This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research article
Qian Chen
Peking University First Hospital
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
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.
Keywords
miscarriage, nomogram, second-trimester threatened miscarriage
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research article
Qian Chen
Peking University First Hospital
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 20 Nov, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
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
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