Abstract
Background
Infants with critical congenital heart disease (CCHD) are more likely to be small for gestational age (GA). It is unclear how this affects mortality. The authors investigated the effect of birth weight Z score on 1‐year mortality separately in preterm (GA <37 weeks), early‐term (GA 37–38 weeks), and full‐term (GA 39–42 weeks) infants with CCHD.
Methods and Results
Live‐born infants with CCHD and GA 22 to 42 weeks born in California 2007–2012 were included in the analysis. The primary predictor was Z score for birth weight and the primary outcome was 1‐year mortality. Multivariable logistic regression was used. Results are presented as adjusted odds ratios and 95% confidence intervals (CIs). The authors identified 6903 infants with CCHD. For preterm and full‐term infants, only a Z score for birth weight <−2 was associated with increased mortality compared with the reference group (Z score 0–0.5, adjusted odds ratio, 2.15 [95% CI, 1.1–4.21] and adjusted odds ratio, 3.93 [95% CI, 2.32–6.68], respectively). In contrast, in early‐term infants, the adjusted odds ratios for Z scores <−2, −2 to −1, and −1 to −0.5 were 3.42 (95% CI, 1.93–6.04), 1.78 (95% CI, 1.12–2.83), and 2.03 (95% CI, 1.27–3.23), respectively, versus the reference group.
Conclusions
GA seems to modify the effect of birth weight Z score on mortality in infants with CCHD. In preterm and full‐term infants, only the most severe small‐for‐GA infants (Z score <−2) were at increased risk for mortality, while, in early‐term infants, the risk extended to mild to moderate small‐for‐GA infants (Z score <−0.5). This information helps to identify high‐risk infants and is useful for surgical planning.
Keywords: birth weight Z score, congenital cardiac defect, congenital heart disease, fetal growth, mortality
Subject Categories: Pediatrics, Mortality/Survival
Clinical Perspective
What Is New?
The effect of small for gestational age (GA) on 1‐year mortality seems to be modified by GA in infants with critical congenital heart disease.
In preterm and full‐term infants, only most severe small‐for‐GA infants (Z score <−2) were at increased risk for mortality, while, in early‐term infants, the risk extended to mild to moderate small‐for‐GA infants (Z score <−0.5).
What Are Clinical Implications?
This study identifies early‐term infants (GA 37–38 weeks) as a group particularly sensitive to the effects of low birth weight on survival in infants with critical congenital heart disease.
In contrast, mild to moderate small‐for‐GA (−2> birth weight Z score >−0.5) preterm and term infants with critical congenital heart disease do not appear to be at increased risk for mortality and this may assist in the counseling of parents regarding possible surgical interventions.
Introduction
Congenital heart disease (CHD) is the most common category of birth defect, with an incidence rate between 0.3% and 0.8%.1, 2 Critical CHD (CCHD)—defined as requiring neonatal intervention—is reported to have an incidence rate of 0.17%.3 Despite advances in medical and surgical management of affected infants, mortality and morbidity remain relatively high.4, 5
Research has mainly focused on specific anatomical details, surgical techniques, and postnatal complications as factors affecting mortality and morbidity, while the impact of other infant characteristics remains less well understood.6 Two recent studies investigated the impact of gestational age (GA) at birth on postnatal outcomes in infants with CCHD.7, 8 Both studies found that the length of gestation independently affects mortality, postoperative complications, and neonatal morbidity after adjusting for severity of CHD, and that early‐term infants (GA 37–38 weeks) are at higher risk for poor outcomes compared with full‐term infants (GA ≥39 weeks).
Birth weight (BW) percentile (or the corresponding Z score), standardized for GA and infant sex, is also an important infant characteristic, representing fetal growth. It has been shown that infants with CHD are more likely to be born small for GA (SGA; defined as BW for GA and sex <10th percentile).9, 10 In infants without CHD, the negative effect of severe SGA (BW <5th percentile) on neonatal outcomes has been documented in preterm and term infants.11 To date, the few studies that have evaluated the effect of SGA on mortality in infants with CHD are either relatively small (n=136–308)12, 13, 14 or have examined BW Z score as a dichotomous variable (eg, SGA versus adequate for GA [AGA]). While these studies provide useful information, they potentially missed a more complex relationship between fetal growth and mortality in this patient population.15 None of these studies investigated the potentially differential effect of BW Z score on mortality within GA categories.
The aim of this analysis was to investigate the role of BW Z score on 1‐year mortality in preterm, early‐term, and full‐term infants with CCHD. We hypothesized that not only would severely SGA infants (<5%ile, Z score −1.96) with CCHD have a higher mortality but that this effect would extend to infants with higher BW Z scores. We further investigated whether the association is different in different GA groups. Additionally, we report survival estimate curves, which have greater utility for counseling and planning of medical treatment than odds or hazard ratios from statistical models.
Methods
The data, analytic methods, and study materials will not be made available to other researchers for purposes of reproducing the results or replicating the procedure. The data use agreement with the California Office of Statewide Health Planning and Development (OSHPD) prohibits distribution of any patient‐level data. Data can be requested from OSHPD (https://www.oshpd.ca.gov/HID/HIRC/index.html) by qualified researchers for a fee. All other analytic methods and study materials are available upon reasonable request from the corresponding author.
OSHPD maintains a birth cohort database containing 3 160 268 live births from the years 2007 to 2012. This database includes detailed information on infant characteristics derived from hospital discharge records (birth hospitalization and readmissions) and is linked to birth and death certificates, from birth to 1 year of age. The file provides diagnosis and procedure codes based on the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD‐9‐CM).16
This same database has been used by our group to investigate the effect of GA on mortality and severe neonatal morbidity in infants with CCHD.7
We included all live‐born infants with GA 22 to 42 completed weeks and excluded newborns with known chromosomal abnormalities or major structural birth defects other than CCHD. Structural birth defects were considered “major” if determined by clinical review to result in mortality or major morbidity and likely to be identified at birth or lead to hospitalization during the first year of life.17
Infants with CCHD were identified by ICD‐9‐CM diagnostic and procedure codes present in the birth, transfer, or readmission records. CCHD was defined as one or a combination of the following lesions: hypoplastic left heart syndrome, pulmonary atresia, tetralogy of Fallot, transposition of the great arteries, tricuspid atresia, truncus arteriosus, total anomalous venous return, coarctation of the aorta, double outlet right ventricle, Ebstein anomaly, and single ventricle.3, 18 Additionally, we included pulmonary and aortic stenosis requiring intervention during the first year of life.18 Two study collaborators (M.A.S. and A.M.G.) reviewed all cases according to a proposed framework based on morphogenetically similar developmental mechanisms3, 19 to ensure correct classifications of infants with multiple ICD‐9‐CM codes. Final diagnosis was reached by consensus. Infants with multiple CCHD codes consistent with heterotaxy were also classified as CCHD.
To adjust for complexity of CCHD, we used 6 severity groups modified from risk adjustment in congenital heart surgery (RACHS)20 as further detailed in Steurer et al.7 It was not possible to use RACHS in its original form, since some surgical details needed for classifications were not available in this database.
The outcome assessed was 1‐year mortality determined by death certificate. Our main predictor was Z score for BW calculated using data published by Talge et al,21 who derived Z scores for BW by GA and sex from US live‐birth files maintained by the National Center for Health Statistics (years 2009–2010) and corrected for implausible GA estimates. We used this reference because of the similarity of the population and time period to our study cohort. Infants with a Z score <−4 and >+4 were excluded from the analysis because of the likelihood of either implausible GA or BW (n=40). Given that the above‐mentioned data21 to calculate BW Z score were derived from singleton gestations only, we performed a sensitivity analysis excluding multiple gestation infants from our cohort.
We first divided the cohort into the 3 groups most widely used when assessing fetal growth: SGA (BW <10th percentile for GA and sex, corresponding to a Z score <−1.27), adequate for GA (AGA; BW 10–90th percentile for GA and sex, Z sore −1.27 to 1.27), and large for GA (LGA; BW >90th percentile for GA and sex, Z score >+1.27).
We then planned to evaluate BW z‐score as a continuous predictor variable separately in 3 different gestational age groups: preterm (<37 weeks), early‐term (37–38 weeks), and full‐term (39–42 weeks) infants. However, the lowest plots suggested departure from linearity between log odds of mortality and Z score for BW in all 3 groups (not shown). The relationship was best modeled using logistic regression with restricted cubic splines for Z score for BW with knots at −2, 0, and +2. To graphically represent the logistic models involving cubic splines, we derived curves for predicted probability of death separately in each group. Z score–specific margins were calculated for different GA categories while adjusting for sex, multiple gestation, and complexity of CHD (all confounders were kept at their mean values). To numerically quantify the effect and the nonlinear relationship, Z score for BW was used as a categorical variable with 8 categories (<−2, ≥−2 to −1, ≥−1 to −0.5, ≥−0.5 to 0, ≥0–0.5, ≥0.5–1, ≥1–2, and >2). Multivariable models were adjusted for complexity of CCHD (by modified RACHS), GA, sex, and multiple gestation. The results are presented as odds ratios (ORs) and 95% confidence intervals (CIs).
To describe baseline characteristics, t test was used to compare means and chi‐square was used to compare proportions. A P<0.05 was considered significant.
All analyses were performed using Stata version 14.2 (version 14, StataCorp LP). The study was approved by the Committee for the Protection of Human Subjects within the California Health and Human Services Agency. The informed consent requirement was waived.
Results
We identified 6903 live‐born infants with CCHD born between 22 and 42 weeks of gestation without chromosomal anomalies, corresponding to an incidence of 0.23% (6903/2 968 566 live births). Overall, mean BW in infants with CCHD was 3090 g (SD 733.8 g) and 3306.7 g (SD 555.3 g) in infants without CCHD, respectively (t test, P<0.001). A total of 16.2% of infants with CCHD were SGA (n=1120), while 8.9% of infants without CCHD were classified as SGA (n=266 133, chi‐square test; P<0.001). There was no difference in the percentage of infants born LGA (CCHD: 9.6%, n=664; no CCHD: 9.8%, n=293 001 [chi‐square test, P=0.57]). Overall, 18.1% (1246/6903) of infants with CCHD were born prematurely (<37 weeks’ gestation) compared with 8.4% of infants without CCHD (251 029/2 983 022; chi‐square test, P<0.001).
Table 1 shows the baseline characteristics of infants with CCHD born SGA, AGA, and LGA. When compared with AGA infants, SGA infants were more likely to be women (P=0.016) and less likely to be singleton (P<0.001), while LGA infants were more likely to be singleton (P<0.001). SGA and LGA infants were more likely to be born to a mother with preeclampsia (SGA: P<0.001 and LGA: P=0.025), and LGA infants were also more likely to be born to a mother with diabetes mellitus (P<0.001) (Table 1).
Table 1.
Characteristics of Infants With Critical Congenital Heart Disease by BW Category for Gestational Age
| AGA (Reference) | SGA | P Value | LGA | P Value | |
|---|---|---|---|---|---|
| Sample | 5119 | 1111 | 633 | ||
| BW | |||||
| Mean BW (SD), g | 3139.4 (598.5) | 2339.2 (519.0) | 3987.4 (657.2) | ||
| Mode of delivery | <0.0001 | <0.0001 | |||
| Cesarean | 2023 (39.5) | 547 (49.2) | 344 (54.3) | ||
| Vaginal | 3096 (60.5) | 564 (50.8) | 289 (44.7) | ||
| Race | <0.0001 | 0.0010 | |||
| White not Hispanic | 1460 (28.5) | 261 (23.5) | 174 (27.5) | ||
| Hispanic | 2383 (46.6) | 491 (44.2) | 334 (52.8) | ||
| Black | 235 (4.6) | 86 (7.7) | 32 (5.1) | ||
| Asian | 568 (11.1) | 169 (15.2) | 39 (6.2) | ||
| Other | 473 (9.2) | 104 (9.2) | 54 (8.5) | ||
| Sex | 0.0168 | 0.4497 | |||
| Female | 2063 (40.3) | 491 (44.2) | 265 (41.9) | ||
| Male | 3056 (59.7) | 620 (55.8) | 368 (58.1) | ||
| Gestation | <0.0001 | <0.0001 | |||
| Singleton | 4893 (95.6) | 986 (88.8) | 630 (99.5) | ||
| Multiple | 226 (4.4) | 125 (11.3) | 3 (0.5) | ||
| Maternal education | 0.2319 | 0.1384 | |||
| <12 y | 1215 (23.7) | 251 (22.6) | 171 (27.0) | ||
| 12 y | 1303 (25.5) | 301 (27.1) | 170 (26.9) | ||
| >12 y | 2308 (45.1) | 482 (43.4) | 261 (41.2) | ||
| Missing | 293 (5.7) | 77 (6.9) | 31 (4.9) | ||
| Payment for delivery | 0.7391 | 0.0419 | |||
| Private insurance | 2361 (46.1) | 532 (47.9) | 275 (43.4) | ||
| Public insurance | 2513 (49.1) | 531 (47.8) | 337 (53.2) | ||
| Self‐pay | 68 (1.3) | 16 (1.4) | 11 (1.7) | ||
| Other | 168 (3.3) | 30 (2.7) | 10 (1.5) | ||
| Missing | 9 (0.2) | 2 (0.2) | 0 (0.0) | ||
| Parity | 0.0001 | <0.0001 | |||
| Nulliparous | 1950 (38.1) | 500 (45.0) | 168 (26.5) | ||
| Multiparous | 3165 (61.8) | 610 (54.9) | 464 (73.3) | ||
| Missing | 4 (0.1) | 1 (0.1) | 1 (0.2) | ||
| Oligohydramnios | <0.0001 | 0.0158 | |||
| No | 4947 (96.6) | 1011 (91.0) | 623 (98.4) | ||
| Yes | 172 (3.4) | 100 (9.0) | 10 (1.6) | ||
| PROM | 0.3010 | 0.7490 | |||
| No | 4737 (92.5) | 1018 (91.6) | 588 (92.9) | ||
| Yes | 382 (7.5) | 93 (8.4) | 45 (7.1) | ||
| Chorioamnionitis | 0.2341 | 0.9064 | |||
| No | 5002 (97.7) | 1092 (98.3) | 619 (97.8) | ||
| Yes | 117 (2.3) | 19 (1.7) | 14 (2.2) | ||
| Maternal age, y | 0.1807 | 0.0029 | |||
| <18 | 140 (2.7) | 32 (2.9) | 8 (1.3) | ||
| 18–34 | 3979 (77.7) | 855 (77.0) | 475 (75.0) | ||
| >34 | 1000 (19.5) | 223 (20.1) | 150 (23.7) | ||
| Missing | 0 (0.0) | 1 (0.1) | 0 (0.0) | ||
| Maternal diabetes mellitus | 0.6181 | <0.0001 | |||
| None | 4422 (86.4) | 972 (87.5) | 437 (69.0) | ||
| Preexisting | 152 (3.0) | 30 (2.7) | 61 (9.6) | ||
| Gestational | 545 (10.7) | 109 (9.8) | 135 (21.3) | ||
| Maternal BMIa | <0.0001 | <0.0001 | |||
| Underweight | 231 (4.5) | 73 (6.6) | 8 (1.3) | ||
| Normal weight | 2194 (42.9) | 541 (48.7) | 182 (28.8) | ||
| Overweight | 1241 (24.2) | 225 (20.3) | 175 (27.7) | ||
| Obese | 1016 (19.9) | 179 (16.1) | 211 (33.3) | ||
| Missing | 437 (8.5) | 93 (8.4) | 57 (9.0) | ||
| Mental illness | 0.4323 | 0.6244 | |||
| No | 4867 (95.1) | 1050 (94.5) | 599 (94.6) | ||
| Yes | 252 (4.9) | 61 (5.5) | 34 (5.4) | ||
| Smoking during pregnancy | 0.1255 | 0.5942 | |||
| No | 4834 (94.4) | 1036 (93.3) | 601 (94.9) | ||
| Yes | 285 (5.6) | 75 (6.8) | 32 (5.1) | ||
| Illicit drug use | 0.2088 | 0.1611 | |||
| No | 5012 (97.9) | 1081 (97.3) | 625 (98.7) | ||
| Yes | 107 (2.1) | 30 (2.7) | 8 (1.3) | ||
| Hypertension | 0.1047 | 0.4981 | |||
| None | 4920 (96.1) | 1052 (94.8) | 607 (95.9) | ||
| Preexisting | 84 (1.6) | 27 (2.4) | 14 (2.2) | ||
| Gestational | 115 (2.3) | 31 (2.8) | 12 (1.9) | ||
| Preeclampsia | <0.0001 | 0.0890 | |||
| No | 4875 (95.2) | 996 (89.7) | 593 (93.7) | ||
| Yes | 244 (4.8) | 115 (10.4) | 40 (6.3) | ||
Values are expressed as number (percentage) unless otherwise indicated. Chi‐square test was used to compare variables. P<0.05 was considered statistically significant. AGA indicates adequate for gestational age; BW, birth weight; LGA, large for gestational age; PROM, premature rupture of membranes; SGA, small for gestational age.
Underweight: body mass index (BMI) <18.5 kg/m2; normal weight: BMI 18.5 to 24.9 kg/m2; overweight: BMI 25.0 to 29.9 kg/m2; and obese: BMI ≥30.0 kg/m2.
For infants with CCHD, Figure 1 shows the crude rates of mortality by GA group for AGA, SGA, and LGA infants. In preterm infants (GA <37 weeks), the OR for mortality was not significantly higher for SGA infants compared with AGA infants in each GA group (Table 2). In contrast, for infants born at 37, 38, 39, or 40 weeks GA, SGA had a significantly higher crude and adjusted OR for mortality when compared with AGA. LGA infants of any GA group did not have significantly higher crude or adjusted ORs than AGA infants (Table 2).
Figure 1.
Fetal growth and 1‐year mortality rates by gestational age in infants with critical congenital heart disease. AGA indicates adequate for gestational age; LGA, large for gestational age; SGA, small for gestational age.
Table 2.
Effects of Small and Large for Gestational Age on Mortality by Gestational Age in Infants With Critical Congenital Heart Disease
| Gestational Age | SGA vs AGA | LGA vs AGA | ||
|---|---|---|---|---|
| Crude OR | Adjusted ORa | Crude OR | Adjusted ORa | |
| <32 wk (n=280) | 1.18 (0.60–2.36) | 1.61 (0.77–3.36) | 1.60 (0.72–3.55) | 1.46 (0.61–3.52) |
| 32–33 wk (n=178) | 2.00 (0.83–4.83) | 2.29 (0.85–6.20) | 2.6 (0.98–6.94) | 2.26 (0.78–6.57) |
| 34 wk (n=161) | 0.81 (0.28–2.34) | 0.93 (0.29–3.0) | 0.62 (0.13–2.95) | 0.46 (0.09–2.41) |
| 35 wk (n=222) | 1.45 (0.67–3.14) | 1.82 (0.76–4.36) | 0.97 (0.26–3.59) | 0.58 (0.14–2.34) |
| 36 wk (n=385) | 1.27 (0.72–2.27) | 1.73 (0.91–3.29) | 0.41 (0.12–1.40) | 0.46 (0.13–1.65) |
| 37 wk (n=731) | 2.1 (1.32–3.21)b | 2.75 (1.69–4.48)b | 1.27 (0.62–2.62) | 1.92 (0.88–4.21) |
| 38 wk (n=1363) | 1.67 (1.11–2.53)b | 1.64 (1.05–2.57)b | 0.43 (0.19–1.0) | 0.51 (0.21–1.20) |
| 39 wk (n=2004) | 1.90 (1.32–2.73)b | 1.88 (1.29–2.76)b | 0.93 (0.52–1.65) | 1.03 (0.57–1.86) |
| 40 wk (n=1206) | 2.51 (1.51–4.16)b | 2.60 (1.52–4.43)b | 0.47 (0.17–1.31) | 0.51 (0.18–1.46) |
| 41 wk (n=299) | 1.48 (0.47–4.65) | 1.32 (0.39–4.44) | 1.11 (0.24–5.11) | 0.72 (0.15–3.51) |
| 42 wk (n=34) | N/Ac | N/Ac | N/Ac | N/Ac |
AGA indicates adequate for gestational age; OR, odds ratio.
Adjusted for severity of critical congenital heart disease, sex, and multiple gestation.
Statistically significant with P value <0.05.
No deaths in the small‐for‐gestational age (SGA) or large‐for‐gestational age (LGA) groups.
Table 3 shows the effect of fetal growth as a categorical variable on mortality in preterm (<37 weeks), early‐term (37–38 weeks), and full‐term (39–42 weeks) infants with CCHD. In preterm infants, the highest mortality was in infants with a Z score of 1 to 2 (34/108, 31.5%) and the lowest mortality was in infants with a Z score of 0.5 to 1 (21/115, 18.3%). In early‐term infants, the highest mortality was in infants with a Z score of <−2 (30/111, 25.2%) and the lowest mortality was in infants with a Z score of 0.5 to 1 (20/245, 8.2%). In full‐term infants, the mortality rate decreased from 23.7% (31/131) in the Z score category <−2% to 2.7% (3/111) in the Z score category >+2. In preterm and full‐term infants—after adjusting for severity of CCHD, sex, multiple gestation, and GA in weeks, only the groups with the most severe growth restriction (Z score <−2) had a higher adjusted OR for mortality (OR, 2.15 [95% CI, 1.10–4.21] in preterm and OR, 3.61 [95% CI, 2.18–5.96] in full‐term infants, respectively) than the reference group (Z score 0–0.5). There was a trend towards higher mortality in preterm infants with a Z score of 1 to 2 compared with the reference group, but this did not reach statistical significance (adjusted OR, 1.49; 95% CI, 0.83–2.70). In contrast, in full‐term infants, there was a trend towards lower mortality as the Z score increased, but, again, this did not reach statistical significance. In early‐term infants, the crude and adjusted ORs for mortality were increased for Z score groups of <−2, −2 to −1, and −1 to −0.5 compared with the reference group. Table 4 shows the results of the sensitivity analysis excluding multiple‐gestation infants without major changes of the results. For easy reference, Figure 2 shows mortality predictions using cubic splines adjusted for multiple gestation, sex, and complexity of CCHD by GA in preterm (Figure 2A), early‐term (Figure 2B), and full‐term (Figure 2C) infants to model the effect of Z score for BW while keeping the adjusted confounders at their mean level.
Table 3.
Effects of BW Z Score on Mortality in Preterm (<37 Weeks of Gestation), Early‐Term (37–38 Weeks of Gestation), and Full‐Term (39–42 Weeks of Gestation) Infants With Critical Congenital Heart Disease
| Mortality, % | Crude OR (95% CI) | Adjusted OR (95% CI)a | |
|---|---|---|---|
| Preterm: GA <37 wk | |||
| Z score <−2 (n=78) | 26.9 | 1.10 (0.59–2.02) | 2.15 (1.10–4.21)b |
| Z score −2 to −1 (n=262) | 23.7 | 0.92 (0.59–1.45) | 1.40 (0.85–2.31) |
| Z score −1 to −0.5 (n=214) | 18.7 | 0.68 (0.42–1.12) | 0.94 (0.55–1.61 |
| Z score −0.5 to 0 (n=214) | 22.4 | 0.86 (0.54–1.38) | 1.13 (0.67–1.90) |
| Z score 0–0.5 (n=167) | 25.2 | Reference | Reference |
| Z score 0.5–1 (n=115) | 18.3 | 0.66 (0.37–1.20) | 0.63 (0.33–1.20) |
| Z score 1–2 (n=108) | 31.5 | 1.37 (0.80–2.34) | 1.49 (0.83–2.70) |
| Z score >2 (n=61) | 21.3 | 0.81 (0.40–1.63) | 0.87 (0.40–1.88) |
| Early term: GA 37–38 wk | |||
| Z score <−2 (n=111) | 25.2 | 3.42 (1.93–6.04)b | 3.63 (1.98–6.67)b |
| Z score −2 to −1 (n=402) | 14.9 | 1.78 (1.12–2.83)b | 1.69 (1.04–2.75)b |
| Z score −1 to −0.5 (n=366) | 16.7 | 2.03 (1.27–3.23)b | 1.78 (1.10–2.89)b |
| Z score −0.5 to 0 (n=371) | 10.5 | 1.19 (0.72–1.96) | 1.13 (0.68–1.90) |
| Z score 0–0.5 (n=334) | 8.9 | Reference | Reference |
| Z score 0.5–1 (n=245) | 8.2 | 0.90 (0.50–1.77) | 0.79 (0.43–1.46) |
| Z score 1–2 (n=189) | 8.5 | 0.94 (0.50–1.77) | 1.0 (0.52–1.94) |
| Z score >2 (n=71) | 8.5 | 0.94 (0.37–2.34) | 1.08 (0.42–2.77) |
| Term: GA 39–42 wk | |||
| Z score <−2 (n=131) | 23.7 | 3.61 (2.18–5.96)b | 3.93 (2.31–6.68)b |
| Z score −2 to −1 (n=574) | 11.0 | 1.43 (0.96–2.14) | 1.48 (0.98–2.24) |
| Z score −1 to −0.5 (n=591) | 8.3 | 1.05 (0.69–1.60) | 1.17 (0.76–1.80) |
| Z score −0.5 to 0 (n=709) | 9.0 | 1.15 (0.78–1.71) | 1.18 (0.78–1.78) |
| Z score 0–0.5 (n=581) | 7.9 | Reference | Reference |
| Z score 0.5–1 (n=445) | 6.7 | 0.84 (0.52–1.36) | 0.90 (0.56–1.56) |
| Z score 1–2 (n=398) | 6.5 | 0.81 (0.49–1.35) | 0.93 (0.56–1.56) |
| Z score >2 (n=111) | 2.7 | 0.32 (0.10–1.06) | 0.39 (0.12–1.30) |
BW indicates birth weight; CI, confidence interval; OR, odds ratio.
Adjusted for severity of critical congenital heart disease, sex, multiple gestation, and gestational age (GA) in weeks.
Statistically significant with P‐value < 0.05.
Table 4.
Sensitivity Analysis
| Mortality, % | Crude OR (95% CI) | Adjusted OR (95% CI)a | |
|---|---|---|---|
| Preterm: GA <37 wk | |||
| Z score <−2 (n=56) | 28.6 | 1.12 (0.56–2.25) | 1.92 (0.90–4.12) |
| Z score −2 to −1 (n=189) | 25.4 | 0.96 (0.58–1.58) | 1.25 (0.72–2.18) |
| Z score −1 to −0.5 (n=158) | 19.0 | 0.66 (0.38–1.14) | 0.84 (0.46–1.52) |
| Z score −0.5 to 0 (n=158) | 25.3 | 0.95 (0.56–1.60) | 1.16 (0.65–2.06) |
| Z score 0–0.5 (n=137) | 26.3 | Reference | Reference |
| Z score 0.5–1 (n=101) | 19.8 | 0.69 (0.37–1.29) | 0.64 (0.32–1.27) |
| Z score 1–2 (n=102) | 32.4 | 1.34 (0.76–2.36) | 1.45 (0.78–2.70) |
| Z score >2 (n=60) | 21.7 | 0.78 (0.38–1.60) | 0.86 (0.39–1.89) |
| Early term: GA 37–38 wk | |||
| Z score <−2 (n=94) | 27.7 | 3.94 (2.13–6.90)b | 3.93 (2.11–7.31)b |
| Z score −2 to −1 (n=363) | 14.9 | 1.75 (1.09–2.82)b | 1.61 (1.04–2.63)b |
| Z score −1 to −0.5 (n=346) | 16.8 | 2.02 (1.26–3.23)b | 1.75 (1.07–2.85)b |
| Z score −0.5 to 0 (n=366) | 10.7 | 1.20 (0.73–1.98) | 1.16 (0.69–1.94) |
| Z score 0–0.5 (n=331) | 9.1 | Reference | Reference |
| Z score 0.5–1 (n=241) | 8.3 | 0.91 (0.50–1.64) | 0.80 (0.43–1.46) |
| Z score 1–2 (n=188) | 8.5 | 0.93 (0.50–1.76) | 1.0 (0.52–1.94) |
| Z score >2 (n=71) | 8.5 | 0.93 (0.37–2.32) | 1.07 (0.42–2.74) |
| Term: GA 39–42 wk | |||
| Z score <−2 (n=128) | 23.4 | 3.55 (2.14–5.91)b | 3.85 (2.26–6.57)b |
| Z score −2 to −1 (n=572) | 11.0 | 1.44 (0.96–2.14) | 1.49 (0.98–2.25) |
| Z score −1 to −0.5 (n=590) | 8.3 | 1.05 (0.69–1.60) | 1.17 (0.76–1.80) |
| Z score −0.5 to 0 (n=709) | 9.0 | 1.15 (0.78–1.71) | 1.18 (0.78–1.78) |
| Z score 0–0.5 (n=580) | 7.9 | Reference | Reference |
| Z score 0.5–1 (n=445) | 6.7 | 0.84 (0.52–1.35) | 0.90 (0.55–1.47) |
| Z score 1–2 (n=398) | 6.5 | 0.81 (0.49–1.34) | 0.93 (0.56–1.55) |
| Z score >2 (n=111) | 2.7 | 0.32 (0.10–1.06) | 0.39 (0.12–1.30) |
CI indicates confidence interval; OR, odds ratio. Effects of birth weight Z score on mortality in preterm (<37 weeks of gestation), early‐term (37–38 weeks of gestation), and full‐term (39–42 weeks of gestation) singleton infants with critical congenital heart disease.
Adjusted for severity of critical congenital heart disease, sex, and gestational age (GA) in weeks.
Statistically significant with P‐value < 0.05.
Figure 2.
Adjusted mortality prediction by Z score for birth weight in preterm (A), early‐term (B), and term (C) infants with critical congenital heart disease. Mortality predictions are adjusted for sex, severity of critical congenital heart disease, and multiple birth. All predictors are kept at their mean. GA indicates gestational age.
Discussion
This population‐based study of infants with CCHD investigated the effect of fetal growth measured by BW Z score on 1‐year mortality and found a different pattern of its effect in different GA groups. In preterm infants, only severe SGA (Z score <−2) was associated with increased mortality compared with infants with a BW Z score of 0 to 0.5 and there was a trend toward increased mortality in LGA infants that did not reach statistical significance. In early‐term infants, a more pronounced association between low BW (LBW) Z score and mortality was found. Infants with a Z score up to −0.5 experienced a higher mortality rate than infants with a Z score 0 to 0.5. Similar to preterm infants, in full‐term infants, only severe SGA (Z score <−2) was associated with increased mortality. However, in contrast to preterm infants, mortality in full‐term infants continued to decrease as the Z score increased, although this did not reach statistical significance.
Several reports show higher mortality and morbidity rates in LBW infants with CHD compared with infants with normal BW.22, 23, 24 It is important to distinguish between LBW and SGA since they represent 2 different concepts. The term LBW includes appropriately grown but preterm infants, thus a group of infants with LBW will have a lower mean GA than a group of infants with normal BW. In contrast, SGA, AGA, LGA, and Z score for BW all report measures standardized for GA and sex, and as such are often used as surrogate markers for fetal growth. Increased mortality in LBW infants with CHD does not address the question of whether fetal growth—as measured by SGA/AGA/LGA or Z score for BW—impacts this outcome since the increased mortality rate in LBW infants is mainly driven by lower GA, and it is well known that GA is a major determinant of mortality in infants with7, 8, 25 and without CHD.26
Overall, infants with CHD are more likely to be SGA.10 However, few studies have investigated the impact of SGA birth on postnatal outcomes in this patient population. In a single institution, retrospective review of 230 infants requiring neonatal cardiothoracic intervention, SGA infants had a higher 30‐day and discharge mortality rate compared with AGA infants.12 This study was relatively small, only adjusted for sex in the multivariate models, and did not have the power to address a potential interaction between SGA and GA. Another small single‐institution study (n=76)14 compared SGA and non‐SGA infants of similar absolute weights and found no differences in postoperative mortality. This result was most likely explained by the higher GA at birth in the SGA versus non‐SGA infants. Best and colleagues15 recently published data on long‐term survival estimates in 5093 infants with CHD born between the years 1985 and 2003 in the north of England. They divided the cases into 3 Z score categories and found that infants with Z score <−1 had a higher crude and adjusted hazard ratio for 5‐year mortality than infants with a Z score 1≤ Z ≤1, and infants with a Z score >1 had a slightly lower adjusted hazard ratio. While these findings are similar to our findings in full‐term infants, the study by Best and colleagues assessed only 3 Z score categories and, although they adjusted for GA, they did not include a statistical interaction term in their model between Z score for BW and GA, nor did they stratify by GA and, as such, they were potentially missing a more complex relationship.
Our study is novel and unique in that it assesses the effect of BW Z score on mortality as a multicategorical variable and not just as SGA versus non‐SGA. Second, it stratifies the analysis by different GA groups in order to explore a potentially different impact of Z score for BW on mortality in preterm, early‐term, and full‐term infants with CCHD. We found that across all 3 GA groups, severely SGA infants with CCHD were at increased risk for mortality. These results are similar to findings in infants without CCHD.11 In infants without CCHD, SGA has been linked to the development of early systemic hypertension,27 type 2 diabetes mellitus,28 hyperlipidemia,28 and reduced renal function.29, 30 We hypothesize that this link is even more apparent in infants with CCHD. Further studies should focus on follow‐up of SGA infants with CCHD to understand its implications not only for mortality but also for long‐term outcomes and to develop early interventions.
Most interestingly, we found that in early‐term infants with CCHD, the association between BW Z score and mortality is much more pronounced than in other GA categories and that even Z scores as high as −1 to −0.5 present an increased risk for mortality. Historically, term infants born at 37 to 42 weeks have been considered a uniform group.31 However, more recently, early‐term infant vulnerability has been documented and several studies in infants without CCHD have shown that early‐term infants born at 37 to 38 weeks have a higher incidence of respiratory distress, developmental morbidities, and even infant mortality.32, 33 In infants with CCHD, 2 studies have shown increased mortality, neonatal morbidities, and postoperative complications in early‐term versus full‐term infants.7, 8 Our current study suggests that Z score for BW has the most granular effect in early‐term infants with CCHD, making this group particularly vulnerable. A possible explanation for these findings is that in preterm infants, GA is a much stronger driver of mortality and that BW plays a less important role. Similarly, in full‐term infants, the mature GA seems to be protective against increased mortality from lower Z score for BW. In early‐term infants, on the other hand, the effects of lower BW Z scores become most apparent. These findings should be validated in other cohorts of infants with CCHD.
It is also interesting to mention that the effect of high BW Z scores appears to be different in preterm versus term infants, although this did not reach statistical significance. In term infants, there is a trend toward decreased mortality with higher BW Z score, while in preterm infants, there is a trend toward higher mortality with a BW Z score >1 (Figures 1 and 2). We speculate that this trend in preterm infants is caused by hydrops fetalis that might be present in severe cases of CCHD, leading to preterm delivery of LGA infants.
The results of this study provide important information for the medical team taking care of these infants. BW Z score as low as −2 in preterm infants with CCHD should not automatically be considered as a risk factor for mortality when counseling parents or when deciding whether to provide surgical interventions. It is unclear whether our results should impact timing of delivery of early‐term infants with low estimated fetal weight corresponding to a low Z score. In fact, early delivery might be a confounder in the relationship between LBW Z score and mortality if the elective early deliveries were initiated because of poor fetal growth. With regards to postnatal care, weight gain of early‐term infants with CCHD, even if only mildly growth restricted, should be followed carefully. However, it is unclear what postnatal growth trajectory should be targeted since there is some evidence that early catch‐up growth in SGA infants might be associated with childhood and adulthood obesity.34, 35 Further studies are needed to address these important questions in infants with CCHD.
The underlying mechanism by which fetal growth affects outcome in CCHD remains speculative. Recently, the fetal environment has been recognized as a potential important contributor to postnatal outcomes in infants with CCHD.36, 37 Gaynor and colleagues36 showed that after cardiac surgery in neonates, the presence of an impaired maternal‐fetal environment, defined as preeclampsia, SGA, or preterm birth, was associated with lower survival at 36 months of age. Miller et al37 found that uteroplacental insufficiency was associated with asymmetric prenatal growth, poor weight gain, and decreased myocardial performance in infants with hypoplastic left heart syndrome. Future studies should investigate potential underlying biological mechanisms explaining these finding.
Study Limitations
This study has some important limitations. First, the data set used does not contain data on longitudinal intrauterine growth or information on head circumference, thus we were unable to assess fetal growth restriction per se because this term implies an in utero insult that led to a fetus not meeting its growth potential.38 Assessing the growth potential in infants with CCHD is further complicated by the fact that cardiac lesion–specific differences in BW have been described.39 Additionally, with the lack of head circumference data, we were unable to distinguish between symmetric and asymmetric growth restriction.38 Future studies should focus on these unanswered questions and assess lesion‐specific outcomes to better understand the nuanced relationship between BW and GA in neonates with CCHD.
Another potential limitation is the fact that identification of the cases with CCHD depended on ICD‐9‐CM codes. Thus, it is possible that we missed cases if the ICD‐9 coding was incomplete. With regards to the classification of CCHD, although 2 physicians independently reviewed every case with multiple codes for CCHD, we could not exclude misclassification of infants with CHD based on ICD‐9 codes.40 Lack of data regarding surgical repair details made grouping of CCHD according to RACHS or another established surgical classification system challenging, and we ended up modifying the RACHS classification. Still, given that the only purpose of classification and severity grouping of CCHD cases in this study was to ensure that CCHD severity was adjusted for across Z score categories, and we are confident that this goal was achieved. It is also important to mention that we were unable to include fetal demises or stillbirths, which could potentially have an impact on our findings. A significant benefit of this study is its population‐based nature, and, in contrast to studies from surgical databases, it is less prone to selection bias as it includes infants who died before surgical interventions.
Conclusions
This study provides further important insight into the association of fetal growth and 1‐year mortality in neonates with CCHD. We identified the strongest association between LBW Z score and mortality in early‐term infants with CCHD. This information could be of great value for counseling of parents and for medical providers caring for this patient population.
Sources of Funding
This work was supported by the California Preterm Birth Initiative.
Disclosures
None.
(J Am Heart Assoc. 2018;7:e009693 DOI: 10.1161/JAHA.118.009693.)
This article was handled independently by Mark W. Russell, MD, as a guest editor. The editors had no role in the evaluation of the article or in the decision about its acceptance.
References
- 1. Dolk H, Loane M, Garne E; a European Surveillance of Congenital Anomalies (EUROCAT) Working Group . Congenital heart defects in Europe: prevalence and perinatal mortality, 2000 to 2005. Circulation. 2011;123:841–849. [DOI] [PubMed] [Google Scholar]
- 2. van der Linde D, Konings EEM, Slager MA, Witsenburg M, Helbing WA, Takkenberg JJM, Roos‐Hesselink JW. Birth prevalence of congenital heart disease worldwide. J Am Coll Cardiol. 2011;58:2241–2247. [DOI] [PubMed] [Google Scholar]
- 3. Oster ME, Lee KA, Honein MA, Riehle‐Colarusso T, Shin M, Correa A. Temporal trends in survival among infants with critical congenital heart defects. Pediatrics. 2013;131:e1502–e1508. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, Das SR, de Ferranti S, Després J‐P, Fullerton HJ, Howard VJ, Huffman MD, Isasi CR, Jiménez MC, Judd SE, Kissela BM, Lichtman JH, Lisabeth LD, Liu S, Mackey RH, Magid DJ, McGuire DK, Mohler ER, Moy CS, Muntner P, Mussolino ME, Nasir K, Neumar RW, Nichol G, Palaniappan L, Pandey DK, Reeves MJ, Rodriguez CJ, Rosamond W, Sorlie PD, Stein J, Towfighi A, Turan TN, Virani SS, Woo D, Yeh RW, Turner MB; American Heart Association Statistics Committee, Stroke Statistics Subcommittee . Heart disease and stroke statistics—2016 update: a report from the American Heart Association. Circulation. 2016;133:e38–e360. [DOI] [PubMed] [Google Scholar]
- 5. Triedman JK, Newburger JW. Trends in congenital heart disease: the next decade. Circulation. 2016;133:2716–2733. [DOI] [PubMed] [Google Scholar]
- 6. Jacobs ML, Jacobs JP, Hill KD, Hornik C, O'Brien SM, Pasquali SK, Vener D, Kumar SR, Habib RH, Shahian DM, Edwards FH, Fernandez FG. The Society of Thoracic Surgeons Congenital Heart Surgery Database: 2017 update on research. Ann Thorac Surg. 2017;104:731–741. [DOI] [PubMed] [Google Scholar]
- 7. Steurer MA, Baer RJ, Keller RL, Oltman S, Chambers CD, Norton ME, Peyvandi S, Rand L, Rajagopal S, Ryckman KK, Moon‐Grady AJ, Jelliffe‐Pawlowski LL. Gestational age and outcomes in critical congenital heart disease. Pediatrics. 2017;140:e20170999. [DOI] [PubMed] [Google Scholar]
- 8. Costello JM, Pasquali SK, Jacobs JP, He X, Hill KD, Cooper DS, Backer CL, Jacobs ML. Gestational age at birth and outcomes after neonatal cardiac surgery: an analysis of the Society of Thoracic Surgeons Congenital Heart Surgery Database. Circulation. 2014;129:2511–2517. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Khoury MJ, Erickson JD, Cordero JF, McCarthy BJ. Congenital malformations and intrauterine growth retardation: a population study. Pediatrics. 1988;82:83–90. [PubMed] [Google Scholar]
- 10. Malik S, Cleves MA, Zhao W, Correa A, Hobbs CA; and the National Birth Defects Prevention Study . Association between congenital heart defects and small for gestational age. Pediatrics. 2007;119:e976–e982. [DOI] [PubMed] [Google Scholar]
- 11. Ray JG, Park AL, Fell DB. Mortality in infants affected by preterm birth and severe small‐for‐gestational age birth weight. Pediatrics. 2017;140:e20171881. [DOI] [PubMed] [Google Scholar]
- 12. Sochet AA, Ayers M, Quezada E, Braley K, Leshko J, Amankwah EK, Quintessenza JA, Jacobs JP, Dadlani G. The importance of small for gestational age in the risk assessment of infants with critical congenital heart disease. Cardiol Young. 2014;23:896–904. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Mitting R, Marino L, Macrae D, Shastri N, Meyer R, Pathan N. Nutritional status and clinical outcome in postterm neonates undergoing surgery for congenital heart disease. Pediatr Crit Care Med. 2015;16:448–452. [DOI] [PubMed] [Google Scholar]
- 14. Wei D, Azen C, Bhombal S, Hastings L, Paquette L. Congenital heart disease in low‐birth‐weight infants: effects of small for gestational age (SGA) status and maturity on postoperative outcomes. Pediatr Cardiol. 2015;36:1–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Best KE, Tennant PW, Rankin J. Survival, by birth weight and gestational age, in individuals with congenital heart disease: a population‐based study. J Am Heart Assoc. 2017;6:e005213 DOI: 10.1161/JAHA.116.005213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. American Medical Association . International Classification of Diseases: ICD‐9‐CM 2008. Chicago, IL: American Medical Association; 2007. [Google Scholar]
- 17. Jelliffe‐Pawlowski LL, Norton ME, Shaw GM, Baer RJ, Flessel MC, Goldman S, Currier RJ. Risk of critical congenital heart defects by nuchal translucency norms. Am J Obstet Gynecol. 2015;212:518.e1–10. [DOI] [PubMed] [Google Scholar]
- 18. Mahle WT, Newburger JW, Matherne GP, Smith FC, Hoke TR, Koppel R, Gidding SS, Beekman RH, Grosse SD; American Heart Association Congenital Heart Defects Committee of the Council on Cardiovascular Disease in the Young, Council on Cardiovascular Nursing, and Interdisciplinary Council on Quality of Care and Outcomes Research, American Academy of Pediatrics Section on Cardiology and Cardiac Surgery, and Committee on Fetus and Newborn . Role of pulse oximetry in examining newborns for congenital heart disease: a scientific statement from the American Heart Association and American Academy of Pediatrics. Circulation. 2009;120:447–458. [DOI] [PubMed] [Google Scholar]
- 19. Riehle‐Colarusso T, Strickland MJ, Reller MD, Mahle WT, Botto LD, Siffel C, Atkinson M, Correa A. Improving the quality of surveillance data on congenital heart defects in the metropolitan Atlanta congenital defects program. Birth Defects Res A Clin Mol Teratol. 2007;79:743–753. [DOI] [PubMed] [Google Scholar]
- 20. Jenkins KJ, Gauvreau K, Newburger JW, Spray TL, Moller JH, Iezzoni LI. Consensus‐based method for risk adjustment for surgery for congenital heart disease. J Thorac Cardiovasc Surg. 2002;123:110–118. [DOI] [PubMed] [Google Scholar]
- 21. Talge NM, Mudd LM, Sikorskii A, Basso O. United States birth weight reference corrected for implausible gestational age estimates. Pediatrics. 2014;133:844–853. [DOI] [PubMed] [Google Scholar]
- 22. Curzon CL, Milford‐Beland S, Li JS, O'Brien SM, Jacobs JP, Jacobs ML, Welke KF, Lodge AJ, Peterson ED, Jaggers J. Cardiac surgery in infants with low birth weight is associated with increased mortality: analysis of the Society of Thoracic Surgeons Congenital Heart Database. J Thorac Cardiovasc Surg. 2008;135:546–551. [DOI] [PubMed] [Google Scholar]
- 23. Ades A, Johnson BA, Berger S. Management of low birth weight infants with congenital heart disease. Clin Perinatol. 2005;32:999–1015. [DOI] [PubMed] [Google Scholar]
- 24. Ades AM, Dominguez TE, Nicolson SC, Gaynor JW, Spray TL, Wernovsky G, Tabbutt S. Morbidity and mortality after surgery for congenital cardiac disease in the infant born with low weight. Cardiol Young. 2010;20:8–17. [DOI] [PubMed] [Google Scholar]
- 25. Costello JM, Polito A, Brown DW, McElrath TF, Graham DA, Thiagarajan RR, Bacha EA, Allan CK, Cohen JN, Laussen PC. Birth before 39 weeks’ gestation is associated with worse outcomes in neonates with heart disease. Pediatrics. 2010;126:277–284. [DOI] [PubMed] [Google Scholar]
- 26. Ancel P‐Y, Goffinet F, Kuhn P, Langer B, Matis J, Hernandorena X, Chabanier P, Joly‐Pedespan L, Lecomte B, Vendittelli F, Dreyfus M, Guillois B, Burguet A, Sagot P, Sizun J, Beuchée A, Rouget F, Favreau A, Saliba E, Bednarek N, Morville P, Thiriez G, Marpeau L, Marret S, Kayem G, Durrmeyer X, Granier M, Baud O, Jarreau PH, Mitanchez D, Boileau P, Boulot P, Cambonie G, Daudé H, Bédu A, Mons F, Fresson J, Vieux R, Alberge C, Arnaud C, Vayssière C, Truffert P, Pierrat V, Subtil D, D'Ercole C, Gire C, Simeoni U, Bongain A, Sentilhes L, Rozé JC, Gondry J, Leke A, Deiber M, Claris O, Picaud JC, Ego A, Debillon T, Poulichet A, Coliné E, Favre A, Fléchelles O, Samperiz S, Ramful D, Branger B, Benhammou V, Foix‐L'Hélias L, Marchand‐Martin L, Kaminski M. Survival and morbidity of preterm children born at 22 through 34 weeks’ gestation in France in 2011. JAMA Pediatr. 2015;169:230–239. [DOI] [PubMed] [Google Scholar]
- 27. Barker DJ, Bull AR, Osmond C, Simmonds SJ. Fetal and placental size and risk of hypertension in adult life. BMJ. 1990;301:259–262. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Barker DJ, Hales CN, Fall CH, Osmond C, Phipps K, Clark PM. Type 2 (non‐insulin‐dependent) diabetes mellitus, hypertension and hyperlipidaemia (syndrome X): relation to reduced fetal growth. Diabetologia. 1993;36:62–67. [DOI] [PubMed] [Google Scholar]
- 29. Luyckx VA, Bertram JF, Brenner BM, Fall C, Hoy WE, Ozanne SE, Vikse BE. Effect of fetal and child health on kidney development and long‐term risk of hypertension and kidney disease. Lancet. 2013;382:273–283. [DOI] [PubMed] [Google Scholar]
- 30. Hoy WE, Rees M, Kile E, Mathews JD, Wang Z. A new dimension to the Barker hypothesis: low birthweight and susceptibility to renal disease. Kidney Int. 1999;56:1072–1077. [DOI] [PubMed] [Google Scholar]
- 31. Craighead DV, Elswick RK. The influence of early‐term birth on NICU admission, length of stay, and breastfeeding initiation and duration. J Obstet Gynecol Neonatal Nurs. 2014;43:409–421. [DOI] [PubMed] [Google Scholar]
- 32. Engle WA. Morbidity and mortality in late preterm and early term newborns: a continuum. Clin Perinatol. 2011;38:493–516. [DOI] [PubMed] [Google Scholar]
- 33. Reddy UM, Bettegowda VR, Dias T, Yamada‐Kushnir T, Ko C‐W, Willinger M. Term pregnancy: a period of heterogeneous risk for infant mortality. Obstet Gynecol. 2011;117:1279–1287. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Ong KK, Ahmed ML, Emmett PM, Preece MA, Dunger DB. Association between postnatal catch‐up growth and obesity in childhood: prospective cohort study. BMJ. 2000;320:967–971. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Stettler N. Nature and strength of epidemiological evidence for origins of childhood and adulthood obesity in the first year of life. Int J Obes (Lond). 2007;31:1035–1043. [DOI] [PubMed] [Google Scholar]
- 36. Gaynor JW, Parry S, Moldenhauer JS, Simmons RA, Rychik J, Ittenbach RF, Russell WW, Zullo E, Ward JL, Nicolson SC, Spray TL, Johnson MP. The impact of the maternal‐foetal environment on outcomes of surgery for congenital heart disease in neonates. Eur J Cardiothorac Surg. 2018;54:348–353. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Miller TA, Joss‐Moore L, Menon SC, Weng C, Puchalski MD. Umbilical artery systolic to diastolic ratio is associated with growth and myocardial performance in infants with hypoplastic left heart syndrome. Prenat Diagn. 2014;34:128–133. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Nardozza LMM, Araujo Júnior E, Barbosa MM, Caetano ACR, Lee DJR, Moron AF. Fetal growth restriction: current knowledge to the general Obs/Gyn. Arch Gynecol Obstet. 2012;286:1–13. [DOI] [PubMed] [Google Scholar]
- 39. Rosenthal GL, Wilson PD, Permutt T, Boughman JA, Ferencz C. Birth weight and cardiovascular malformations: a population‐based study. The Baltimore‐Washington Infant Study. Am J Epidemiol. 1991;133:1273–1281. [DOI] [PubMed] [Google Scholar]
- 40. Strickland MJ, Riehle‐Colarusso TJ, Jacobs JP, Reller MD, Mahle WT, Botto LD, Tolbert PE, Jacobs ML, Lacour‐Gayet FG, Tchervenkov CI, Mavroudis C, Correa A. The importance of nomenclature for congenital cardiac disease: implications for research and evaluation. Cardiol Young. 2008;18(suppl 2):92–100. [DOI] [PMC free article] [PubMed] [Google Scholar]