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ORIGINAL RESEARCH

Development, Validation and Clinical Utility of a Risk Prediction Model for Maternal and Neonatal Adverse Outcomes in Pregnant Women with Hypothyroidism

, , , &
Pages 1953-1969 | Received 03 Jan 2024, Accepted 02 Apr 2024, Published online: 01 May 2024

Figures & data

Figure 1 Flowchart of patient selection.

Figure 1 Flowchart of patient selection.

Table 1 Comparison of General Clinical Data of the Mother and Neonatal During a Pregnancy Complicated by Hypothyroidism

Table 2 Comparison of Variable Characteristics of Maternal Adverse Outcomes

Table 3 Comparison of Variable Characteristics of Neonatal with or Without Adverse Outcomes

Table 4 Logistic Regression Model for Adverse Maternal Outcomes

Table 5 Logistic Regression Model for Adverse Neonatal Outcomes

Figure 2 Nomogram of adverse maternal outcomes.

Figure 2 Nomogram of adverse maternal outcomes.

Figure 3 Nomogram of adverse neonatal outcomes.

Figure 3 Nomogram of adverse neonatal outcomes.

Table 6 Discrimination and Calibration of Predictive Models for Adverse Maternal Outcomes

Table 7 Discrimination and Calibration of Prediction Models for Adverse Neonatal Outcomes

Figure 4 ROC curve of logistic regression model for adverse outcomes. (A) Training set-adverse maternal outcomes; (B) Validation set-adverse maternal outcome; (C) Training set-neonatal adverse outcomes; (D) Validation set-neonatal adverse outcome.

Abbreviations: Pro_LR_preg, Logistic regression model for adverse maternal outcomes with all variables included; Pro_LR_preg_sel, Logistic regression model for adverse maternal outcomes including variables with p <0.05; Pro_LR_newb; Logistic regression model for adverse neonatal outcomes with all variables included; Pro_LR_newb_sel, Logistic regression model for adverse neonatal outcomes including p <0.05 variables.
Figure 4 ROC curve of logistic regression model for adverse outcomes. (A) Training set-adverse maternal outcomes; (B) Validation set-adverse maternal outcome; (C) Training set-neonatal adverse outcomes; (D) Validation set-neonatal adverse outcome.

Figure 5 Calibration curve for logistic regression model for adverse outcomes. (A) Training set-adverse maternal outcomes; (B) Validation set-adverse maternal outcome; (C) Training set-neonatal adverse outcomes; (D) Validation set-neonatal adverse outcome.

Abbreviations: Pro_LR_preg, Logistic regression model for adverse maternal outcomes with all variables included; Pro_LR_preg_sel, Logistic regression model for adverse maternal outcomes including variables with p <0.05; Pro_LR_newb, Logistic regression model for adverse neonatal outcomes with all variables included; Pro_LR_newb_sel, Logistic regression model for adverse neonatal outcomes including p <0.05 variables.
Figure 5 Calibration curve for logistic regression model for adverse outcomes. (A) Training set-adverse maternal outcomes; (B) Validation set-adverse maternal outcome; (C) Training set-neonatal adverse outcomes; (D) Validation set-neonatal adverse outcome.

Figure 6 DCA curve from logistic regression model for adverse outcomes. (A) Training set-adverse maternal outcomes; (B) Validation set-adverse maternal outcome; (C) Training set-neonatal adverse outcomes; (D) Validation set-neonatal adverse outcome.

Abbreviations: Pro_LR_preg, Logistic regression model for adverse maternal outcomes with all variables included; Pro_LR_preg_sel, Logistic regression model for adverse maternal outcomes, including variables with p <0.05; Pro_LR_newborn, Logistic regression model for adverse neonatal outcomes with all variables included; Pro_LR_newborn selection, Logistic regression model for adverse neonatal outcomes including p <0.05 variables.
Figure 6 DCA curve from logistic regression model for adverse outcomes. (A) Training set-adverse maternal outcomes; (B) Validation set-adverse maternal outcome; (C) Training set-neonatal adverse outcomes; (D) Validation set-neonatal adverse outcome.