Estimating the individual singleton preterm birth risk: nomogram establishment and independent validation

Area of Science:

• Reproductive Health
• Maternal-Fetal Medicine
• Biostatistics

Background:

• Preterm birth (PTB) remains a significant global health challenge.
• Accurate prediction of PTB risk is crucial for timely intervention.
• Existing prediction models may lack generalizability across diverse populations.

Purpose of the Study:

• To develop and validate robust nomograms for predicting singleton preterm birth (PTB) risk.
• To provide clinicians with tools for individualized PTB risk assessment.
• To improve early identification and management of PTB.

Main Methods:

• A large-scale cohort study utilizing the National Vital Statistics System (NVSS) database (2016-2020).
• Multivariate logistic regression analysis to identify independent PTB risk factors.
• Development of PTB prediction nomograms using US data and validation with US Territories data.

Main Results:

• Four nomograms were constructed to predict overall PTB, moderate/late PTB, very PTB, and extremely PTB.
• The training set included over 16 million mother-newborn pairs; the validation set comprised over 54,000 pairs.
• Hypertensive eclampsia and infertility treatment emerged as the leading contributors to PTB risk.

Conclusions:

• Validated nomograms offer a reliable method for predicting individualized PTB probability.
• These tools can aid physicians in early PTB identification and personalized clinical decision-making.
• The developed nomograms have the potential to enhance obstetric care and improve neonatal outcomes.