Prediction of cyanotic and acyanotic congenital heart disease using machine learning models

BACKGROUND Congenital heart disease is most commonly seen in neonates and it is a major cause of pediatric illness and childhood morbidity and mortality.AIM To identify and build the best predictive model for predicting cyanotic and acyanotic congenital heart disease in children during pregnancy and identify their potential risk factors.METHODS The data were collected from the Pediatric Cardiology Department at Chaudhry Pervaiz Elahi Institute of Cardiology Multan,Pakistan from December 2017 to October 2019.A sample of 3900 mothers whose children were diagnosed with identify the potential outliers.Different machine learning models were compared,and the best-fitted model was selected using the area under the curve,sensitivity,and specificity of the models.RESULTS Out of 3900 patients included,about 69.5%had acyanotic and 30.5%had cyanotic congenital heart disease.Males had more cases of acyanotic(53.6%)and cyanotic(54.5%)congenital heart disease as compared to females.The odds of having cyanotic was 1.28 times higher for children whose mothers used more fast food frequently during pregnancy.The artificial neural network model was selected as the best predictive model with an area under the curve of 0.9012,sensitivity of 65.76%,and specificity of 97.23%.CONCLUSION Children having a positive family history are at very high risk of having cyanotic and acyanotic congenital heart disease.Males are more at risk and their mothers need more care,good food,and physical activity during pregnancy.The best-fitted model for predicting cyanotic and acyanotic congenital heart disease is the artificial neural network.The results obtained and the best model identified will be useful for medical practitioners and public health scientists for an informed decision-making process about the earlier diagnosis and improve the health condition of children in Pakistan.

Elevated serum levels of ghrelin and TNF-a in patients with cyanotic and acyanotic congenital heart disease

Background:The levels of ghrelin and tumor necrosis factor alpha (TNF-a) are considered biological markers of congenital heart diseases (CHD).The present meta-analysis was conducted to investigate the clinical significance of serum levels of ghrelin and TNF-α in children with (CHD).Methods:Chinese and English scientific literature databases were searched to retrieve published studies relevant to ghrelin,TNF-α and CHD.Manual search was additionally employed to identify other relevant studies from cross-references.The retrieved studies were screened on the basis of our stringent inclusion and exclusion criteria to select high quality case-control studies for meta-analysis.Results:We initially retrieved 108 published studies (20 in Chinese and 88 in English) from database searches.Finally,6 case-control studies (5 in English and 1 in Chinese) were enrolled in our meta-analysis,and contained a total of 160 cyanotic congenital heart disease (CCHD) patients and 215 acyanotic congenital heart disease (ACHD) patients,along with 162 healthy controls.The results of meta-analysis showed that serum levels of ghrelin and TNF-α in CCHD or ACHD children were significantly higher than those in healthy controls.Conclusion:Our meta-analysis results showed that serum levels of ghrelin and TNF-α are elevated in children with CHD,and could be used as effective biologic markers in early diagnosis of CHD.