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- Creators: Arizona State University
- Creators: Johnston, Carol
- Creators: College of Health Solutions
- Creators: Dean, W.P. Carey School of Business
- Status: Published
2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing fetal heart development but they warrant revalidation and adjustment. 377 normal fetuses with healthy mothers, 98 normal fetuses with diabetic mothers, and 37 fetuses with cardiomyopathy and diabetic mothers had their cardiac structural dimensions, cardiothoracic ratio, valve flow velocities, and heart rates measured by fetal ECHO in a retrospective chart review. Cardiac features were fitted to linear functions, with respect to gestational age, femur length, head circumference, and biparietal diameter and z-scores were created to model normal fetal growth for all parameters. These z-scores were used to assess what metrics had no difference in means between the normal fetuses of both healthy and diabetic mothers but differed from those diagnosed with cardiomyopathy. It was found that functional metrics like mitral and tricuspid E wave and pulmonary velocity could be important predictors for cardiomyopathy when fitted by gestational age, femur length, head circumference, and biparietal diameter. Additionally, aortic and tricuspid annulus diameters when fitted to estimated gestational age showed potential to be predictors for fetal cardiomyopathy. While the metrics overlapped over their full range, combining them together may have the potential for predicting cardiomyopathy in utero. Future directions of this study will explore creating a classifier model that can predict cardiomyopathy using the metrics assessed in this study.
2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing fetal heart development but they warrant revalidation and adjustment. 377 normal fetuses with healthy mothers, 98 normal fetuses with diabetic mothers, and 37 fetuses with cardiomyopathy and diabetic mothers had their cardiac structural dimensions, cardiothoracic ratio, valve flow velocities, and heart rates measured by fetal ECHO in a retrospective chart review. Cardiac features were fitted to linear functions, with respect to gestational age, femur length, head circumference, and biparietal diameter and z-scores were created to model normal fetal growth for all parameters. These z-scores were used to assess what metrics had no difference in means between the normal fetuses of both healthy and diabetic mothers, but differed from those diagnosed with cardiomyopathy. It was found that functional metrics like mitral and tricuspid E wave and pulmonary velocity could be important predictors for cardiomyopathy when fitted by gestational age, femur length, head circumference, and biparietal diameter. Additionally, aortic and tricuspid annulus diameters when fitted to estimated gestational age showed potential to be predictors for fetal cardiomyopathy. While the metrics overlapped over their full range, combining them together may have the potential for predicting cardiomyopathy in utero. Future directions of this study will explore creating a classifier model that can predict cardiomyopathy using the metrics assessed in this study.
ormoglycemic controls (NC), dyslipidemic
ormoglycemic (DN), dyslipidemic/prediabetic (DPD) and dyslipidemic/diabetic (DD). Total cholesterol (TC) was 30% higher among DD than in NC participants (p<0.0001). The DPD group had 27% and 12% higher LDL-C concentrations than the NC and DN groups, respectively. Similarly, LDL-C was 29% and 13% higher in DD than in NC and DN participants (p=0.013). An increasing trend was observed in %10-year CVD risk with increasing degree of hyperglycemia (p<0.0001). The NC group had less cholesterol in sdLDL particles than dyslipidemic groups, regardless of glycemic status (p<0.0001). When hyperglycemia was part of the phenotype (DPD and DD), there was a greater proportion of total and HDL-C in sHDL particles in dyslipidemic individuals than in NC (p=0.023; p<0.0001; respectively). Percent 10-year CVD risk was positively correlated with triglyceride (TG) (r=0.384, p<0.0001), TC (r=0.340, p<0.05), cholesterol in sdLDL(r=0.247; p<0.05), and TC to HDL-C ratio (r=0.404, p<0.0001), and negatively correlated with HDL-C in intermediate and large HDL(r=-0.38, p=0.001; r=0.34, p=0.002, respectively). The TC/HDL-C was positively correlated with cholesterol in sdLDL particles (r=0.698, p<0.0001) and HDL-C in sHDL particles (r=0.602, p<0.0001), and negatively correlated with cholesterol in small (r=-0.35, p=0.002), intermediate (r=-0.91, p<0.0001) and large (r=-0.84, p<0.0001) HDL particles, and HDL-C in the large HDL particles (r=-0.562, p<0.0001). No significant association was found between %10-year CVD risk and hsCRP. Collectively, these results corroborate that dyslipidemic Mexican-American adults have higher CVD risk than normolipidemic individuals. Hyperglycemia may further affect CVD risk by modulating cholesterol in LDL and HDL subfractions.