A Proposed Fetal Risk Scoring System for Gestational Diabetes to assist in optimizing Timing of Delivery

Abstract

Background: Gestational diabetes is characterized by three main factors: macrosomia, increased metabolic rate and large vascular cross sections. A critical and crucial finding in diabetic pregnancies is that significant acidaemia and hyperlacticemia can occur in fetuses in the absence of hypoxaemia. The increased metabolic rate results in significant increases in oxidative metabolism but this capacity is reduced in fetuses due to low pyruvate dehydrogenase activity increasing the risk for acidosis. This pathophysiology is not recognized by standard monitoring models which revolves around placental insufficiency which is in fact not the problem in a gestational diabetic pregnancy. A proposed risk scoring system has been developed based on our previous studies to risk categorise gestational diabetics in terms of fetal outcome.Methods: The diabetic cases from four case-control studies were combined to form a total sample of 159 cases for validation of the risk scoring system. Univariate logistic regression was used to assess the effect of individual risk factors with proposed cutoffs on adverse pregnancy outcome. The diagnostic accuracy of the total summative score, was assessed by computing the area under the ROC curve.Results: Four potential parameters were identified to risk- categorise fetuses in a gestational diabetic pregnancy ie the myocardial performance index (MPI), E/A ratio (marker of diastolic dysfunction), increasing fetal weight (macrosomia) and increased amniotic fluid index (AFI). The total score, obtained by summation of the composite scores for parameters ranged from 0 to 11. The total score performed as an excellent predictor of adverse outcome, evidenced by the ROC area under the curve of 0.94. A cutpoint of 6 on the score confers a sensitivity of 84.2% and specificity of 90.2% for detection of adverse outcome. Conclusion: To our knowledge this is the first Gestational Diabetic Scoring system proposed to predict an adverse outcome.