A nomogram based on fetal cardiac function parameters (LMPI, LKI, and RIRT) demonstrated excellent discrimination for predicting composite adverse perinatal outcomes in GDM (AUC 0.960; 95% CI 0.924-0.996).
Case-Control (n=378)
Does well-controlled gestational diabetes mellitus alter fetal cardiac function assessed by HOLO-PW ultrasound, and can these parameters predict adverse perinatal outcomes?
Even under well-controlled glycemic conditions, fetal cardiac function is altered in GDM pregnancies, and novel ultrasound parameters can accurately predict adverse perinatal outcomes.
Effect estimate: AUC 0.960 (95% CI 0.924-0.996)
OBJECTIVES: To investigate the changes in fetal cardiac function in pregnant women with well-controlled gestational diabetes mellitus (GDM) using a novel ultrasound technology named HOLO-PW. Secondly, we aim to evaluate the predictive ability of cardiac function parameters for adverse perinatal outcomes and establish an individualized nomogram. METHODS: This study included 122 pregnant women with well-controlled GDM and 256 pregnant women with normal blood glucose. Fetal cardiac function parameters were extracted based on the HOLO-PW technology. The differences between the 2 groups were analyzed. Subgroup analysis was performed in the GDM group according to the pregnancy outcome and fetal growth status. The effectiveness of cardiac function parameters in predicting adverse pregnancy outcomes in GDM was evaluated by receiver operating characteristic (ROC) curves. Independent predictors were identified through logistic regression with LASSO variable selection, and a nomogram was developed. The model's performance was evaluated with ROC analysis, calibration curves, and decision curve analysis (DCA). RESULTS: Compared with the control cohort, the myocardial performance index (MPI), K index (KI), isovolumic contraction time (ICT), and isovolumic relaxation time (IRT) of left and right ventricles were increased in the fetuses of GDM cohort (p < .05). Compared with the appropriate for gestational age (AGA), the fetuses with abnormal growth in the GDM cohort presented significant differences in the cardiac function parameters (p < .05). The incidence of adverse pregnancy outcomes in the GDM cohort was higher than that in the control cohort. The cardiac function parameters of fetuses with adverse and normal perinatal outcomes significantly differed in the GDM cohort (p < .05). We also evaluated the predictive capacity of each heart function parameter for adverse pregnancy outcomes in GDM. The LMPI showed the strongest ability to predict adverse pregnancy outcomes with an AUC of 0.951 (95% CI: 0.909-0.993). A nomogram constructed with the 3 key predictors selected by LASSO regression (LMPI, LKI, and RIRT) demonstrated excellent discrimination, with an AUC of 0.960 (95% CI: 0.924-0.996). The model was well calibrated, and DCA indicated clinical utility. CONCLUSION: Even under well-controlled glycemic conditions, fetal cardiac function is altered in GDM pregnancies. In this cohort, a model based on fetal cardiac function parameters showed good predictive performance for composite adverse perinatal outcomes. However, external validation is required before clinical implementation.
Yi et al. (Fri,) conducted a case-control in Gestational diabetes mellitus (n=378). Well-controlled gestational diabetes mellitus vs. Normal blood glucose was evaluated on Adverse pregnancy outcomes (AUC 0.960, 95% CI 0.924-0.996). A nomogram based on fetal cardiac function parameters (LMPI, LKI, and RIRT) demonstrated excellent discrimination for predicting composite adverse perinatal outcomes in GDM (AUC 0.960; 95% CI 0.924-0.996).