A predictive model of offspring congenital heart disease based on maternal risk factors during pregnancy: a hospital based case-control study in Nanchong City

Abstract

Objective: Based on epidemiological field data, this study was to develop a prediction model which can be used as a preliminary screening tool to identify pregnant women who were at high risk of offspring congenital heart disease (CHD) in Nanchong City, and be beneficial in guiding prenatal management and prevention. Methods: A total of 367 children with CHD and 367 children without congenital malformations aged 0 to 14 years old were recruited from the Affiliated Hospital of North Sichuan Medical College and Nanchong Central Hospital between March 2016 and November 2018. Using the SPSS 22.0 case-control matching module, the controls were matched to the cases at a rate of 1:1, according to the same gestational age of child (premature delivery or full-term), the maternal age of pregnancy (less than 1 year). 327 matched case-control pairs were analyzed by SPSS 22. Univariate and multivariate analysis were performed to find the important maternal influencing factors of offspring CHD. A logistic regression disease prediction model was constructed as the final predictors, and Hosmer-Lemeshow goodness of fit test and receiver operating characteristic (ROC) curve were used to evaluate the model. Results: 654 subjects (327 cases and 327 controls) were matched. The 25 variables were analysed. The logistic regression model established in this study was as follows: Logit(P)= -2.871+(0.686×respiratory infections)+(1.176×water pollution)+(1.019×adverse emotions during pregnancy) - (0.617×nutrition supplementation). The Hosmer-Lemeshow chi-square value was 7.208 (df = 6), with a nonsignificant p value of 0.302, which indicates that the model was well-fitted. The calibration plot showed good agreement between the bias-corrected prediction and the ideal reference line. Area under the ROC curve was 0.72 (95% CI: 0.681~0.759), which means that the predictive power of the model set fitted the data. Conclusion: In Nanchong city, more attention should be paid to mother who had a history of respiratory infections, exposure to polluted water, adverse emotions during pregnancy and nutritional deficiency. The risk model might be an effective tool for predicting of the risk of CHD in offspring by maternal experience during pregnancy, which can be used for clinical practise in Nanchong area.

How Parental Predictors Jointly Affect the Risk of Offspring Congenital Heart Disease: A Nationwide Multicenter Study Based on the China Birth Cohort

“…The association between maternal folic acid as well as multivitamin supplementation and the risk of offspring CHD was controversial (19,22,23). The protective effect of maternal folic acid and multivitamin supplementation against offspring CHD may be because folic acid and multivitamin have antagonistic effects on the process of vascular disruption, and have a rescue effect on apoptotic cells with folic acid deficiency (6). Offspring of our study conceived through assisted reproductive technology was more likely to develop CHD compared with those conceived spontaneously (20).…”

“…Congenital heart disease (CHD) is the most common structural birth defect with an incidence rate of 6-12 per 1,000 newborns (1)(2)(3)(4), and its estimated prevalence is about 19-20 per 1,000 newborns when the bicuspid aortic valve is included (5,6). In China, a national study reported an overall CHD prevalence of 9 per 1,000 newborns (7), and it remains the leading noninfectious cause of death in infancy and childhood despite tremendous progress in surgical therapies (8).…”

Risk Assessment for Birth Defects in Offspring of Chinese Pregnant Women

“…Other predictive models have been developed for birth defects. Based on epidemiological field data, using logistic regression, Liang Y et al developed a prediction model that can be used to identify pregnant women who are at high risk of offspring congenital heart defects in Nanchong City, China [ 30 ]. Wang JF et al collected socioeconomic and geographical factors for 7880 live births, and used a support vector machine to develop a prediction model for neural tube defects [ 31 ].…”

“…Thousands of different birth defects affect the structure or function of fetuses. Most of the clinical studies and predictive models were focused on major birth defects, such as congenital heart defects and neural tube defects [ 30 , 31 , 32 ]. Based on a predictive model for any type of birth defect, we developed a nomogram that can be used as a preliminary screening tool to identify pregnant women at high risk of producing offspring with any birth defects and that can help to guide prenatal management and prevention.…”

Dietary Inflammatory Index during Pregnancy and Congenital Heart Defects

“…However, to our knowledge there has been no study assessing the association between DII during pregnancy and CHD risk. Previous studies have evaluated some maternal predictors in pregnancy for CHD [ 14 , 19 , 20 ], giving references for the early prediction of CHD. However, the predictive value of DII for CHD has not been assessed.…”