Prediction of preterm delivery based on thyroid peroxidase antibody levels and other identified risk factors

Abstract

ObjectiveThyroid dysfunction and TPOAb positivity during pregnancy are associated with adverse pregnancy outcomes such as preterm delivery. The aim of this study was to predict preterm delivery based on identified risk factors, especially TPOAb levels. Study designA secondary analysis was run on data collected in the Tehran Thyroid and Pregnancy study (TTPs). We used the data of 1515 pregnant women with singletons. The association between risk factors and preterm birth (delivery before 37 completed weeks of gestation) was investigated in univariate analysis. Multivariate logistic regression analysis was performed to identify independent risk factors, and a stepwise backward elimination method was used to determine the helpful combination of risk factors. The nomogram was developed based on a multivariate logistic regression model. The performance of the nomogram was evaluated using a concordance index and calibration plots with bootstrap samples. Statistical analysis was performed using STATA software package; the significance level was set at P < 0.05. ResultsBased on multivariate logistic regression analysis, a combination of previous preterm delivery [OR: 5.25; 95 %CI: (2.13–12.90), p < 0.01], TPOAb [OR: 1.01; 95 %CI: (1.01–1.02), and T4 [OR: 0.90; 95 %CI: (0.83–0.97); p = 0.04] as independent risk factors that most precisely predicted preterm birth. The area under the curve (AUC) was 0.66 (95% CI: 0.61–0.72). The calibration plot suggests that the fit of the nomogram is reasonable. ConclusionA combination of T4, TPOAb, and previous preterm delivery was identified as independent risk factors that accurately predicted preterm delivery. The total score obtained based on the nomogram designed based on risk factors can predict the risk of preterm delivery.