A risk-prediction nomogram for patients with second-trimester threatened miscarriage associated with adverse outcomes
Background: Both ultrasound, demographic, biochemical and laboratory markers alone have been analyzed in the previous literatures for the prediction of miscarriage; however, these independent factors have not yet been integrated for analysis. Thus, we performed this analysis to determine the best combination markers to establish a nomogram prediction model for patients presenting with second-trimester threatened miscarriage and verify its validity prospectively.
Methods: We retrospectively collected information from the patients hospitalized with second-trimester threatened miscarriage and used the logistic regression analyzes to determine the most significant predictive factors associated with miscarriage. While the individualized risk-prediction nomogram model was established based on the predictors’ regression coefficients. The area under the receiver operating characteristic curves and the Hosmer-Lemeshow test were utilized to verify the discrimination and calibration of the prediction model, respectively.
Results: This study demonstrates that gestational weeks, C-reactive protein, vaginal blood loss, premature rupture of membranes, and uterine adenomyosis or adenomyoma were the most significant independent risk factors of the second-trimester threatened miscarriage associated with adverse outcomes.
Conclusions: We can estimate the possibility of second-trimester miscarriage through the nomogram prediction model which has good recognition and calibration.
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Posted 20 Nov, 2020
A risk-prediction nomogram for patients with second-trimester threatened miscarriage associated with adverse outcomes
Posted 20 Nov, 2020
Background: Both ultrasound, demographic, biochemical and laboratory markers alone have been analyzed in the previous literatures for the prediction of miscarriage; however, these independent factors have not yet been integrated for analysis. Thus, we performed this analysis to determine the best combination markers to establish a nomogram prediction model for patients presenting with second-trimester threatened miscarriage and verify its validity prospectively.
Methods: We retrospectively collected information from the patients hospitalized with second-trimester threatened miscarriage and used the logistic regression analyzes to determine the most significant predictive factors associated with miscarriage. While the individualized risk-prediction nomogram model was established based on the predictors’ regression coefficients. The area under the receiver operating characteristic curves and the Hosmer-Lemeshow test were utilized to verify the discrimination and calibration of the prediction model, respectively.
Results: This study demonstrates that gestational weeks, C-reactive protein, vaginal blood loss, premature rupture of membranes, and uterine adenomyosis or adenomyoma were the most significant independent risk factors of the second-trimester threatened miscarriage associated with adverse outcomes.
Conclusions: We can estimate the possibility of second-trimester miscarriage through the nomogram prediction model which has good recognition and calibration.
Figure 1
Figure 2
Figure 3