Developing and validating a predictive model of delivering large-for-gestational-age infants among women with gestational diabetes mellitus

Figure 1 Flowchart of the study population selection and data availability. GDM: Gestational diabetes mellitus; LASSO: Least Absolute Shrinkage and Selection Operator.

Figure 2 The potential predictors selected by the Least Absolute Shrinkage and Selection Operator regression analysis model. A: Regression coefficient path diagram; B: Cross verification curve.

Figure 3 Results of the multivariable logistic regression analysis of delivering an large-for-gestational-age infant in pregnant women with gestational diabetes mellitus. WGW: Weight gain during pregnancy measured at the 24^th week; TyG: Triglyceride-glucose index; FT4: Free tetraiodothyronine; AC: Abdominal circumference; ALT: Alanine transaminase; AST: Aspartate aminotransferase.

Figure 4 Nomogram for predicting large-for-gestational-age infant in pregnant women with gestational diabetes mellitus. WGW: Weight gain during pregnancy at 24 gestational weeks; TyG: Triglyceride-glucose index; FT4: Free tetraiodothyronine; AC: Abdominal circumference; ALT: Alanine transaminase; AST: Aspartate aminotransferase.

Figure 5 The receiver operating characteristic curve and area under the receiver operating characteristic curve for the prediction of large-for-gestational-age in women with gestational diabetes mellitus. A: Training cohort; B: Validation cohort; C: Test cohort.

Figure 6 Calibration curve for the prediction of large-for-gestational-age in women with gestational diabetes mellitus. A: Training cohort; B: Validation cohort; C: Test cohort.

Figure 7 Decision curve analysis for predicting large-for-gestational-age in women with gestational diabetes mellitus. A: Training cohort; B: Validation cohort; C: Test cohort.