Chromosomal analysis and short-term outcome of prenatally diagnosed complex congenital heart disease

Chromosomal analysis and short-term outcome of prenatally diagnosed complex congenital heart disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Chromosomal analysis and short-term outcome of prenatally diagnosed complex congenital heart disease Marcellino Verbeke, Laurens Hannes, Koen Devriendt, Kris Van den Bogaert, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5038076/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Congenital structural heart disease (CHD) is the leading cause of infant death from birth defects. Postnatal survival primarily depends on the type and severity of the defect. In addition, worse cardiac prognosis is observed when extra-cardiac anomalies (ECA) are associated. This retrospective chart review was aimed at finding markers for short-term outcome prediction of prenatally-diagnosed complex CHD, focusing in particular on the impact of CHD category, of CHD severity score and of prenatal or postnatal diagnosis of ECA or chromosomal anomalies on 4 primary outcomes: termination of pregnancy (TOP), intrauterine fetal demise, neonatal mortality and 1-year-survival rate. We reviewed medical files from 381 fetuses, presenting at our center between 2018 and 2021 with CHD for which prenatal advice by a pediatric cardiologist was sought. 341 fetuses met the inclusion criteria for the study. Twin pregnancies (7.62%; OR 4.76 (p<0.001)) and pregnancies resulting from assisted reproductive technology (7.33%; OR 2.44 (p<0.001)) were more prevalent compared to the general population. CHD categories and CHD severity scores, ranging from A (extremely high risk) to D (low risk), were assigned to each fetus. Prenatal or postnatal chromosomal microarray results were available for 232 fetuses (68%) and were abnormal in 30 (12.9%). Logistic regression analysis was used to determine significant predictors for the 4 primary outcomes. TOP was carried out significantly more with: prenatal genetic diagnosis (p<0.001), prenatal extracardiac symptoms (p<0.001), severity score A (p=0.045) and B (p=0.036). Survival was significantly lower with: prenatal extracardiac symptoms (p=0.002), prematurity (p=0.046), severity scores A (p=0.009) and B (p=0.004), and with univentricular heart. CHD severity score, chromosomal anomalies and ECA are determining factors for continuation of the pregnancy, for survival and for overall mortality, underscoring the importance of prenatal ultrasound and genotyping for prognostication of fetuses with CHD. Health sciences/Cardiology/Cardiovascular biology/Cardiovascular genetics Biological sciences/Genetics/Cytogenetics Health sciences/Health care/Diagnosis/Genetic testing Health sciences/Health care/Health services/Genetic services/Genetic counselling Health sciences/Diseases/Cardiovascular diseases/Congenital heart defects congenital heart defects chromosomal prenatal outcome Introduction Congenital heart disease (CHD) is the most common type of birth defect, occurring in about 1% of pregnancies and in 0.8% of live births 1,2 . Although surgical advances have improved the pooled survival rate of CHD to adulthood to about 90% 3 , CHD remains the leading cause of mortality from birth defects and imposes a heavy disease burden. Neonatal outcome of prenatally-diagnosed CHD primarily depends on the type and severity of the defect. CHD types are often grouped together in CHD categories based on shared morphology or embryological mechanisms. The most common prenatally diagnosed CHD categories are septal defects (16-48%), conotruncal heart defects (20%), left ventricle outflow tract obstruction (LVOTO, 7-21%), right-sided anomalies (5-7%), univentricular hearts (UVH) (5%) and heterotaxy (6%) 4–7 . Postnatal mortality ranges from 38% in UVH to 2.5% in ventricular septal defects 8,9 . However, outcome varies within each CHD category and even between individuals with the same CHD type. For example individuals with isolated d-transposition of the great arteries (d-TGA) have a better outcome compared to those with complex d-TGA 10 . Neonatal CHD outcome is further determined by perinatal CHD management, by pregnancy complications, such as prematurity, dysmaturity or multiple pregnancies, and by demographic parameters 5,11,12 . In addition, worse cardiac (and extra-cardiac) prognosis is observed when extra-cardiac anomalies (ECA) and/or genetic pathogenic variants are present 5,7 . The diagnostic yield of genetic testing highly depends on CHD type, family history and co-occurrence of ECA. The majority of CHD are non-syndromic (NS-CHD) (80%) and have a complex background with an interplay of hitherto unknown genetic and environmental factors. Chromosomal or genetic pathogenic variants are found in less than 5% of individuals with sporadic NS-CHD, increasing up to 10-30% for familial CHD, which represents 3-5% of the NS-CHD cohort 13–15 . Syndromic CHD (S-CHD), defined as CHD in association with additional congenital defects and/or abnormal growth (>2SD or <-2SD), development and/or behavior, represents 20% of the CHD cohort. Aneuploidy, including monosomy X and trisomy 21, 13 or 18, is observed in about 14% of individuals with S-CHD 16 , while submicroscopic copy number variants (CNVs) are identified by chromosomal microarray (CMA) or CNV sequencing (CNVseq) in 15-20% 4 . The spectrum of CHD-related pathogenic CNVs ranges from recurrent clinically recognizable CNV syndromes, like 22q11.2 deletion syndrome or Williams-Beuren syndrome, to partially overlapping CNVs with unique breakpoints comprising dosage-sensitive genes or regulatory elements. Pathogenic or likely pathogenic single nucleotide variants (SNVs), diagnosed by Sanger sequencing, by targeted gene panels or by exome or genome sequencing, are found in about 35-40% of individuals with S-CHD with normal CMA results 17–19 . When CHD is diagnosed prenatally, S-CHD is difficult to differentiate from NS-CHD, as assessment of facial features and development is impossible or limited, and some ECA, such as coloboma, minor limb defects or cleft palate, may be missed. Therefore, prenatal genetic testing is gaining importance in the prognostication of fetuses with complex CHD. Non-invasive prenatal testing is increasingly applied to screen for fetal aneuploidies, leading to diagnosis of trisomy 21, 18 or 13, even before CHD is diagnosed on prenatal ultrasound 20 . Although sensitivity to detect submicroscopic CNVs by NIPT is increasing, prenatal invasive CNV analysis by CMA or CNVseq is considered the gold standard to identify pathogenic CNV when complex CHD or S-CHD is diagnosed prenatally, with a diagnostic yield of about 10-15%, including fetuses with apparently isolated CHD on ultrasound 5–7,20 . In those with normal CNV results, a pathogenic genetic variant is found by prenatal trio exome sequencing (ES) in 5-21%, varying according to presence of ECA and/or to CHD type 5–7,21–23 . In a systematic review, comprising 18 studies, the yield of prenatal ES was 21%, 11% and 37% respectively in all fetuses with CHD, in fetuses with apparently isolated CHD and in fetuses with CHD associated with ECA 23 . This single-center retrospective chart review is aimed at finding markers for short-term outcome prediction of prenatally-diagnosed complex CHD, focusing in particular on the impact of CHD category, of CHD severity score and of prenatal or postnatal diagnosis of ECA or submicroscopic pathogenic CNVs on 4 primary outcomes: termination of pregnancy (TOP), intrauterine fetal demise (IUM), neonatal mortality and 1-year-survival rate. Patients and methods Study approval Ethical approval to study these files was obtained from the ethical commission of KU and UZ Leuven (MP020190). Due to the retrospective nature of the study, the ethical commission of KU and UZ Leuven waived the need of obtaining informed consent. The study was conducted in accordance with the ethical standards of the Helsinki Declaration. Inclusion criteria Medical charts were reviewed from all fetuses or children who were diagnosed and/or followed prenatally with CHD at the obstetrics and pediatric cardiology department at University Hospitals Leuven (UZL) between January 1, 2018 and November 22, 2021. Inclusion was restricted to fetuses or children with CHD requiring prenatal counseling by a pediatric cardiologist at UZL, regardless of ethnic background, type of CHD on prenatal ultrasound, course of the pregnancy, neonatal outcome, and regardless of the eventual cardiac diagnosis made postnatally or post-mortem. Fetuses appearing to have a normal heart on first trimester ultrasound and diagnosed with fetal aneuploidy (trisomy 21, 18 or 13, or monosomy X) by non-invasive prenatal screening (NIPS) were excluded. Additional exclusion criteria were: (1) fetuses with prenatal diagnosis of arrhythmia, cardiomyopathy, left-sided superior caval vein or cardiac tumors in the absence of CHD, (2) children with postnatal diagnosis of CHD, (3) fetuses referred to UZL for a second opinion after CHD diagnosis in a different university hospital, (4) fetuses with CHD for whom no prenatal advice by a pediatric cardiologist was sought either because of a low risk CHD (not requiring neonatal intervention), or because of a suspected poor prognosis due to severe ECA (for which termination of pregnancy (TOP) was requested regardless of the cardiac prognosis). Data collection Medical information, demographic data and results from diagnostic genetic testing were retrieved from fetal, pediatric and maternal medical files, and were pseudonymized. Familial history of CHD (up to 3rd degree relatives) and/or familial occurrence of known pathogenic CNVs or SNVs for congenital or developmental disorders was recorded. Pregnancy information included: maternal age at the start of pregnancy, gravidity, spontaneous pregnancy versus assisted reproduction, singleton versus multiple pregnancy, and postmenstrual age (PMA) at the time of fetal CHD diagnosis. Pre- and postnatal CHD types were recorded based on the recordings by the pediatric cardiologist. ECA diagnosed either prenatally, at birth or at post-mortem investigation were documented. ECA included additional congenital anomalies, intrauterine growth restriction (IUGR), micro/macrocephaly, increased nuchal translucency and congenital anomalies with little or no functional impact (e.g. facial dysmorphic features, hyperechogenic bowel, single umbilical artery…). Acquired anomalies (e.g. ischemic or infectious brain damage, post-surgical diaphragm paralysis, feeding difficulties…) were not considered as ECA. Primary pregnancy outcomes were (1) termination of pregnancy, (2) intrauterine fetal demise, (3) live birth. Postnatal outcome was documented as (1) 1-year survival, (2) early postnatal demise (1 month <1 year). CHD categories and CHD severity scores CHD types were grouped together in CHD categories based on shared morphology or embryological mechanisms in accordance with the classification that was used by Gowda et al. 24 ( Table 1 ). Only one CHD category was ascribed to each fetus. If several CHD types were diagnosed, CHD classification was based on the most important prognostic and anatomical cardiac defect (e.g. isolated pulmonary valve atresia (PA), tetralogy of Fallot with PA and univentricular heart with PA were classified respectively as a right sided heart defect, conotruncal heart defect and univentricular heart). In addition, a severity score was assigned to each fetus based on the cardiac phenotype or the co-occurrence of additional major congenital anomalies and/or chromosomal aneuploidy. A 4-class scoring system (A, B, C or D) was applied as described by Gowda et al. 24 ( Supplementary Table 1 ). In summary, severity score A was assigned to CHD associated with severe potentially lethal ECA (e.g. congenital diaphragmatic hernia or hydrops fetalis), with aneuploidy or with genetic disorders associated with severe intellectual impairment (extremely high risk). Score B corresponds to isolated CHD requiring multiple surgeries and associated with high mortality after surgery (high risk). Score C (moderate risk) and score D (low risk) relate to isolated CHD with respectively variable and good prognosis after surgery. For severity scores A and B, the option of TOP was considered whenever legally permissible. For scores C and D continued monitoring of pregnancy with postnatal surgery was emphasized if applicable. Prenatal genetic work-up by CMA was recommended for fetuses with scores A or B, and CMA was offered, either prenatally or postnatally, for all other fetuses 25 . Isolated versus non-isolated CHD Fetuses were classified as having non-isolated CHD when associated with at least one of the following prenatal ultrasound findings: (1) additional major congenital anomaly, (2) microcephaly and/or IUGR (3.5 mm at 12 weeks of gestation), cystic hygroma or hydrops fetalis, (5) isomerism/situs anomalies. If prenatal phenotyping was restricted to the cardiac phenotype, fetuses were considered to have CHD with undetermined extracardiac status. Postnatal classification of non-isolated CHD was defined as CHD in association with at least one of the following criteria: (1) additional major congenital anomaly, (2) microcephaly and/or abnormal growth (+2.5 SD) taking gestational age at birth into consideration, (3) facial dysmorphic features (defined as the presence of at least 3 minor facial anomalies), (4) severe unexplained hypotonia or motor delay, (5) pathogenic or likely pathogenic CNVs or SNVs associated with developmental disorders. If postnatal development or growth could not be assessed due to intrauterine demise, termination of pregnancy or postnatal loss of follow-up, patients were considered to have CHD with undetermined extracardiac status. Genetic data The retrieval of genetic data was restricted to documented pathogenic or likely pathogenic CNV or SNV (in accordance to the ACMG guidelines for CNV or SNV classification) 26,27 which were identified by prenatal or postnatal CMA or sequencing. Prenatal CMA by OGT 60k array, postnatal CMA by OGT 180k array and NGS by clinical exome sequencing were performed as described 28–30 . NIPS was done as described 31 . Raw genetic data were not re-analyzed nor were newly generated for this retrospective chart review. Statistical analyses One sample t-test was used to compare mean values of continuous variables (e.g. maternal age, gestational age) and chi-square test (or Fisher exact test) to compare categorical variables (e.g. IVF versus spontaneous pregnancy, singleton versus twins) between the patient population and the Belgian reference population 32–34 . A logistic regression analysis was used to determine significant predictors for outcome. We took the possible influence of multiple variables on the pre- and postnatal outcome into account. This analysis was repeated for three different types of outcomes: TOP versus non-TOP in the entire prenatal CHD cohort. postnatal survival versus postnatal death in the subgroup of live births with a prenatally diagnosed CHD. Mortality (including TOP, IUM and postnatal death) versus survival across the entire prenatal cohort. Fetuses or live births with missing outcome data were excluded. Logistic regression was used on the entire prenatal population (n=341) for the dependent variables ‘TOP’ and ‘mortality’: TOP ~ prenatal genetic diagnosis + CHD category + severity score + prenatal extracardiac abnormalities. Mortality ~ prenatal genetic diagnosis + CHD category + severity score + prenatal extracardiac abnormalities. Logistic regression was used for the dependent variable ‘survival’ on the population of live births (n=277): Survival ~ prenatal genetic diagnosis + CHD type + prematurity + severity score + prenatal extracardiac abnormalities. Significance of the severity score was determined among the different CHD types: significance of severity scores A, B or C was determined in comparison to score D. The significance of the 8 different CHD categories was also determined among the different categories where each category was compared to the anomalous venous return category. Prematurity defined as birth <36 weeks PMA was compared to the cohort born ≥36 weeks PMA. P-values of <0.05 were judged as significant. Results Fetal cohort From January 2018 until November 2021 prenatal advice by the pediatric cardiologist was sought for 384 fetuses with prenatally diagnosed CHD. After exclusion of 43 fetuses (25 referrals from other university hospitals for second opinion; 5 without prenatal CHD; 5 with isolated arrhythmia; 4 with isolated cardiomyopathy; 3 with cardiac tumors and 1 with isolated left VCS), maternal and fetal data from 341 fetuses with CHD were reviewed ( supplementary figure 1 ). The average maternal age at the time of CHD diagnosis was 30.93 years (range 18-44), which is equal to the average maternal age of all pregnancies in Belgium in 2020 32 ( supplementary figure 2 ). The majority of pregnancies involved G1 (N=96) and G2 (N=98) pregnancies (supplementary figure 3 ). Twin pregnancies represented 7.62% of the fetal CHD cohort (26/341), including 10 DCDA, 14 MCDA and 2 MCMA twins (including one MCDA twin with CHD in both fetuses). At least 25 pregnancies (7.33%) were documented to have occurred after assisted reproduction by in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI). Familial history was positive for CHD (regardless the CHD type) in 40 out of 341 fetuses (11.73%), with respectively 4.99%, 2.34% and 4.4% having at least one first, second or third-degree relative with CHD. Prenatal CHD diagnosis The average postmenstrual age (PMA) at CHD diagnosis at our center was 25.29 weeks (Most diagnoses were made between PMA week 20-23, at week 30-31 or at week 36 ( supplementary figure 4 ). CHD categories and CHD severity scores were assigned to each fetus 24 . Conotruncal heart defects (33.72%) and LVOTO (18.77%) were the most common CHD categories ( Table 1 ). Severity scores A, B, C and D were assigned respectively to 7%, 40%, 34% and 19% of the fetuses ( Table 2 ). Table 1. CHD categories (and common CHD types per category). Distribution of CHD categories within this study was compared to that of previously reported cohorts (4-7,27). Abbreviations: Art: arteriosus; AS: aortic stenosis; AVR: anomalous venous return; CoAo: aortic coarctation; CHD: congenital heart defect; DORV: double outlet right ventricle; d-TGA: dextro-transposition of great arteries; IAA: interrupted aortic arch; LVOTO: left ventricle outflow tract obstruction; PS: pulmonary valve stenosis; RAA: right aortic arch; TA: tricuspid atresia; TOF: tetralogy of Fallot; UVH: univentricular heart. CHD categories and types number % Hureaux et al. Qiao et al. van Nisselrooij et al. Gowda et al. Stallings et al. Average literature conotruncal ToF, d-TGA, truncus art 115 33.72 25% 25% 19.77% 32.85% 39.54% 28.43% LVOTO AS, CoAo, IAA 64 18.77 21% 7.22% 15.82% 25.55% 33.76% 20.67% UVH HLHS 39 11.44 21% NA 9.46% 5.84% 18.28% 13.65% septal VSD, ASD, AVSD 36 10.56 16% 48.34% 20.34% 32.85% NA 29.38% right-sided PS, TA, DORV 31 9.09 5% 6.94% 16.65% 32.85% 25.02% 17.29% situs anomaly heterotaxy, left/right isomerism 16 4.69 NA 5.83% 1.69% 4.37% NA 3.96% AVR TAPVR, PAPVR 9 2.64 NA NA 2.54% 8.03% 6.64% 5.74% other RAA 31 9.09 12% 6.67% 13.42% 1.46% NA 8.39% total 341 100 Table 2. CHD severity scores (from score A to D) based on the scoring system reported by Gowda et al. (27) and available in supplementary table 1 . CHD severity score score A score B score C score D total Number 24 136 116 65 341 % 7% 40% 34% 19% 100% Gowda et al. 10% 45.5% 20.5% 24% Non-isolated CHD Non-isolated CHD was diagnosed prenatally in 86 out of 341 (25%) fetuses, of which 63% (54/86) were confirmed postnatally or post-TOP to have a syndromic entity, 16% (14/86) were considered to have isolated CHD at birth, 8% (7/86) were diagnosed with situs anomalies and 13% (11/86) could not be assessed due to insufficient phenotypic information after birth or post-TOP. In the cohort of 277 liveborn, 60 individuals complied with the criteria of having non-isolated CHD (22%, 60/277)) and 37 individuals could not be assigned to either class due to insufficient information regarding growth or development (13%; 37/277). Forty-three liveborns with non-isolated CHD (72%; 43/60) were diagnosed with ECA prenatally. The remainder (17/60; 28%) presented prenatally with apparently isolated CHD. NIPS results NIPS results were available for 154 pregnancies (45%), retrieving 7 abnormal results (trisomy 7 (2x), 18, 20, 21 (2x) and 22q11 deletion), 4 of which (T7 (2x), T20 and T21 (1x)) could not be confirmed by prenatal CMA on amniotic fluid due to false positive results or to confined placental mosaicism. The fetuses with confirmed T18, T21 and 22q11DS had a diagnosis of CHD on prenatal ultrasound prior to performing NIPS. NIPS was not performed or results were not available for the other 187 pregnancies. CMA results After excluding fetuses with an abnormal NIPS, CMA results were available for 232 fetuses (68%, 232/341), either performed prenatally (N=126) or after birth/TOP (N=106). Pathogenic or likely pathogenic chromosomal variants were identified for 30 patients either prenatally (N=18; 18/126 (14%)) or postnatally (N=12; 12/106 (11%)) ( table 3; supplementary table 2 ). The most common chromosomal disorders were 22q11.2 deletion syndrome (N=10) and trisomy 21 (N=4) ( supplementary table 3 ) . For 27 fetuses with normal prenatal CMA results, CMA was repeated postnatally by 180k OGT array, but did not yield additional pathogenic variants. In accordance with the Belgian guidelines for variant reporting of prenatal genetic testing 28 , CNVs of unknown significance (VUS) identified by prenatal CMA were not communicated. These regulations did not apply for postnatal CMA results, reporting back VUS for 21 liveborn children who only had postnatal CMA analysis (N=107) or who had both prenatal and postnatal CMA analysis (N=27) (15.5%; 21/134). None of these VUS were reclassified as pathogenic or likely pathogenic after parental segregation analysis and clinical assessment. We also compared CMA results between fetuses with and without prenatal diagnosis of ECA. Pre- or postnatal CMA results were available for 135 fetuses with prenatal apparently isolated CHD, for 68 fetuses with non-isolated CHD and for 29 fetuses with undetermined extracardiac status, and identified pathogenic CNVs in respectively 7.4% (10/135), 27.9% (19/68) and 3.4% (1/29) fetuses. Table 3. Diagnostic yield by prenatal (PREN) or postnatal (POST) chromosomal microarray analysis (CMA) in fetuses with apparently isolated versus non-isolated CHD on prenatal ultrasound. Chromosomal pathogenic variants identified by NIPS were excluded. ECA status CMA total positive negative diagnostic yield (%) isolated-CHD N=206 PREN CMA 60 5 55 POST CMA 75 5 70 135 10 125 7.4% non-isolated CHD N= 86 PREN CMA 43 13 30 POST CMA 25 6 19 68 19 49 27.9% CHD of unknown ECA status N=49 PREN CMA 23 0 23 POST CMA 6 1 5 29 1 28 3.4% Total CHD cohort N=341 PREN CMA 126 18 108 POST CMA 106 12 94 232 30 202 12.9% NGS results NGS-based targeted gene panel testing or clinical exome sequencing (ES) was not systematically conducted, but was restricted to 16 individuals with diagnosis of non-isolated CHD and normal CMA results. Pathogenic or likely pathogenic SNVs were retrieved by prenatal NGS in 1 patient ( RIT1 ) and by postnatal (or post-TOP) NGS in 11 patients ( KMT2D (2x) , PTPN11, RAF1, SON, DYNC2H1, PBX1, FOXF1, SMARCA4, KAT6A, PAH ). Variants of unknown significance, inherited from an unaffected parent, were reported in 2 patients ( FLT4, SMAD6 ). Outcome Prenatal outcome was not documented for 16 out of 341 pregnancies. The pregnancy in the remaining 325 fetuses ended either in TOP, an intrauterine demise or a live birth in respectively 44 (13.5%), 4 (1.2%) and 277 (85.3%) pregnancies. Early (1 month) postnatal demise were documented for respectively 33 (11.9%) and 15 (5.5%) liveborn children (N=277). Full-term and premature birth (<36 weeks PMA) was recorded for respectively 232 and 31 liveborn children. Extreme prematurity (≤28 weeks PMA) was documented in 7 children. PMA at birth was not available for 14 liveborn children. Prenatal and postnatal outcome according to CMA results, CHD category, CHD severity score and multiple pregnancies are summarized in Table 4 . Table 4. Pregnancy outcomes in accordance to severity score, CHD category, genetic diagnosis and singleton versus multiple pregnancy. Abbreviations: AVR: anomalous venous return; IUM: intra-uterine demise; LVOTO: left ventricle outflow tract obstruction; TOP: termination of pregnancy; UVH: univentricular heart. numbers TOP IUM unknown live birth mortality < 1 month mortality 1-12 months survival to 12 months pregnancy singleton 315 43 (13.65%) 4 (1.27%) 15 (4.76%) 253 (80.32%) 29 (9.21%) 14 (4.44%) 210 (66.67%) multiple 26 1 (3.85%) 0 1 (3.85%) 24 (92.31%) 4 (15.38%) 1 (3.85%) 19 (73.08%) genetic diagnosis yes 45 12 (26.7%) 0 1 (2.2%) 32 (71%) 8 (17.8%) 1 (2.2%) 23 (51%) no 296 32 (10.8%) 4 (1.35%) 15 (5%) 245 (82.7%) 25 (8.4%) 14 (4.7%) 206 (69.6%) severity score A 24 9 (37.50%) 0 2 (8.33%) 13 (54.17%) 3 (12.50%) 3 (12.50%) 7 (29.17%) B 136 30 (22.06%) 4 (2.94%) 10 (7.35%) 92 (67.65%) 24 (17.65%) 9 (6.62%) 59 (43.38%) C 116 4 (3.45%) 0 2 (1.72%) 110 (94.83%) 6 (5.17%) 2 (1.72%) 102 (87.93%) D 65 1 (1.54%) 0 2 (3.08%) 62 (95.38%) 0 1 (1.54%) 61 (93.85%) CHD category conotruncal 115 6 (5.22%) 1 (0.87%) 3 (2.61%) 105 (91.30%) 7 (6.09%) 5 (4.35%) 93 (80.87%) LVOTO 64 5 (7.81%) 1 (1.56%) 3 (4.69%) 55 (85.94%) 7 (10.94%%) 3 (4.69%) 45 (70.31%) UVH 39 18 (46.15%) 0 3 (7.69%) 18 (46.15%) 10 (25.64%) 3 (7.69%) 5 (12.82%) Septal 36 6 (16.67%) 0 2 (5.56%) 28 (77.78%) 2 (5.56%) 0 26 (72.22%) Right-sided 31 5 (16.13%) 1 (3.23%) 2 (6.45%) 23 (74.19%) 4 (12.90%) 0 19 (61.29%) Situs anomaly 16 2 (12.5%) 1 (6.25%) 3 (18.75%) 10 (62.50%) 0 4 (25.00%) 6 (37.50%) AVR 9 0 0 0 9 (100.00%) 3 (33.33%) 0 6 (66.67%) other 31 2 (6.45%) 0 0 29 (93.55%) 0 0 29 (93.55%) Total all 341 44 (12.9%) 4 (1.17%) 16 (4.69%) 277 (81.23%) 33 (9.68%) 15 (4.40%) 229 (67.16%) Markers for outcome Logistic regression was performed to find variables predisposing to ‘TOP’, to overall ‘mortality’ (fetal death, TOP or postnatal demise (<1 year)) and to postnatal ‘survival’ beyond the age of 1 year. Logistic regression analysis with outcome TOP determined that prenatal genetic diagnosis (p<0.001), prenatal extracardiac symptoms (p=0.045), severity score A (p=0.021) and severity score B (p=0.036) were significant contributing factors in the decision for TOP. Significance of the severity scores A, B and C was determined versus severity score D. Scores A and B were significantly more associated with TOP than score D. There was no significant difference between scores C and D. When using the CHD category ‘anomalous venous return’ as a reference, none of the 8 CHD categories had sufficient power in this model to determine significant association with TOP. No significant results were obtained if other CHD categories were used as a reference. Logistic regression analysis for postnatal survival determined that prenatal extracardiac symptoms (p=0.002), prematurity of <36 weeks PMA (p=0.046) and severity score A (p=0.009 and B (p=0.004) had a significant negative impact on survival of a life birth with a complex CHD. When using univentricular heart as a reference for each other CHD category, we determined that there is a lower chance of postnatal survival in live births with a univentricular heart compared to patients with conotruncal abnormalities (p=0.009) or right sided cardiac abnormalities (p=0.02) Logistic regression analysis for total mortality determined significance for prenatal extracardiac symptoms (p<0.001) and severity score A (p<0.001), B (p<0.001) and C (p=0.046) in the full cohort (n=341). These factors significantly increase the chances of mortality. Furthermore, the CHD categories conotruncal abnormalities (p=0.003) and LVOTO (p=0.041) had a significantly lower chance of mortality if we normalized versus the univentricular heart category. Discussion Early and accurate prenatal diagnosis of CHD is crucial to optimize perinatal care to reduce CHD-related mortality and to improve quality of survival. However, risk stratification after prenatal diagnosis of CHD remains challenging 35 . Heart anatomy and coexisting congestive heart failure, reflected by ultrasound markers such as cardiomegaly, hydrops, abnormal myocardial function or abnormal venous Doppler, play the most important role in fetal and postnatal survival, underlying the importance of longitudinal prenatal echocardiographic examination for individualized outcome prediction of fetuses with CHD 36,37 . In this single-center retrospective chart review of 341 fetuses with CHD, we showed that in addition to high CHD severity scores (A or B) other factors such as prenatal diagnosis of pathogenic CNVs and prenatal co-occurrence of extracardiac anomalies were significantly associated with a decision to terminate pregnancy as well. This is in line with the study of Qiu et al. showing that more complex CHD and presence of ECA were inversely correlated with continuation of the pregnancy 36 . In addition, prenatal diagnosis of ECA and high CHD severity score, as well as prematurity <36 weeks PMA, were negatively correlated with postnatal survival beyond the age of 1 year. These results showed that prenatal cardiac and extracardiac phenotyping, complemented with prenatal genotyping, aid to provide adequate counseling to parents of fetuses with CHD with respect to postnatal survival rates. In this cohort of prenatally diagnosed complex CHD, the pregnancy was terminated in 13% and was complicated by fetal death in 1%. Pregnancy outcome was not documented in 4.5%. The overall postnatal mortality in our cohort was 17% (4wk in 15/277 liveborn children), which is similar to previous studies 24 ( table 4 ). Survival was significantly lower in fetuses with UVH compared to conotruncal CHD and right sided-CHD. Larger sample sizes per CHD category are required to attain sufficient statistical power to accurately associate CHD categories to TOP decisions or to short- or long-term survival. Ultrasound markers for outcome prediction, as described by Wieczorek et al. 37 and Qiu et al. 36 , were not available and therefore the use of ultrasound parameters, such as the cardiovascular profile score, could not be applied. The distribution of CHD categories in this study aligns well with the average distribution based on previously reported prenatal CHD cohorts 4–7 . ( Table 1 ). Differences between individual reports is likely due to differences in classification of CHD categories. In this study, each fetus was attributed to only one CHD category based on the CHD type that was anatomically or prognostically most prominent, explaining the relatively low prevalence of septal defects in our cohort. Prenatal counseling by pediatric cardiologists in our center is less frequently requested in fetuses with CHD of lower complexity (CHD severity score D) or in fetuses with chromosomal aneuploidy en/or life-threatening ECA (CHD severity score A). Therefore, a shift towards CHD severity score C was observed, in comparison to the CHD severity distribution reported by Gowda et al. 24 . ( Table 2 ). As expected, TOP and postnatal mortality were significantly higher among fetuses with severity scores A and B compared to severity score D, while scores A, B and C are associated with higher overall mortality. We used the same parameters to score CHD severity as those introduced by Gowda et al. 24 . Although the distribution of CHD severity scores was comparable between both cohorts (except for score C which was more represented in our study population), we observed in our CHD cohort a higher survival rate beyond 6 months: overall (67% versus 40%) and across the subgroups with scores A (29% versus 7%), B (44% versus 9.7%) and C (88% versus 55.6%). These differences were related to a lower fetal death rate (1% versus 11.7%) and lower neonatal mortality (9.6% versus 24.1%), which may be due to differences in TOP policy as a more restrictive TOP policy may add to higher mortality rates. Large sample size follow-up studies are required to confirm these findings. A significantly higher rate of multiple pregnancies (7.62%;p<0.001) and of IVF/ICSI pregnancies (7.33%;p<0.001) was observed in this CHD cohort compared to the general population (twinning rate of 1.6% and IVF/ICSI rate of 5.1% according to the 2019 report of the Flemish Center for Study of Perinatal Epidemiology). Compared to singletons, multiple pregnancies are known to be at increased risk of CHD, particularly among monochorionic twins due to altered intra-uterine hemodynamics 38–41 . In addition, we confirm the findings of Giorgione et al. showing that assisted human reproduction by IVF or ICSI was associated with a higher CHD incidence as well (odds ratio 1,45) 40,42 . CHD (of any type) in first-degree relatives was documented in 4.99% fetuses with CHD, which is similar to previous reports on familial CHD 43 . A pathogenic variant was identified by pre- or postnatal CMA in 27.9% of fetuses presenting prenatally with non-isolated CHD. Nine additional fetuses from this subgroup were diagnosed by NGS with a pathogenic SNV. The diagnostic yield of chromosomal testing in fetuses with apparently isolated CHD (N=206) or with CHD of undetermined extracardiac status (N=49) was significantly lower (5.8%; 1 by NIPS, 5 by prenatal CMA, 6 by postnatal or post-TOP CMA, 3 by WES). All these patients presented with ECA at birth or post-mortem, despite having an isolated CHD on prenatal ultrasound ( supplementary table 3 ). Our results are in line with those by van Nisselrooij et al. reporting chromosomal or genetic pathogenic variants in 15%: in 28.7% of fetuses with non-isolated CHD and in 11% of fetuses with apparently isolated CHD on prenatal ultrasound 7 . The most common chromosomal and genetic syndromes in fetuses with CHD identified by us and others 7 were 22q11 deletion syndrome and Noonan syndrome. We also confirmed that CHD categories ‘septal defects’ (AVSD and VSD) and ‘LVOTO’ (interrupted aortic arch and CoAo) were associated with the highest yield of genetic testing, respectively in 19.4% and 20.3% ( supplementary Table 2 ). Results from NIPS were available for 45% of fetuses (154/341), which is lower compared to the uptake of NIPS in the general population of pregnant women in Belgium (78.7%), where NIPS is available as a publicly funded nationwide first-tier screening as of July 2017 44 . Prenatal invasive testing is preferred over NIPS when first trimester ultrasound is abnormal, which explains the lower uptake in the CHD cohort. Since fetal aneuploidy (T21, T18 or T13) weighs heavily on the decision to terminate pregnancy regardless of the presence of CHD 45 potentially causing a bias with respect to outcome prediction in this study, we excluded fetuses with abnormal non-invasive aneuploidy screening prior to the diagnosis of CHD on prenatal ultrasound. NGS was performed in only a small subset of patients, either presenting with prenatal features of a rasopathy as described 46 , explaining the high incidence of Noonan syndrome in our cohort, or presenting postnatally or post-mortem with unexplained non-isolated CHD. The outcome measures of this retrospective study were restricted to pregnancy continuation, overall mortality and postnatal survival. Long-term follow-up data on growth, development, behavior or survival into infancy were not available. ‘CHD category’, ‘extracardiac anomalies’ and ‘CHD severity score’ were included in the logistic regression outcome prediction model. However, as CHD severity scores were based on CHD type and on the presence of ECA, these variables are not independent, potentially impacting the results. As previously mentioned, CMA analysis was offered, either prenatally or postnatally, for all fetuses, but CMA results were available for only 68%, failing us to provide insight into chromosomal anomalies in the full cohort. NGS was not offered systematically, and was restricted to fetuses or live born children with non-isolated CHD and normal CMA results. This NGS policy is a limitation of this study. As NGS technology becomes broadly available and sequencing costs are dropping, ultrarapid trio exome or genome sequencing emerges as the standard-of-care prenatal genetic test when non-isolated CHD is diagnosed, and could be considered in fetuses with apparently isolated complex CHD despite the low diagnostic yield. However, when moving from postnatal to prenatal genetic testing, some challenges need to be taken into consideration, including technology availability, access to health care, health insurance issues and sociocultural differences. Moreover, short turn-around-times should be guaranteed and adequate pre-test counseling is required, dealing with diagnostic yield, risks of invasive prenatal procedures and the reporting of incidental findings. Expectations and preferences of the parents should be prioritized when offering prenatal genomic testing. In conclusion, we showed that cardiac and extracardiac phenotyping by prenatal ultrasound and elaborate prenatal genetic testing are crucial to provide adequate counseling to parents of fetuses with CHD with respect to postnatal survival rates. Conclusion Data availability The dataset generated and analysed during this retrospective study is not publicly available due to the sensitive nature of the data. However, inquiries regarding the dataset and its use can be directed to the corresponding author upon reasonable request. Acknowledgements The authors would like to thank the patients and their families for their participation. Author contributions J.B. and M.V. conceptualized the study, J.B., K.D., K.V.d.B, B.C., L.D.C. and M.G. retrospectively included patients. M.V. reviewed medical files and collected relevant data. J.B., M.V. and L.H. analyzed the data and wrote the main text of the manuscript. All authors reviewed the manuscript. Funding sources J.B. is funded by a clinical investigator fellowship by FWO-Flanders. Conflict of interest The authors declare no conflicts of interest. References van der Linde, D. et al. Birth Prevalence of Congenital Heart Disease Worldwide. Journal of the American College of Cardiology 58 , 2241–2247 (2011). Wu, W., He, J. & Shao, X. Incidence and mortality trend of congenital heart disease at the global, regional, and national level, 1990-2017. Medicine 99 , (2020). Best, K. E. & Rankin, J. Long‐Term Survival of Individuals Born With Congenital Heart Disease: A Systematic Review and Meta‐Analysis. 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Genetics in medicine : official journal of the American College of Medical Genetics 22 , 245–257 (2020). Richards, S. et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genetics in Medicine 17 , 405–424 (2015). Vanakker, O. et al. Implementation of genomic arrays in prenatal diagnosis: The Belgian approach to meet the challenges. European Journal of Medical Genetics 57 , 151–156 (2014). Breckpot, J. et al. Copy number variation analysis in adults with catatonia confirms haploinsufficiency of SHANK3 as a predisposing factor. European Journal of Medical Genetics 59 , 436–443 (2016). Winters, L. et al. Massive parallel sequencing identifies RAPSN and PDHA1 mutations causing fetal akinesia deformation sequence. European Journal of Paediatric Neurology 21 , 745–753 (2017). Lannoo, L. et al. 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Prenatal diagnosis and pregnancy outcomes of 1492 fetuses with congenital heart disease: role of multidisciplinary-joint consultation in prenatal diagnosis. Scientific Reports 10 , (2020). Wieczorek, A. et al. Prediction of outcome of fetal congenital heart disease using a cardiovascular profile score. Ultrasound in Obstetrics and Gynecology 31 , 284–288 (2008). Bahtiyar, M. O., Dulay, A. T., Weeks, B. P., Friedman, A. H. & Copel, J. A. Prevalence of Congenital Heart Defects in Monochorionic/Diamniotic Twin Gestations. Journal of Ultrasound in Medicine 26 , 1491–1498 (2007). Herskind, A. M., Almind Pedersen, D. & Christensen, K. Increased Prevalence of Congenital Heart Defects in Monozygotic and Dizygotic Twins. Circulation 128 , 1182–1188 (2013). Panagiotopoulou, O. et al. Congenital heart disease in twins: The contribution of type of conception and chorionicity. International Journal of Cardiology 218 , 144–149 (2016). Best, K. E. & Rankin, J. Original article: Increased risk of congenital heart disease in twins in the North of England between 1998 and 2010. Heart 101 , 1807 (2015). Giorgione, V. et al. Congenital heart defects in IVF/ICSI pregnancy: systematic review and meta-analysis. Ultrasound in Obstetrics & Gynecology 51 , 33–42 (2018). Calcagni, G., Digilio, M. C., Sarkozy, A., Dallapiccola, B. & Marino, B. Familial recurrence of congenital heart disease: an overview and review of the literature. European Journal of Pediatrics 166 , 111–116 (2006). Van Den Bogaert, K. et al. Outcome of publicly funded nationwide first-tier noninvasive prenatal screening. Genetics in Medicine 23 , 1137–1142 (2021). Shaffer, B. L., Caughey, A. B. & Norton, M. E. Variation in the decision to terminate pregnancy in the setting of fetal aneuploidy. Prenatal Diagnosis 26 , 667–671 (2006). Stuurman, K. E. et al. Prenatal ultrasound findings of rasopathies in a cohort of 424 fetuses: update on genetic testing in the NGS era. Journal of Medical Genetics 56 , 654–661 (2019). Additional Declarations No competing interests reported. Supplementary Files supplementalmaterial.docx Cite Share Download PDF Status: Published Journal Publication published 31 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 11 Nov, 2024 Reviews received at journal 08 Nov, 2024 Reviewers agreed at journal 05 Oct, 2024 Reviews received at journal 04 Oct, 2024 Reviewers agreed at journal 17 Sep, 2024 Reviewers invited by journal 11 Sep, 2024 Editor assigned by journal 11 Sep, 2024 Editor invited by journal 09 Sep, 2024 Submission checks completed at journal 06 Sep, 2024 First submitted to journal 05 Sep, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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07:03:31","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":423998,"visible":true,"origin":"","legend":"","description":"","filename":"supplementalmaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-5038076/v1/20d952c457d5d564449141d4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Chromosomal analysis and short-term outcome of prenatally diagnosed complex congenital heart disease","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCongenital heart disease (CHD) is the most common type of birth defect, occurring in about 1% of pregnancies and in 0.8% of live births\u0026nbsp;\u003csup\u003e1,2\u003c/sup\u003e. Although\u0026nbsp;surgical advances have improved the pooled survival rate of CHD to adulthood to about\u0026nbsp;90%\u0026nbsp;\u003csup\u003e3\u003c/sup\u003e,\u0026nbsp;CHD remains the leading cause of mortality from birth defects and imposes a heavy disease burden.\u0026nbsp;Neonatal outcome of prenatally-diagnosed CHD primarily depends on the type and severity of the defect. CHD types are often grouped together in CHD categories based on shared morphology or embryological mechanisms. The most common prenatally diagnosed CHD categories are septal defects (16-48%), conotruncal heart defects (20%), left ventricle outflow tract obstruction (LVOTO, 7-21%), right-sided anomalies (5-7%), univentricular hearts (UVH) (5%) and heterotaxy (6%)\u0026nbsp;\u003csup\u003e4\u0026ndash;7\u003c/sup\u003e.\u0026nbsp;Postnatal mortality ranges from 38% in UVH to 2.5% in ventricular septal defects\u0026nbsp;\u003csup\u003e8,9\u003c/sup\u003e.\u0026nbsp;However, outcome varies within each CHD category and even between individuals with the same CHD type. For example individuals with isolated d-transposition of the great arteries (d-TGA) have a better outcome compared to those with complex d-TGA\u0026nbsp;\u003csup\u003e10\u003c/sup\u003e.\u0026nbsp;Neonatal CHD outcome is further determined by\u0026nbsp;perinatal CHD management, by pregnancy complications, such as prematurity, dysmaturity or multiple pregnancies, and by demographic parameters\u0026nbsp;\u003csup\u003e5,11,12\u003c/sup\u003e.\u0026nbsp;In addition, worse cardiac (and extra-cardiac) prognosis is observed when extra-cardiac anomalies (ECA) and/or genetic pathogenic variants are present\u0026nbsp;\u003csup\u003e5,7\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe diagnostic yield of genetic testing highly depends on CHD type, family history and co-occurrence of ECA.\u0026nbsp;The majority of CHD are non-syndromic (NS-CHD) (80%) and have a complex background with an interplay of hitherto unknown genetic and environmental factors. Chromosomal or genetic pathogenic variants are found in less than 5% of individuals with sporadic NS-CHD, increasing up to 10-30% for familial CHD, which represents 3-5% of the NS-CHD cohort\u0026nbsp;\u003csup\u003e13\u0026ndash;15\u003c/sup\u003e. Syndromic CHD (S-CHD), defined as CHD in association with additional congenital defects and/or abnormal growth (\u0026gt;2SD or \u0026lt;-2SD), development and/or behavior, represents 20% of the CHD cohort. Aneuploidy, including monosomy X and trisomy 21, 13 or 18, is observed in about 14% of individuals with S-CHD\u0026nbsp;\u003csup\u003e16\u003c/sup\u003e, while submicroscopic copy number variants (CNVs) are identified by chromosomal microarray (CMA) or CNV sequencing (CNVseq) in 15-20%\u0026nbsp;\u003csup\u003e4\u003c/sup\u003e. The spectrum of CHD-related pathogenic CNVs ranges from recurrent clinically recognizable CNV syndromes, like 22q11.2 deletion syndrome or Williams-Beuren syndrome, to partially overlapping CNVs with unique breakpoints comprising dosage-sensitive genes or regulatory elements. Pathogenic or likely pathogenic single nucleotide variants (SNVs), diagnosed by Sanger sequencing, by targeted gene panels or by exome or genome sequencing, are found in about 35-40% of individuals with S-CHD with normal CMA results\u0026nbsp;\u003csup\u003e17\u0026ndash;19\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWhen CHD is diagnosed prenatally, S-CHD is difficult to differentiate from NS-CHD,\u0026nbsp;as assessment of facial features and development is impossible or limited, and\u0026nbsp;some ECA, such as coloboma, minor limb defects or cleft palate, may be missed. Therefore, prenatal genetic testing is gaining importance in the prognostication of fetuses with complex CHD. Non-invasive prenatal testing is increasingly applied to screen for fetal aneuploidies, leading to diagnosis of trisomy 21, 18 or 13, even before CHD is diagnosed on prenatal ultrasound\u0026nbsp;\u003csup\u003e20\u003c/sup\u003e. Although sensitivity to detect submicroscopic CNVs by NIPT is increasing, prenatal invasive CNV analysis by CMA or CNVseq is considered the gold standard to identify pathogenic CNV when complex CHD or S-CHD is diagnosed prenatally, with a diagnostic yield of about 10-15%, including fetuses with apparently isolated CHD on ultrasound\u0026nbsp;\u003csup\u003e5\u0026ndash;7,20\u003c/sup\u003e. In those with normal CNV results, a pathogenic genetic variant is found by prenatal trio exome sequencing (ES) in 5-21%, varying according to presence of ECA and/or to CHD type\u0026nbsp;\u003csup\u003e5\u0026ndash;7,21\u0026ndash;23\u003c/sup\u003e. In a systematic review, comprising 18 studies, the yield of prenatal ES was 21%, 11% and 37% respectively in all fetuses with CHD, in fetuses with apparently isolated CHD and in fetuses with CHD associated with ECA\u0026nbsp;\u003csup\u003e23\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThis single-center retrospective chart review is aimed at finding markers for short-term outcome prediction of prenatally-diagnosed complex CHD, focusing in particular on the impact of CHD category, of CHD severity score and of prenatal or postnatal diagnosis of ECA or submicroscopic pathogenic CNVs on 4 primary outcomes: termination of pregnancy (TOP), intrauterine fetal demise (IUM), neonatal mortality and 1-year-survival rate. \u0026nbsp;\u003c/p\u003e"},{"header":"Patients and methods","content":"\u003cp\u003e\u003cem\u003eStudy approval\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval to study these files was obtained from the ethical commission of KU and UZ Leuven (MP020190). Due to the retrospective nature of the study, the ethical commission of KU and UZ Leuven waived the need of obtaining informed consent. The study was conducted in accordance with the ethical standards of the Helsinki Declaration.\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInclusion criteria\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMedical charts were reviewed from all fetuses or children who were diagnosed and/or followed prenatally with CHD at the obstetrics and pediatric cardiology department at University Hospitals Leuven (UZL) between January 1, 2018 and November 22, 2021. Inclusion was restricted to fetuses or children with CHD requiring prenatal counseling by a pediatric cardiologist at UZL, regardless of ethnic background, type of CHD on prenatal ultrasound, course of the pregnancy, neonatal outcome, and regardless of the eventual cardiac diagnosis made postnatally or post-mortem. Fetuses appearing to have a normal heart on first trimester ultrasound and diagnosed with fetal aneuploidy (trisomy 21, 18 or 13, or monosomy X) by non-invasive prenatal screening (NIPS) were excluded. Additional exclusion criteria were: (1) fetuses with prenatal diagnosis of arrhythmia, cardiomyopathy, left-sided superior caval vein or cardiac tumors in the absence of CHD, (2) children with postnatal diagnosis of CHD, (3) fetuses referred to UZL for a second opinion after CHD diagnosis in a different university hospital, (4) fetuses with CHD for whom no prenatal advice by a pediatric cardiologist was sought either because of a low risk CHD (not requiring neonatal intervention), or because of a suspected poor prognosis due to severe ECA (for which termination of pregnancy (TOP) was requested regardless of the cardiac prognosis).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData collection\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMedical information, demographic data and results from diagnostic genetic testing were retrieved from fetal, pediatric and maternal medical files, and were pseudonymized. Familial history of CHD (up to 3rd degree relatives) and/or familial occurrence of known pathogenic CNVs or SNVs for congenital or developmental disorders was recorded. Pregnancy information included: maternal age at the start of pregnancy, gravidity, spontaneous pregnancy versus assisted reproduction, singleton versus multiple pregnancy, and postmenstrual age (PMA) at the time of fetal CHD diagnosis. Pre- and postnatal CHD types were recorded based on the recordings by the pediatric cardiologist. ECA diagnosed either prenatally, at birth or at post-mortem investigation were documented. ECA included additional congenital anomalies, intrauterine growth restriction (IUGR), micro/macrocephaly, increased nuchal translucency and congenital anomalies with little or no functional impact (e.g. facial dysmorphic features, hyperechogenic bowel, single umbilical artery\u0026hellip;). Acquired anomalies (e.g. ischemic or infectious brain damage, post-surgical diaphragm paralysis, feeding difficulties\u0026hellip;) were not considered as ECA. Primary pregnancy outcomes were (1) termination of pregnancy, (2) intrauterine fetal demise, (3) live birth. Postnatal outcome was documented as (1) 1-year survival, (2) early postnatal demise (\u0026lt;1 month) (3) demise during infancy (\u0026gt;1 month \u0026lt;1 year).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCHD categories and CHD severity scores\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCHD types were grouped together in CHD categories based on shared morphology or embryological mechanisms in accordance with the classification that was used by Gowda \u003cem\u003eet al.\u0026nbsp;\u003c/em\u003e\u003csup\u003e24\u003c/sup\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e(\u003cstrong\u003eTable 1\u003c/strong\u003e). Only one CHD category was ascribed to each fetus. If several CHD types were diagnosed, CHD classification was based on the most important prognostic and anatomical cardiac defect (e.g. isolated pulmonary valve atresia (PA), tetralogy of Fallot with PA and univentricular heart with PA were classified respectively as a right sided heart defect, conotruncal heart defect and univentricular heart).\u003c/p\u003e\n\u003cp\u003eIn addition, a severity score was assigned to each fetus based on the cardiac phenotype or the co-occurrence of additional major congenital anomalies and/or chromosomal aneuploidy. A 4-class scoring system (A, B, C or D) was applied as described by Gowda \u003cem\u003eet al.\u0026nbsp;\u003c/em\u003e\u003csup\u003e24\u003c/sup\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e(\u003cstrong\u003eSupplementary Table 1\u003c/strong\u003e). In summary, severity score A was assigned to CHD associated with severe potentially lethal ECA (e.g. congenital diaphragmatic hernia or hydrops fetalis), with aneuploidy or with genetic disorders associated with severe intellectual impairment (extremely high risk). Score B corresponds to isolated CHD requiring multiple surgeries and associated with high mortality after surgery (high risk). Score C (moderate risk) and score D (low risk) relate to isolated CHD with respectively variable and good prognosis after surgery. For severity scores A and B, the option of TOP was considered whenever legally permissible. For scores C and D continued monitoring of pregnancy with postnatal surgery was emphasized if applicable. Prenatal genetic work-up by CMA was recommended for fetuses with scores A or B, and CMA was offered, either prenatally or postnatally, for all other fetuses \u003csup\u003e25\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIsolated versus non-isolated CHD\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFetuses were classified as having non-isolated CHD when associated with at least one of the following prenatal ultrasound findings: (1) additional major congenital anomaly, (2) microcephaly and/or IUGR (\u0026lt;-2 SD), (3) facial dysmorphic features, (4) increased nuchal translucency (\u0026gt;3.5 mm at 12 weeks of gestation), cystic hygroma or hydrops fetalis, (5) isomerism/situs anomalies. If prenatal phenotyping was restricted to the cardiac phenotype, fetuses were considered to have CHD with undetermined extracardiac status.\u003c/p\u003e\n\u003cp\u003ePostnatal classification of non-isolated CHD was defined as CHD in association with at least one of the following criteria: (1) additional major congenital anomaly, (2) microcephaly and/or abnormal growth (\u0026lt;-2.5 SD or \u0026gt;+2.5 SD) taking gestational age at birth into consideration, (3) facial dysmorphic features (defined as the presence of at least 3 minor facial anomalies), (4) severe unexplained hypotonia or motor delay, (5) pathogenic or likely pathogenic CNVs or SNVs associated with developmental disorders. If postnatal development or growth could not be assessed due to intrauterine demise, termination of pregnancy or postnatal loss of follow-up, patients were considered to have CHD with undetermined extracardiac status.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGenetic data\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe retrieval of genetic data was restricted to documented pathogenic or likely pathogenic CNV or SNV (in accordance to the ACMG guidelines for CNV or SNV classification) \u003csup\u003e26,27\u003c/sup\u003e which were identified by prenatal or postnatal CMA or sequencing. Prenatal CMA by OGT 60k array, postnatal CMA by OGT 180k array and NGS by clinical exome sequencing were performed as described \u003csup\u003e28\u0026ndash;30\u003c/sup\u003e. NIPS was done as described \u003csup\u003e31\u003c/sup\u003e. Raw genetic data were not re-analyzed nor were newly generated for this retrospective chart review.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical analyses\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOne sample t-test was used to compare mean values of continuous variables (e.g. maternal age, gestational age) and chi-square test (or Fisher exact test) to compare categorical variables (e.g. IVF versus spontaneous pregnancy, singleton versus twins) between the patient population and the Belgian reference population \u003csup\u003e32\u0026ndash;34\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eA logistic regression analysis was used to determine significant predictors for outcome. We took the possible influence of multiple variables on the pre- and postnatal outcome into account. This analysis was repeated for three different types of outcomes:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eTOP versus non-TOP in the entire prenatal CHD cohort.\u003c/li\u003e\n \u003cli\u003epostnatal survival versus postnatal death in the subgroup of live births with a prenatally diagnosed CHD.\u003c/li\u003e\n \u003cli\u003eMortality (including TOP, IUM and postnatal death) versus survival across the entire prenatal cohort.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eFetuses or live births with missing outcome data were excluded.\u003c/p\u003e\n\u003cp\u003eLogistic regression was used on the entire prenatal population (n=341) for the dependent variables \u0026lsquo;TOP\u0026rsquo; and \u0026lsquo;mortality\u0026rsquo;:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eTOP ~ prenatal genetic diagnosis + CHD category + severity score + prenatal extracardiac abnormalities.\u003c/li\u003e\n \u003cli\u003eMortality ~ prenatal genetic diagnosis + CHD category + severity score + prenatal extracardiac abnormalities.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eLogistic regression was used for the dependent variable \u0026lsquo;survival\u0026rsquo; on the population of live births (n=277):\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eSurvival ~ prenatal genetic diagnosis + CHD type + prematurity + severity score + prenatal extracardiac abnormalities.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eSignificance of the severity score was determined among the different CHD types: significance of severity scores A, B or C was determined in comparison to score D. The significance of the 8 different CHD categories was also determined among the different categories where each category was compared to the anomalous venous return category. Prematurity defined as birth \u0026lt;36 weeks PMA was compared to the cohort born \u0026ge;36 weeks PMA. P-values of \u0026lt;0.05 were judged as significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eFetal cohort\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFrom January 2018 until November 2021 prenatal advice by the pediatric cardiologist was sought for 384 fetuses with prenatally diagnosed CHD. After exclusion of 43 fetuses (25 referrals from other university hospitals for second opinion; 5 without prenatal CHD; 5 with isolated arrhythmia; 4 with isolated cardiomyopathy; 3 with cardiac tumors and 1 with isolated left VCS), maternal and fetal data from 341 fetuses with CHD were reviewed (\u003cstrong\u003esupplementary\u003c/strong\u003e \u003cstrong\u003efigure 1\u003c/strong\u003e). The average maternal age at the time of CHD diagnosis was 30.93 years (range 18-44), which is equal to the average maternal age of all pregnancies in Belgium in 2020 \u003csup\u003e32\u003c/sup\u003e (\u003cstrong\u003esupplementary figure 2\u003c/strong\u003e). The majority of pregnancies involved G1 (N=96) and G2 (N=98) pregnancies \u003cstrong\u003e(supplementary figure 3\u003c/strong\u003e). Twin pregnancies represented 7.62% of the fetal CHD cohort (26/341), including 10 DCDA, 14 MCDA and 2 MCMA twins (including one MCDA twin with CHD in both fetuses). At least 25 pregnancies (7.33%) were documented to have occurred after assisted reproduction by in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI). Familial history was positive for CHD (regardless the CHD type) in 40 out of 341 fetuses (11.73%), with respectively 4.99%, 2.34% and 4.4% having at least one first, second or third-degree relative with CHD. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePrenatal CHD diagnosis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe average postmenstrual age (PMA) at CHD diagnosis at our center was 25.29 weeks (Most diagnoses were made between PMA week 20-23, at week 30-31 or at week 36 (\u003cstrong\u003esupplementary figure 4\u003c/strong\u003e). CHD categories and CHD severity scores were assigned to each fetus \u003csup\u003e24\u003c/sup\u003e. Conotruncal heart defects (33.72%) and LVOTO (18.77%) were the most common CHD categories (\u003cstrong\u003eTable 1\u003c/strong\u003e). Severity scores A, B, C and D were assigned respectively to 7%, 40%, 34% and 19% of the fetuses (\u003cstrong\u003eTable 2\u003c/strong\u003e). \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eCHD categories (and common CHD types per category). Distribution of CHD categories within this study was compared to that of previously reported cohorts (4-7,27). Abbreviations: Art: arteriosus; AS: aortic stenosis; AVR: anomalous venous return; CoAo: aortic coarctation; CHD: congenital heart defect; DORV: double outlet right ventricle; d-TGA: dextro-transposition of great arteries; IAA: interrupted aortic arch; LVOTO: left ventricle outflow tract obstruction; PS: pulmonary valve stenosis; RAA: right aortic arch; TA: tricuspid atresia; TOF: tetralogy of Fallot; UVH: univentricular heart.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHD categories and types\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003enumber\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHureaux \u003cem\u003eet al.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQiao \u003cem\u003eet al.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003evan Nisselrooij \u003cem\u003eet al.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGowda \u003cem\u003eet al.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStallings \u003cem\u003eet al.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage literature\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003econotruncal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eToF, d-TGA, truncus art\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e33.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e19.77%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e32.85%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e39.54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e28.43%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLVOTO\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAS, CoAo, IAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e18.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e21%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e7.22%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e15.82%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e25.55%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e33.76%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e20.67%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUVH\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eHLHS\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e11.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e21%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e9.46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e5.84%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e18.28%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e13.65%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eseptal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eVSD, ASD, AVSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e10.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e48.34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e20.34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e32.85%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e29.38%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eright-sided\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePS, TA, DORV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e9.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e6.94%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e16.65%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e32.85%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e25.02%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e17.29%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003esitus anomaly\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eheterotaxy, left/right isomerism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e4.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e5.83%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e1.69%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e4.37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e3.96%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAVR\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTAPVR, PAPVR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e2.54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e8.03%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e6.64%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e5.74%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eother\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eRAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e9.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e6.67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e13.42%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e1.46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e8.39%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003etotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 2.\u003c/strong\u003e CHD severity scores (from score A to D) based on the scoring system reported by Gowda et al. (27) and available in \u003cstrong\u003esupplementary table 1\u003c/strong\u003e.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2673%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHD severity score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e\u003cstrong\u003escore A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e\u003cstrong\u003escore B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e\u003cstrong\u003escore C\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e\u003cstrong\u003escore D\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e\u003cstrong\u003etotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2673%;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e341\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2673%;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e19%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2673%;\"\u003e\n \u003cp\u003eGowda \u003cem\u003eet al.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e45.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e20.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e24%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3465%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNon-isolated CHD\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNon-isolated CHD was diagnosed prenatally in 86 out of 341 (25%) fetuses, of which 63% (54/86) were confirmed postnatally or post-TOP to have a syndromic entity, 16% (14/86) were considered to have isolated CHD at birth, 8% (7/86) were diagnosed with situs anomalies and 13% (11/86) could not be assessed due to insufficient phenotypic information after birth or post-TOP.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the cohort of 277 liveborn, 60 individuals complied with the criteria of having non-isolated CHD (22%, 60/277)) and 37 individuals could not be assigned to either class due to insufficient information regarding growth or development (13%; 37/277). Forty-three liveborns with non-isolated CHD (72%; 43/60) were diagnosed with ECA prenatally. The remainder (17/60; 28%) presented prenatally with apparently isolated CHD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNIPS results\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNIPS results were available for 154 pregnancies (45%), retrieving 7 abnormal results (trisomy 7 (2x), 18, 20, 21 (2x) and 22q11 deletion), 4 of which (T7 (2x), T20 and T21 (1x)) could not be confirmed by prenatal CMA on amniotic fluid due to false positive results or to confined placental mosaicism. The fetuses with confirmed T18, T21 and 22q11DS had a diagnosis of CHD on prenatal ultrasound prior to performing NIPS. NIPS was not performed or results were not available for the other 187 pregnancies.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCMA results\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAfter excluding fetuses with an abnormal NIPS, CMA results were available for 232 fetuses (68%, 232/341), either performed prenatally (N=126) or after birth/TOP (N=106). Pathogenic or likely pathogenic chromosomal variants were identified for 30 patients either prenatally (N=18; 18/126 (14%)) or postnatally (N=12; 12/106 (11%)) (\u003cstrong\u003etable 3; supplementary table 2\u003c/strong\u003e). The most common chromosomal disorders were 22q11.2 deletion syndrome (N=10) and trisomy 21 (N=4) (\u003cstrong\u003esupplementary table 3\u003c/strong\u003e)\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eFor 27 fetuses with normal prenatal CMA results, CMA was repeated postnatally by 180k OGT array, but did not yield additional pathogenic variants. In accordance with the Belgian guidelines for variant reporting of prenatal genetic testing\u0026nbsp;\u003csup\u003e28\u003c/sup\u003e,\u0026nbsp;CNVs of unknown significance (VUS) identified by prenatal CMA were not communicated. These regulations did not apply for postnatal CMA results, reporting back VUS for 21 liveborn children who only had postnatal CMA analysis (N=107) or who had both prenatal and postnatal CMA analysis (N=27) (15.5%; 21/134). None of these VUS were reclassified as pathogenic or likely pathogenic after parental segregation analysis and clinical assessment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe also compared CMA results between fetuses with and without prenatal diagnosis of ECA. Pre- or postnatal CMA results were available for 135 fetuses with prenatal apparently isolated CHD, for 68 fetuses with non-isolated CHD and for 29 fetuses with undetermined extracardiac status, and identified pathogenic CNVs in respectively 7.4% (10/135), 27.9% (19/68) and 3.4% (1/29) fetuses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 3.\u003c/strong\u003e Diagnostic yield by prenatal (PREN) or postnatal (POST) chromosomal microarray analysis (CMA) in fetuses with apparently isolated versus non-isolated CHD on prenatal ultrasound. Chromosomal pathogenic variants identified by NIPS were excluded.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"602\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eECA status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCMA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003etotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epositive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003enegative\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ediagnostic yield (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eisolated-CHD\u003c/p\u003e\n \u003cp\u003eN=206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePREN CMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePOST CMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.4%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003enon-isolated CHD\u003c/p\u003e\n \u003cp\u003eN= 86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePREN CMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePOST CMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.9%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eCHD of unknown ECA status\u003c/p\u003e\n \u003cp\u003eN=49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePREN CMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePOST CMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.4%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTotal CHD cohort\u003c/p\u003e\n \u003cp\u003eN=341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePREN CMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePOST CMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e232\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e202\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12.9%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNGS results\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNGS-based targeted gene panel testing or clinical exome sequencing (ES) was not systematically conducted, but was restricted to 16 individuals with diagnosis of non-isolated CHD and normal CMA results. Pathogenic or likely pathogenic SNVs were retrieved by prenatal NGS in 1 patient (\u003cem\u003eRIT1\u003c/em\u003e) and by postnatal (or post-TOP) NGS in 11 patients (\u003cem\u003eKMT2D\u0026nbsp;\u003c/em\u003e(2x)\u003cem\u003e, PTPN11, RAF1, SON, DYNC2H1, PBX1, FOXF1, SMARCA4, KAT6A, PAH\u003c/em\u003e). Variants of unknown significance, inherited from an unaffected parent, were reported in 2 patients (\u003cem\u003eFLT4, SMAD6\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOutcome\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePrenatal outcome was not documented for 16 out of 341 pregnancies. The pregnancy in the remaining 325 fetuses ended either in TOP, an intrauterine demise or a live birth in respectively 44 (13.5%), 4 (1.2%) and 277 (85.3%) pregnancies. Early (\u0026lt;1 month) and late (\u0026gt;1 month) postnatal demise were documented for respectively 33 (11.9%) and 15 (5.5%) liveborn children (N=277). Full-term and premature birth (\u0026lt;36 weeks PMA) was recorded for respectively 232 and 31 liveborn children. Extreme prematurity (\u0026le;28 weeks PMA) was documented in 7 children. PMA at birth was not available for 14 liveborn children. Prenatal and postnatal outcome according to CMA results, CHD category, CHD severity score and multiple pregnancies are summarized in \u003cstrong\u003eTable 4\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 4. Pregnancy outcomes in accordance to severity score, CHD category, genetic diagnosis and singleton versus multiple pregnancy. Abbreviations: \u0026nbsp;AVR: anomalous venous return; IUM: intra-uterine demise; LVOTO: left ventricle outflow tract obstruction; TOP: termination of pregnancy; UVH: univentricular heart.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"973\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003enumbers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIUM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eunknown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003elive birth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003emortality\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u0026lt; 1 month\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003emortality\u003cbr\u003e\u0026nbsp;1-12 months\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003esurvival\u003cbr\u003e\u0026nbsp;to 12 months\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epregnancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003esingleton\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e43 (13.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e4 (1.27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e15 (4.76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e253 (80.32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e29 (9.21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e14 (4.44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e210 (66.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003emultiple\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1 (3.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1 (3.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e24 (92.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e4 (15.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1 (3.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e19 (73.08%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003egenetic diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e12 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e32 (71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e8 (17.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e23 (51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e32 (10.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e4 (1.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e15 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e245 (82.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e25 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e14 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e206 (69.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eseverity score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e9 (37.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e2 (8.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e13 (54.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e3 (12.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e3 (12.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e7 (29.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e30 (22.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e4 (2.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e10 (7.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e92 (67.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e24 (17.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e9 (6.62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e59 (43.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e4 (3.45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e2 (1.72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e110 (94.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e6 (5.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e2 (1.72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e102 (87.93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1 (1.54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e2 (3.08%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e62 (95.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1 (1.54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e61 (93.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHD category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003econotruncal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e6 (5.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1 (0.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e3 (2.61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e105 (91.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e7 (6.09%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e5 (4.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e93 (80.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLVOTO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e5 (7.81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1 (1.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e3 (4.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e55 (85.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e7 (10.94%%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e3 (4.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e45 (70.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eUVH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e18 (46.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e3 (7.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e18 (46.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e10 (25.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e3 (7.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e5 (12.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eSeptal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e6 (16.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e2 (5.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e28 (77.78%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e2 (5.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e26 (72.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eRight-sided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e5 (16.13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1 (3.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e2 (6.45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e23 (74.19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e4 (12.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e19 (61.29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eSitus anomaly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e2 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1 (6.25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e3 (18.75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e10 (62.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e4 (25.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e6 (37.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eAVR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e9 (100.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e3 (33.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e6 (66.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eother\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e2 (6.45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e29 (93.55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e29 (93.55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e341\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e44 (12.9%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4 (1.17%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16 (4.69%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e277 (81.23%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e33 (9.68%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15 (4.40%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e229 (67.16%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eMarkers for outcome\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLogistic regression was performed to find variables predisposing to \u0026lsquo;TOP\u0026rsquo;, to overall \u0026lsquo;mortality\u0026rsquo; (fetal death, TOP or postnatal demise (\u0026lt;1 year)) and to postnatal \u0026lsquo;survival\u0026rsquo; beyond the age of 1 year.\u0026nbsp;\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003e\u003cu\u003eLogistic regression analysis with outcome TOP\u003c/u\u003e determined that prenatal genetic diagnosis (p\u0026lt;0.001), prenatal extracardiac symptoms (p=0.045), severity score A (p=0.021) and severity score B (p=0.036) were significant contributing factors in the decision for TOP. Significance of the severity scores A, B and C was determined versus severity score D. Scores A and B were significantly more associated with TOP than score D. There was no significant difference between scores C and D. When using the CHD category \u0026lsquo;anomalous venous return\u0026rsquo; as a reference, none of the 8 CHD categories had sufficient power in this model to determine significant association with TOP. No significant results were obtained if other CHD categories were used as a reference.\u003cu\u003e\u0026nbsp;\u003c/u\u003e\u003c/li\u003e\n \u003cli\u003e\u003cu\u003eLogistic regression analysis for postnatal survival\u003c/u\u003e determined that prenatal extracardiac symptoms (p=0.002), prematurity of \u0026lt;36 weeks PMA (p=0.046) and severity score A (p=0.009 and B (p=0.004) had a significant negative impact on survival of a life birth with a complex CHD. When using univentricular heart as a reference for each other CHD category, we determined that there is a lower chance of postnatal survival in live births with a univentricular heart compared to patients with conotruncal abnormalities (p=0.009) or right sided cardiac abnormalities (p=0.02)\u003c/li\u003e\n \u003cli\u003e\u003cu\u003eLogistic regression analysis for total mortality\u003c/u\u003e determined significance for prenatal extracardiac symptoms (p\u0026lt;0.001) and severity score A (p\u0026lt;0.001), B (p\u0026lt;0.001) and C (p=0.046) in the full cohort (n=341). These factors significantly increase the chances of mortality. Furthermore, the CHD categories conotruncal abnormalities (p=0.003) and LVOTO (p=0.041) had a significantly lower chance of mortality if we normalized versus the univentricular heart category.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Discussion","content":"\u003cp\u003eEarly and accurate prenatal diagnosis of CHD is crucial to optimize perinatal care to reduce CHD-related mortality and to improve quality of survival. However, risk stratification after prenatal diagnosis of CHD remains challenging\u0026nbsp;\u003csup\u003e35\u003c/sup\u003e. Heart anatomy and coexisting congestive heart failure, reflected by ultrasound markers such as cardiomegaly, hydrops, abnormal myocardial function or abnormal venous Doppler, play the most important role in fetal and postnatal survival, underlying the importance of longitudinal prenatal echocardiographic examination for individualized outcome prediction of fetuses with CHD\u0026nbsp;\u003csup\u003e36,37\u003c/sup\u003e.\u003cem\u003e\u0026nbsp;\u003c/em\u003eIn this single-center retrospective chart review of 341 fetuses with CHD, we showed that in addition to high CHD severity scores (A or B) other factors such as prenatal diagnosis of pathogenic CNVs and prenatal co-occurrence of extracardiac anomalies were significantly associated with a decision to terminate pregnancy as well. This is in line with the study of Qiu \u003cem\u003eet al.\u003c/em\u003e showing that more complex CHD and presence of ECA were inversely correlated with continuation of the pregnancy\u0026nbsp;\u003csup\u003e36\u003c/sup\u003e.\u0026nbsp;In addition, prenatal diagnosis of ECA and high CHD severity score, as well as prematurity \u0026lt;36 weeks PMA, were negatively correlated with postnatal survival beyond the age of 1 year. These results showed that prenatal cardiac and extracardiac phenotyping, complemented with prenatal genotyping, aid to provide adequate counseling to parents of fetuses with CHD with respect to postnatal survival rates. In this cohort of prenatally diagnosed complex CHD, the pregnancy was terminated in 13% and was complicated by fetal death in 1%. Pregnancy outcome was not documented in 4.5%. The overall postnatal mortality in our cohort was 17% (\u0026lt;4wk in 33/277 and \u0026gt;4wk in 15/277 liveborn children), which\u0026nbsp;is similar to previous studies\u0026nbsp;\u003csup\u003e24\u003c/sup\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e(\u003cstrong\u003etable 4\u003c/strong\u003e).\u0026nbsp;Survival was significantly lower in fetuses with UVH compared to conotruncal CHD and right sided-CHD. Larger sample sizes per CHD category are required to attain sufficient statistical power to accurately associate CHD categories to TOP decisions or to short- or long-term survival. Ultrasound markers for outcome prediction, as described by\u0026nbsp;Wieczorek \u003cem\u003eet al.\u0026nbsp;\u003c/em\u003e\u003csup\u003e37\u003c/sup\u003e and Qiu \u003cem\u003eet al.\u003c/em\u003e \u003csup\u003e36\u003c/sup\u003e,\u0026nbsp;were not available and therefore the use of ultrasound parameters, such as the cardiovascular profile score, could not be applied.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe distribution of CHD categories in this study aligns well with the average distribution based on previously reported prenatal CHD cohorts\u0026nbsp;\u003csup\u003e4\u0026ndash;7\u003c/sup\u003e. (\u003cstrong\u003eTable 1\u003c/strong\u003e). Differences between individual reports is likely due to differences in classification of CHD categories. In this study, each fetus was attributed to only one CHD category based on the CHD type that was anatomically or prognostically most prominent, explaining the relatively low prevalence of septal defects in our cohort. Prenatal counseling by pediatric cardiologists in our center is less frequently requested in fetuses with CHD of lower complexity (CHD severity score D) or in fetuses with chromosomal aneuploidy en/or life-threatening ECA (CHD severity score A). Therefore, a shift towards CHD severity score C was observed, in comparison to the CHD severity distribution reported by Gowda \u003cem\u003eet al.\u0026nbsp;\u003c/em\u003e\u003csup\u003e24\u003c/sup\u003e.\u003cem\u003e\u0026nbsp;\u003c/em\u003e(\u003cstrong\u003eTable 2\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs expected, TOP and postnatal mortality were significantly higher among fetuses with severity scores A and B compared to severity score D, while scores A, B and C are associated with higher overall mortality. We used the same parameters to score CHD severity as those introduced by Gowda \u003cem\u003eet al.\u0026nbsp;\u003c/em\u003e\u003csup\u003e24\u003c/sup\u003e.\u003cem\u003e\u0026nbsp;\u003c/em\u003eAlthough\u0026nbsp;the distribution of CHD severity scores was comparable between both cohorts (except for score C which was more represented in our study population), we observed in our CHD cohort a higher survival rate beyond 6 months: overall (67% versus 40%) and across the subgroups with scores A (29% versus 7%), B (44% versus 9.7%) and C (88% versus 55.6%). These differences were related to a lower fetal death rate (1% versus 11.7%) and lower neonatal mortality (9.6% versus 24.1%), which may be due to differences in TOP policy as a more restrictive TOP policy may add to higher mortality rates. Large sample size follow-up studies are required to confirm these findings.\u003c/p\u003e\n\u003cp\u003eA significantly higher rate of multiple pregnancies (7.62%;p\u0026lt;0.001) and of IVF/ICSI pregnancies (7.33%;p\u0026lt;0.001) was observed in this CHD cohort compared to the general population (twinning rate of 1.6% and IVF/ICSI rate of 5.1% according to the 2019 report of the Flemish Center for Study of Perinatal Epidemiology). Compared to singletons, multiple pregnancies are known to be at increased risk of CHD, particularly among monochorionic twins due to altered intra-uterine hemodynamics\u0026nbsp;\u003csup\u003e38\u0026ndash;41\u003c/sup\u003e.\u0026nbsp;In addition, we confirm the findings of Giorgione \u003cem\u003eet al.\u003c/em\u003e showing that assisted human reproduction by IVF or ICSI was associated with a higher CHD incidence as well (odds ratio 1,45)\u0026nbsp;\u003csup\u003e40,42\u003c/sup\u003e. CHD (of any type) in first-degree relatives was documented in 4.99% fetuses with CHD, which is similar to previous reports on familial CHD\u0026nbsp;\u003csup\u003e43\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eA pathogenic variant was identified by pre- or postnatal CMA in 27.9% of fetuses presenting prenatally with non-isolated CHD. Nine additional fetuses from this subgroup were diagnosed by NGS with a pathogenic SNV. The diagnostic yield of chromosomal testing in fetuses with apparently isolated CHD (N=206) or with CHD of undetermined extracardiac status (N=49) was significantly lower (5.8%; 1 by NIPS, 5 by prenatal CMA, 6 by postnatal or post-TOP CMA, 3 by WES). All these patients presented with ECA at birth or post-mortem, despite having an isolated CHD on prenatal ultrasound (\u003cstrong\u003esupplementary table 3\u003c/strong\u003e). Our results are in line with those by van Nisselrooij \u003cem\u003eet al.\u0026nbsp;\u003c/em\u003ereporting chromosomal or genetic pathogenic variants in 15%: in 28.7% of fetuses with non-isolated CHD and in 11% of fetuses with apparently isolated CHD on prenatal ultrasound\u0026nbsp;\u003csup\u003e7\u003c/sup\u003e. The most common chromosomal and genetic syndromes in fetuses with CHD identified by us and others\u0026nbsp;\u003csup\u003e7\u003c/sup\u003e were 22q11 deletion syndrome and Noonan syndrome. We also confirmed that CHD categories \u0026lsquo;septal defects\u0026rsquo; (AVSD and VSD) and \u0026lsquo;LVOTO\u0026rsquo; (interrupted aortic arch and CoAo) were associated with the highest yield of genetic testing, respectively in 19.4% and 20.3% (\u003cstrong\u003esupplementary Table 2\u003c/strong\u003e). Results from NIPS were available for 45% of fetuses (154/341), which is lower compared to the uptake of NIPS in the general population of pregnant women in Belgium (78.7%), where NIPS is available as a publicly funded nationwide first-tier screening as of July 2017\u0026nbsp;\u003csup\u003e44\u003c/sup\u003e. Prenatal invasive testing is preferred over NIPS when first trimester ultrasound is abnormal, which explains the lower uptake in the CHD cohort. Since fetal aneuploidy (T21, T18 or T13) weighs heavily on the decision to terminate pregnancy regardless of the presence of CHD\u0026nbsp;\u003csup\u003e45\u003c/sup\u003e potentially causing a bias with respect to outcome prediction in this study, we excluded fetuses with abnormal non-invasive aneuploidy screening prior to the diagnosis of CHD on prenatal ultrasound. NGS was performed in only a small subset of patients, either presenting with prenatal features of a rasopathy as described\u0026nbsp;\u003csup\u003e46\u003c/sup\u003e, explaining the high incidence of Noonan syndrome in our cohort, or presenting postnatally or post-mortem with unexplained non-isolated CHD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe outcome measures of this retrospective study were restricted to pregnancy continuation, overall mortality and postnatal survival. Long-term follow-up data on growth, development, behavior or survival into infancy were not available. \u0026lsquo;CHD category\u0026rsquo;, \u0026lsquo;extracardiac anomalies\u0026rsquo; and \u0026lsquo;CHD severity score\u0026rsquo; were included in the logistic regression outcome prediction model. However, as CHD severity scores were based on CHD type and on the presence of ECA, these variables are not independent, potentially impacting the results. As previously mentioned, CMA analysis was offered, either prenatally or postnatally, for all fetuses, but CMA results were available for only 68%, failing us to provide insight into chromosomal anomalies in the full cohort. NGS was not offered systematically, and was restricted to fetuses or live born children with non-isolated CHD and normal CMA results. This NGS policy is a limitation of this study. As NGS technology becomes broadly available and sequencing costs are dropping, ultrarapid trio exome or genome sequencing emerges as the standard-of-care prenatal genetic test when non-isolated CHD is diagnosed, and could be considered in fetuses with apparently isolated complex CHD despite the low diagnostic yield. However, when moving from postnatal to prenatal genetic testing, some challenges need to be taken into consideration, including technology availability, access to health care, health insurance issues and sociocultural differences. Moreover, short turn-around-times should be guaranteed and adequate pre-test counseling is required, dealing with diagnostic yield, risks of invasive prenatal procedures and the reporting of incidental findings. Expectations and preferences of the parents should be prioritized when offering prenatal genomic testing.\u003c/p\u003e\n\u003cp\u003eIn conclusion, we showed that cardiac and extracardiac phenotyping by prenatal ultrasound and elaborate prenatal genetic testing are crucial to provide adequate counseling to parents of fetuses with CHD with respect to postnatal survival rates.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset generated and analysed during this retrospective study is not publicly available due to the sensitive nature of the data. However, inquiries regarding the dataset and its use can be directed to the corresponding author upon reasonable request.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the patients and their families for their participation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.B. and M.V. conceptualized the study, J.B., K.D., K.V.d.B, B.C., L.D.C. and M.G. retrospectively included patients. M.V. reviewed medical files and collected relevant data. J.B., M.V. and L.H. analyzed the data and wrote the main text of the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.B. is funded by a clinical investigator fellowship by FWO-Flanders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003evan der Linde, D. \u003cem\u003eet al.\u003c/em\u003e Birth Prevalence of Congenital Heart Disease Worldwide. \u003cem\u003eJournal of the American College of Cardiology\u003c/em\u003e \u003cstrong\u003e58\u003c/strong\u003e, 2241\u0026ndash;2247 (2011).\u003c/li\u003e\n\u003cli\u003eWu, W., He, J. \u0026amp; Shao, X. Incidence and mortality trend of congenital heart disease at the global, regional, and national level, 1990-2017. \u003cem\u003eMedicine\u003c/em\u003e \u003cstrong\u003e99\u003c/strong\u003e, (2020).\u003c/li\u003e\n\u003cli\u003eBest, K. E. \u0026amp; Rankin, J. Long‐Term Survival of Individuals Born With Congenital Heart Disease: A Systematic Review and Meta‐Analysis. \u003cem\u003eJournal of the American Heart Association: Cardiovascular and Cerebrovascular Disease\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, (2016).\u003c/li\u003e\n\u003cli\u003eStallings, E. 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E. \u003cem\u003eet al.\u003c/em\u003e Prenatal ultrasound findings of rasopathies in a cohort of 424 fetuses: update on genetic testing in the NGS era. \u003cem\u003eJournal of Medical Genetics\u003c/em\u003e \u003cstrong\u003e56\u003c/strong\u003e, 654\u0026ndash;661 (2019).\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"congenital heart defects, chromosomal, prenatal, outcome","lastPublishedDoi":"10.21203/rs.3.rs-5038076/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5038076/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Congenital structural heart disease (CHD) is the leading cause of infant death from birth defects. Postnatal survival primarily depends on the type and severity of the defect. In addition, worse cardiac prognosis is observed when extra-cardiac anomalies (ECA) are associated. This retrospective chart review was aimed at finding markers for short-term outcome prediction of prenatally-diagnosed complex CHD, focusing in particular on the impact of CHD category, of CHD severity score and of prenatal or postnatal diagnosis of ECA or chromosomal anomalies on 4 primary outcomes: termination of pregnancy (TOP), intrauterine fetal demise, neonatal mortality and 1-year-survival rate. We reviewed medical files from 381 fetuses, presenting at our center between 2018 and 2021 with CHD for which prenatal advice by a pediatric cardiologist was sought. 341 fetuses met the inclusion criteria for the study. Twin pregnancies (7.62%; OR 4.76 (p\u003c0.001)) and pregnancies resulting from assisted reproductive technology (7.33%; OR 2.44 (p\u003c0.001)) were more prevalent compared to the general population. CHD categories and CHD severity scores, ranging from A (extremely high risk) to D (low risk), were assigned to each fetus. Prenatal or postnatal chromosomal microarray results were available for 232 fetuses (68%) and were abnormal in 30 (12.9%). Logistic regression analysis was used to determine significant predictors for the 4 primary outcomes. TOP was carried out significantly more with: prenatal genetic diagnosis (p\u003c0.001), prenatal extracardiac symptoms (p\u003c0.001), severity score A (p=0.045) and B (p=0.036). Survival was significantly lower with: prenatal extracardiac symptoms (p=0.002), prematurity (p=0.046), severity scores A (p=0.009) and B (p=0.004), and with univentricular heart. CHD severity score, chromosomal anomalies and ECA are determining factors for continuation of the pregnancy, for survival and for overall mortality, underscoring the importance of prenatal ultrasound and genotyping for prognostication of fetuses with CHD. \n","manuscriptTitle":"Chromosomal analysis and short-term outcome of prenatally diagnosed complex congenital heart disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-10 07:03:26","doi":"10.21203/rs.3.rs-5038076/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-11T13:28:02+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-08T18:53:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"330423195233689811516352831298414614845","date":"2024-10-06T00:47:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-04T12:09:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"19625253285881754297602877911171980145","date":"2024-09-17T06:08:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-11T13:54:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-11T13:53:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-09-09T11:02:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-06T11:26:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-09-05T12:12:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4244e424-388a-4e48-94b4-f84ecd6dec88","owner":[],"postedDate":"October 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":38580992,"name":"Health sciences/Cardiology/Cardiovascular biology/Cardiovascular genetics"},{"id":38580993,"name":"Biological sciences/Genetics/Cytogenetics"},{"id":38580994,"name":"Health sciences/Health care/Diagnosis/Genetic testing"},{"id":38580995,"name":"Health sciences/Health care/Health services/Genetic services/Genetic counselling"},{"id":38580996,"name":"Health sciences/Diseases/Cardiovascular diseases/Congenital heart defects"}],"tags":[],"updatedAt":"2025-02-03T16:01:20+00:00","versionOfRecord":{"articleIdentity":"rs-5038076","link":"https://doi.org/10.1038/s41598-025-88570-8","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-01-31 15:57:25","publishedOnDateReadable":"January 31st, 2025"},"versionCreatedAt":"2024-10-10 07:03:26","video":"","vorDoi":"10.1038/s41598-025-88570-8","vorDoiUrl":"https://doi.org/10.1038/s41598-025-88570-8","workflowStages":[]},"version":"v1","identity":"rs-5038076","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5038076","identity":"rs-5038076","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}