Epidemiological and Histopathological Characteristics of Fetuses with Congenital Disorders: A Study in Greece

Abstract

Congenital malformations constitute a major public health issue. Nonetheless, Greece does not participate in the European network of congenital anomalies. To examine the epidemiology of congenital abnormalities and investigate possible factors associated with their development, autopsies were performed on 649 fetuses referred from three healthcare facilities in Thessaloniki during 1992-2008. Adequate statistical analysis methods were implemented. Birth defects were found in 256 fetuses (39.5%)-primarily related to the musculoskeletal (17.3%), nervous (14.5%), cardiovascular (12.5%) and urinary (10.4%) systems. A statistically significant positive correlation (p-values < 0.05) emerged between the presence of a congenital defect and intrauterine growth restriction, inability to identify the fetus' sex, iatrogenic abortion, nuchal oedema and a single umbilical artery. An inverse association (p-values < 0.05) was deduced with the gestational age, twin pregnancy, stillbirth, chorioamnionitis, infarction and intervillous thrombus of the placenta and nuchal cord. In multivariable analysis, the relationship remained significant (p-values < 0.05) between the development of birth defects and iatrogenic abortion, nuchal oedema, presence of a single umbilical artery, chorioamnionitis, infarction of the placenta and nuchal cord. ROC curve analysis indicated area under the curve = 0.800, 95% confidence interval = 0.76-0.84, p-value = 0.000. Our study revealed the epidemiology of congenital anomalies in Greece, confirming the relationship between various factors and birth defect occurrence.

Keywords: Greece; congenital disorders; cross-sectional study; epidemiology; risk factors.

Figure 1

Congenital disorders by organ system/type of anomaly [number of fetuses with the identified anomaly (percentage % of all the recorded anomalies)].

Figure 2

Independent predictors of congenital disorder development—univariable logistic regression analysis.

Figure 3

Independent predictors of congenital disorder development—multivariable logistic regression analysis.

Figure 4

Receiver operating characteristic (ROC) curve analysis on the predictive ability of the created multivariable model. The diagonal green line (sensitivity = 1 − specificity) represents the line of no discrimination, indicating the performance of a classifier that makes random predictions.