20 Briefly, two paediatric cardiologists in the EPICARD study group (LH, DB) attributed by consensus to each case, one, or in less than 20% of cases, two or more six-digit code(s) of the Long List of IPCCC. Cases of PDA, as well as persistent oval foramen were excluded. Each case included in the study was then classified into one (and only one) of the 10 main categories of the ACC-CHD.20 This classification scheme is based on a multidimensional approach encompassing anatomy, echocardiography, clinical and surgical management criteria. ACC-CHD includes 10 main categories, ordered in accordance with the direction of blood flow, and 23 subcategories. It is designed to use the code numbers of the Long List of IPCCC, but can accommodate ICD10 codes.

Data analysis

The main outcome variables were total and live birth prevalence of CHD, proportion with prenatal and the timing of postnatal diagnosis, TOPFA and infant, including neonatal (<28 days) and postneonatal (28 days–1 year) mortality. These variables were assessed for: (1) All CHD combined, (2) CHD, excluding chromosomal anomalies, (3) CHD, excluding chromosomal anomalies and anomalies of other systems, including genetic syndromes; that is, subgroup of ‘isolated’ CHD, which comprised cases with one or more CHD but no other associated anomalies, (4) ‘isolated’ major CHD, that is, isolated CHD after exclusion of cases with isolated ventricular septal defect (VSD), and (5) the 10 main categories of CHD in the ACC-CHD classification.

We reported on the outcomes of the study (prevalence, timing of diagnosis and mortality of infants with CHD) for all CHD as well as separately for the categories, 2–5 above, as they provide complementary information, in particular, for assessing the effects of associated anomalies and type of CHD. Subgroup (2), allows ‘removal’ of any effects on the outcomes studied that may be due to chromosomal anomalies (eg, a higher rate/earlier timing of diagnosis, higher rates of terminations and mortality for cases associated with chromosomal anomalies), and subgroup (3) removes, in addition, any effects that may be due to any other anomalies. Outcomes for the latter subgroup ((3), ie, ‘isolated’ CHD) may be of particular interest to cardiologists as they concern CHD alone. The last subgroup (4) was constituted in order to represent ‘major’ isolated CHD by excluding isolated VSD, which for the most part (other than larger VSD which are a minority of all VSD) comprises benign CHD that does not require intervention.

Prevalence of overall and subgroups or categories of CHD were calculated together with 95% Poisson exact confidence intervals (CIs). Proportions were calculated with 95% binomial exact CIs.

Results

Study population

The total number of births in the study population base (live births plus stillbirths) was 317 538, which included 314 022 live births. The total number of CHD cases included in the study was 2867, including 2348 live births (82%), 466 TOPFA (16.2%) and 53 foetal deaths (1.8%).

Table 1 shows the number and proportion of all, as well as subgroups of CHD in the EPICARD study, and their associations with chromosomal and/or anomalies of other systems, including genetic syndromes. Of the total number of 2867 cases included in the study, approximately 71% were ‘isolated’, 14% were associated with chromosomal anomalies, and 15% with anomalies of other systems, including genetic syndromes. Of the patients with a CHD that was not associated with a chromosomal anomaly but had other associated anomalies, approximately 19% had an identified genetic syndrome, which accounted for about 3% of all cases included in the study.

Table 1

Distribution of categories of congenital heart defects (ACC-CHD*) and associated anomalies: the EPICARD study

VSD (n=1492) comprised more than half the cases (52%). The second largest group was ‘anomalies of the ventricular outflow tracts’ (n=563), which accounted for about 20% of cases. The smallest groups were ‘congenital anomalies of the coronary arteries’ (n=9), ‘complex anomalies of atrioventricular connections’ (n=13), and ‘anomalies of the venous return’ (n=31), which together comprised less than 2% of the cases.

There were large differences in the frequency of associated anomalies across the 10 groups. Anomalies of the atrioventricular junctions and valves were most likely to be associated with chromosomal anomalies (∼57%), whereas, anomalies of the extrapericardial arterial trunks and heterotaxy, including isomerism and mirror-imagery, were most frequently associated with anomalies of other systems (∼31% and ∼24% of cases, respectively).

Pregnancy outcomes and prevalence

Table 2 shows the pregnancy outcomes as well as total and live birth prevalence of CHD, and categories of the ACC-CHD. Of the total number of 2867 cases included in the study, 2348 (82%) were live births, 466 were (TOPFA ∼16%) and 53 stillbirths (∼2%).

Table 2

Total and live birth prevalence of congenital heart defects: the EPICARD

For ‘isolated’ CHD, TOPFA was 6%. TOPFA were most likely to occur for more complex defects, notably heterotaxy, including isomerism and mirror-imagery (∼76%), functionally univentricular hearts (∼63%), and complex anomalies of atrioventricular connections (∼46%).

Overall, the total prevalence of CHD was 90.3 per 10 000 (95% CI 87.0 to 93.6), and the live birth prevalence was 74.8 per 10 000 (95% CI 71.8 to 77.8). Total and live birth prevalence of CHD, excluding chromosomal anomalies were 77.8 and 70.2 per 10 000, respectively, and for ‘isolated’ CHD, 64.1 and 60.2 per 10 000, respectively.

The most prevalent groups other than VSD, which had a total prevalence of 47.0 per 10 000, were ‘anomalies of the ventricular outflow tracts’ (total prevalence 17.7 per 10 000) and ‘anomalies of the atrioventricular junctions and valves’ (total prevalence 6.7 per 10 000). ‘Congenital anomalies of the coronary arteries’ (total prevalence 0.3 per 10 000), ‘complex anomalies of atrioventricular connections’ (0.4 per 10 000), and ‘anomalies of the venous return’ (1.0 per 10 000) had the lowest prevalence among the categories of CHD.

Timing of diagnosis

Table 3 shows the proportion of cases diagnosed prenatally, and timing of postnatal diagnosis for cases of CHD not associated with a chromosomal anomaly. Overall, 25.6% (95% CI 23.9 to 27.3) of cases were diagnosed prenatally. For ‘isolated’ CHD, the proportion with prenatal diagnosis was 23.0%; when isolated VSD were excluded, the proportion with prenatal diagnosis increased to 40.2% (95% CI 37.0 to 43.4).

Table 3

Pre- and postnatal diagnosis of congenital heart defects not associated with chromosomal anomalies: the EPICARD study

The category of ACC-CHD most likely to have a prenatal diagnosis was ‘complex anomalies of the atrioventricular connections’ (n=13, 100% diagnosed prenatally). This category included double discordance with associated defects, and the majority of cases were coded with more than the IPCCC code, suggesting the complexity of CHD with a combination of different cardiac anomalies. Other categories with high probability of prenatal diagnosis were: ‘functionally univentricular hearts’ (92.5%), and ‘heterotaxy’, including isomerism and mirror-imagery (89.2%). ‘Congenital anomalies of the coronary arteries’ (0%), ‘anomalies of the atria and interatrial communications’ (4.3%) and VSD (9.6%) were least likely to be diagnosed prenatally.

Overall, 28.7% of ‘isolated’ CHD-VSD excluded had a postnatal diagnosis before 7 days of life (40.2% had been prenatally diagnosed, as noted above), 10.4% between the first and fourth weeks of life, 14.4% between the first and third month of age, and 5.6% after 3 months of age; 0.7% had a postmortem diagnosis. Postneonatal (after the first 4 weeks of life) diagnoses were most likely to occur for ‘congenital anomalies of coronary arteries’ (100% diagnosed after the first 4 weeks of life), ‘anomalies of the atria and interatrial connections’ (∼38%), ‘anomalies of the venous return’ (∼32%), and ‘anomalies of the ventricular outflow tracts’ (∼20%). Of the VSD, approximately 14%, and of the ‘anomalies of the extrapericardial arterial trunks’, 13% were diagnosed after the first 4 weeks of life.

Infant mortality

Table 4 shows neonatal (≤28 days), postneonatal (29 days to 1 year) and overall infant mortality of newborns in the EPICARD study. For all cases combined, the infant mortality was 6.4% (95% CI 5.5 to 7.5). Neonatal mortality accounted for about 60% of infant deaths, and more than one half of neonatal deaths occurred within the first week of life. Infant mortality was considerably lower for ‘isolated’ CHD (3.6%, 95% CI 2.8 to 4.6), whereas, infant mortality of ‘isolated’ CHD-VSD excluded was 8.7% (95% CI 6.8 to 10.9).

Table 4

Infant mortality of congenital heart defects: the EPICARD study

Both the risk and timing of mortality varied considerably across the categories of ACC-CHD. The highest risk of mortality was associated with functionally univentricular hearts (58.3%, 95% CI 43.2 to 72.4), with more than 70% of deaths occurring within the first week of life; most likely linked, at least in part, with the compassionate care policy for this group of CHD in many centres. Indeed, in this category (n=48), 52% (n=25) had a surgical intervention and 48% did not (n=23). Risk of mortality was 24% (6/25) in patients who underwent surgery versus 96% (22/23) for patients who did not have a surgical intervention. Risk of mortality was also high for ‘heterotaxy’, including isomerism and mirror-imagery (∼38%), ‘anomalies of the atrioventricular junctions and valves’ (∼28%), and ‘anomalies of the venous return’ (∼27%).

Infant mortality was approximately 12% for ‘anomalies of the extrapericardial arterial trunks’, and 8% for ‘anomalies of the ventricular outflow tracts’. By far the majority of deaths for ‘anomalies of the extrapericardial arterial trunks’ occurred within the first 4 weeks of life, whereas for ‘anomalies of the ventricular outflow tracts’, about half the number of deaths occurred after the first 4 weeks of life.

Discussion

Few population-based studies have examined the prevalence, timing of diagnosis, and mortality of newborns with CHD.1 ,5 ,7 ,14 Moreover, previous studies used the ICD10 code that has important shortcomings, including many doublets and inaccuracies as compared with the IPCCC, which provides a precise and detailed scheme for coding of CHD. To our knowledge, this is the first population-based study to use the IPCCC in order to assess the prevalence, timing of diagnosis, TOPFA, and infant mortality of newborns in a large prospective cohort study of CHD.

We found the total and live birth prevalence of CHD to be 90 and 75 per 10 000, respectively. ‘Isolated’ CHD accounted for more than two-thirds of the cases. About 40% of ‘isolated’ CHD-VSD excluded was diagnosed prenatally, with about one half of the remaining cases diagnosed before 7 days of age. Nevertheless, one in five cases of these major CHD was diagnosed after the fourth week of life, with approximately 6% of cases after the third month. The overall infant mortality of ‘isolated’ CHD-VSD excluded was 8.5% with about 40% of deaths occurring after the fourth week of life.

Our results allow, in particular, a population-based evaluation of the prevalence and role of associated anomalies in the timing of diagnosis and the probabilities of TOPFA and infant mortality for newborns with CHD. Timing of diagnosis was earlier and risk of TOPFA and infant mortality considerably higher for cases associated with other anomalies, particularly those associated with chromosomal anomalies and genetic syndromes.

Given the heterogeneity of CHD and the complexity of the IPCCC, we used a classification system for CHD (ACC-CHD)20 that is based on anatomic and clinical criteria, and provides a regrouping of CHD using the IPCCC codes. The ACC-CHD classification currently forms the scaffold of the CHD categories for the website of rare (‘orphan’) diseases (ORPHANET http://www.orpha.net). It is also being discussed as an organising principle for classification of CHD in the planned revisions for the upcoming 11th version of the WHO ICDs.

The timing of diagnosis, likelihood of TOPFA, as well as risk and timing of infant mortality, were highly variable across the categories of ACC-CHD, suggesting that it may be a useful measure of severity and, hence, predictor of outcomes of CHD. By allowing classification of all CHD into a relatively homogeneous set and a manageable number of categories, it can be useful for evaluation of the impact of timing of diagnosis and initial clinical management of CHD, and as a prognostic tool for prediction of short- and long-term outcomes of CHD. This classification has, in particular, the advantage of being inclusive of all CHD, whereas, other proposed measures (RACHS-1, Aristotle and the STS-EACTS scores21–24) are based on measures of risk for CHD that undergo surgical repair. However, the predictive performance of a severity score based on ACC-CHD needs to be evaluated using formal statistical analyses (eg, logistic regression with calculation of indices of discrimination and calibration), which was beyond the scope of the present, essentially descriptive study.

The anatomic basis of ACC-CHD also makes it potentially useful in etiologic studies aimed at assessing specific empirical associations between risk factors or exposures and subtypes of CHD.25 However, both the relative predictive performance of ACC-CHD versus other existing measures of severity of CHD and its utility as compared with other proposed classifications for assessing etiologic relations26 need to be studied further.

Our study has certain limitations. Even though our study which included almost 2900 cases of CHD is, to our knowledge, the largest population-based cohort study of CHD of its kind, given the prevalence of certain defects, the number of cases for certain categories of ACC-CHD was small. Hence, our estimates for these relatively rare defects had limited precision, as indicated by the wide CIs.

We did not include CHD diagnosed after the first year of life. However, this is likely to represent a small minority of CHD in our population, especially in the case of major defects. Moreover, our total and live birth prevalence of CHD were approximately the same or somewhat higher than those of European registries who are members of the EUROCAT, and include diagnoses after the first year of life.1

While the ACC-CHD categories take into account important heterogeneities that exist across the spectrum of CHD, important heterogeneities remain within each of the 10 main categories. The ACC-CHD classification also includes 23 subcategories to take some of this ‘residual’ heterogeneity into account. However, the ACC-CHD classification, as any other one, is a compromise between regrouping of ‘sufficiently similar’ defects, allowing a certain degree of heterogeneity unaccounted for by the classification.

It is difficult to know the extent to which our results may be generalisable to those in other population settings. Prevalence of CHD is known to vary across populations and over time.1 ,2 ,4 These variations are, in part, due to data issues, such as completeness of (pre- and postnatal) diagnosis and/or registration of cases, whether or not TOPFA are included, which (minor) anomalies are excluded, as well as duration of ascertainment, among others. Nevertheless, and notwithstanding possible ‘true’ differences in prevalence of CHD across populations, use of multiple sources of data, prospective registration of cases and standardised definition and expert coding of all cases of CHD, including the TOPFA, by paediatric cardiologists and foetal pathologists comprise important strengths of our study.

France pursues an active policy of prenatal diagnosis and tends to have higher proportions of cases prenatally diagnosed.27 ,28 This may be particularly true in the case for CHD,1 ,5 ,7 specifically in our population, which has wide access to specialised care. Moreover, both the probability and timing of TOPFA varies considerably across countries.28 ,29 This is, in part, due to differences in prenatal diagnosis, but also probability of termination once a prenatal diagnosis has been made.

Both the timing of diagnosis and risk of mortality were highly variable across the categories of an ACC-CHD20 based on the IPCCC code. This classification has the advantage of being all-inclusive and may be a useful tool for etiologic studies25 and for measuring the severity and predicting the outcomes of CHD. By allowing for adjustment of severity of CHD, the classification can also be useful for assessing the role of potentially prognostic factors for CHD, notably timing of diagnosis, the initial and longer-term postnatal medical and surgical management, as well as access to care and socioeconomic factors.

With the high survival rates observed for most categories of CHD, evaluation of long-term outcomes of newborns with CHD becomes increasingly important. In this regard, we believe that population-based cohort data as obtained in the EPICARD study, which includes standardised assessments of long-term neuro-developmental outcomes of newborns with CHD, can make a valuable contribution towards a full assessment of health outcomes for CHD.

Acknowledgments

We thank all study participants and their families as well as the healthcare professionals who participated in the recruitment of cases and collection of information for the EPICARD study. Without their help, this study would not have been possible.

Appendix

EPICARD Study group

Principal Investigators: François Goffinet, Babak Khoshnood.

Steering Committee: Damien Bonnet (Hôpital Necker Enfants Malades, AP-HP, Centre de référence M3C, Université Paris Descartes, Paris). Drina Candilis (Université Paris-Diderot, Paris). Anne-Lise Delezoide (Hôpital Robert Debré, AP-HP, Service de biologie du Développement, Université Paris-Diderot, Paris). François Goffinet (Groupe Hospitalier Cochin-Hôtel Dieu, AP-HP, Maternité Port-Royal et INSERM U953, Université Paris Descartes, Paris). Lucile Houyel (Hôpital Marie Lannelongue, Service de chirurgie des cardiopathies congénitales, Le Plessis-Robinson). Jean-Marie Jouannic (Hôpital Trousseau, AP-HP, Centre pluridisciplinaire de diagnostic. prénatal, UPMC, Paris). Babak Khoshnood (INSERM U953, Paris). Nathalie Lelong (INSERM U953, Paris). Suzel Magnier (Hôpital Robert Debré, AP-HP, Service de cardiologie, Paris). Jean-François Magny (Institut de Puériculture et de périnatologie, Service de néonatologie, Paris). Caroline Rambaud (Hôpital Raymond Poincarré, AP-HP, Service d'anatomie et cytologie pathologiques—Médecine légale, UVSQ, Garches). Dominique Salomon (INSERM U953, Paris). Véronique Vodovar (INSERM U953, Paris).

Project Coordination and Data Analysis Committee: François Goffinet, Babak Khoshnood, Nathalie Lelong, Anne-Claire Thieulin, Thibaut Andrieu, Véronique Vodovar.

Independent Data Monitoring Committee (URC Paris Centre et CIC Cochin Necker Mère Enfant): Maggy Chausson, Anissa Brinis, Laure Faure, Maryline Delattre, Jean-Marc Treluyer (Groupe Hospitalier Cochin-Hôtel Dieu, AP-HP, Université Paris Descartes, Paris).

External Scientific Committee: Gérard Bréart, Dominique Cabrol, Alain Sérraf, Daniel Sidi, Marcel Voyer.

Participating Centres: The Greater Paris Area (Paris and its surrounding suburbs) public (AP-HP) and private maternity units, Departments of Paediatric Cardiology and Paediatric Cardiac Surgery, paediatric cardiologists in private practice, Neonatal Intensive Care Units, Paediatric Intensive Care Units, Emergency Transfer Services (SMUR), Departments of Pathology, Sudden Death Centres, Departments of Family and Infant Protection (DFPE).

References

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Footnotes

  • T EPICARD Study Group are listed in the appendix 1.

  • Funding This work was supported by two grants from the French Ministry of Health (PHRC 2004 and 2008). Additional funding was provided by the AREMCAR (Association pour la Recherche et l'Etude des Maladies Cardiovasculaires) Association.

  • Competing interests None.

  • Ethics approval The EPICARD study was approved by the French National Committee of Information and Freedom (Commission nationale de l'informatique et des libertés).

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement Additional data may be available upon request subject to approval by the Steering Committee of the EPICARD study group.

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