To examine the relationship between area-level material deprivation and the risk of congenital anomalies in infants admitted to neonatal intensive care units (NICUs) across Canada.
The Canadian Neonatal Network database was used to identify admitted infants who had congenital anomalies between 2005 and 2009. The association between congenital anomalies and material deprivation quintile was assessed using logistic regression analysis.
Of 55,961 infants admitted to participating NICUs during the study period, 6002 (10.7%) had major, 6244 (11.2%) had minor, and 43,715 (78.1%) had no anomalies. There were higher odds of major anomalies (odds ratio [OR] 1.13, 95% confidence interval [CI] 1.03 to 1.24) but not minor anomalies (OR 1.01, 95% CI 0.93 to 1.11) in the highest-deprivation areas as compared with the lowest-deprivation area of maternal residence. Analyses of groups of major anomalies revealed higher odds for chromosomal (OR 1.48, 95% CI 1.05 to 2.10) and multiple-systems (OR 1.40, 95% CI 1.14 to 1.71) anomalies in the highest-deprivation areas compared with the lowest-deprivation areas.
There are socioeconomic inequalities in the risk of major congenital anomalies, especially chromosomal and multiple-systems anomalies, in the NICU population with the highest rates in the most socioeconomically deprived areas.
Preterm infants needing patent ductus arteriosus (PDA) ligation are transferred to a pediatric cardiac center (CC) unless the operation can be done locally by a pediatric surgeon at a non-cardiac center (NCC). We compared infant outcomes after PDA ligation at CC and NCC.
We analyzed 990 preterm infants who had PDA ligation between 2005 and 2009 using the Canadian Neonatal Network database. In-hospital mortality and major morbidities were compared between CC (n=18) and NCC (n=9).
SNAP-II-adjusted mortality rates were similar (CC=8.7% vs NCC=10.7%, P=.32). Significant cranial ultrasound abnormalities (CC=24.1% vs NCC=32.1%, P
To develop and validate a statistical prediction model spanning the severity range of neonatal outcomes in infants born at = 30 weeks' gestation.
A national cohort of infants, born at 23 to 30 weeks' gestation and admitted to level III NICUs in Canada in 2010-2011, was identified from the Canadian Neonatal Network database. A multinomial logistic regression model was developed to predict survival without morbidities, mild morbidities, severe morbidities, or mortality, using maternal, obstetric, and infant characteristics available within the first day of NICU admission. Discrimination and calibration were assessed using a concordance C-statistic and the Cg goodness-of-fit test, respectively. Internal validation was performed using a bootstrap approach.
Of 6106 eligible infants, 2280 (37%) survived without morbidities, 1964 (32%) and 1251 (21%) survived with mild and severe morbidities, respectively, and 611 (10%) died. Predictors in the model were gestational age, small (20, outborn status, use of antenatal corticosteroids, and receipt of surfactant and mechanical ventilation on the first day of admission. High model discrimination was confirmed by internal bootstrap validation (bias-corrected C-statistic = 0.899, 95% confidence interval = 0.894-0.903). Predicted probabilities were consistent with the observed outcomes (Cg P value = .96).
Neonatal outcomes ranging from mortality to survival without morbidity in extremely preterm infants can be predicted on their first day in the NICU by using a multinomial model with good discrimination and calibration. The prediction model requires additional external validation.
Gastroschisis is a serious birth defect of the abdominal wall that is associated with mortality and significant morbidity. Our understanding of the factors causing this defect is limited. The objective of this paper is to describe the geographic variation in incidence of gastroschisis and characterize the spatial pattern of all gastroschisis cases in Canada between 2006 and 2011. Specifically, we aimed to ascertain the differences in spatial patterns between geographic regions and identify significant clusters and their location.
The study population included 641 gastroschisis cases from the Canadian Pediatric Surgery Network (CAPSNet) database, a population-based dataset of all gastroschisis cases in Canada. Cases were geocoded based on maternal residence. Using Statistics Canada live-birth data as a denominator, the total prevalence of gastroschisis was calculated at the provincial/territorial levels. Random effects logistic models were used to estimate the rates of gastroschisis in each census division. These rates were then mapped using ArcGIS. Cluster detection was performed using Local Indicators of Spatial Association (LISA).
There is significant spatial heterogeneity of the rate of gastroschisis across Canada at both the provincial/territorial and census-division level. The Yukon, Northwest Territories and Prince Edward Island have higher overall rates of gastroschisis relative to other provinces/territories. Several census divisions in Alberta, Manitoba, Saskatchewan, Ontario, Northwest Territories and British Columbia demonstrated case "clusters", i.e., focally higher rates in discrete areas relative to surrounding areas.
There is clear evidence of spatial variation in the rates of gastroschisis across Canada. Future research should explore the role of area-based variables in these patterns to improve our understanding of the etiology of gastroschisis.