Establishment and validation of a predictive model for spontaneous preterm birth in singleton pregnant women

Abstract

Introduction: Screening for high sensitivity and specificity predictors of premature birth, establishing a sPTB prediction model that is suitable for women in China, easy to operate and popularize, and establishing an sPTB prediction scoring system for early, intuitive, and effective assessment of premature birth risk. Methods: 685 pregnant women with a single pregnancy during the second trimester (16-26 weeks) were divided into premature delivery and non-premature delivery groups based on their delivery outcomes. Clinical and ultrasound information was collected for both groups, and risk factors that could lead to sPTB in pregnant women were screened and analyzed using a cutoff value. A nomogram was developed to establish a prediction model and scoring system for sPTB. Additionally, 119 pregnant women who met the inclusion criteria for the modeling cohort were included for external validation of the model. The accuracy and consistency of the model were evaluated through the area under the ROC curve and the C-calibration curve. Results: The results of multivariate Logistic regression analysis showed that there was a significant correlation (P<0.05) between the number of miscarriages in pregnant women, history of miscarriages at the first week of pregnancy, history of preterm birth, CL of pregnant women, open and continuous cervical opening, and the occurrence of sPTB in pregnant women. Draw a Nomogram column chart based on the six risk factors mentioned above, obtain a predictive model for sPTB, and establish a scoring system to divide premature birth into three risk groups: low, medium, and high. Validate the model, and the Hosmer Lemeshow test indicates a good fit of the model (p=0.997); Modeling queue C calibration curve close to diagonal (C index=0.856), verifying that queue C calibration curve is also close to diagonal (C index=0.854); The AUC of the modeling queue is 0.850, and the AUC of the validation queue is 0.881. Conclusion: This study established a predictive model for sPTB, which is suitable for women in China, easy to operate and popularize. Risk assessment was conducted by assigning scores to each cutoff value, which can guide early, intuitive, and effective clinical assessment of premature birth risk in pregnant women.