A nomogram to predict extremely preterm birth in women with singleton pregnancies undergoing cervical cerclage.

Objective: To develop a nomogram to predict preterm birth before 28 weeks in pregnant women undergoing cervical cerclage. Study design: We retrospectively studied the medical records on pregnant women who underwent cervical cerclage in January 2016 to September 2020. We developed the model from a development cohort in Women's Hospital, Zhejiang university, School of medicine, which randomly divided by 7:3 into training cohort for nomogram development, and internal validation cohort to confirm the model's performance. We then tested the nomogram in an external validation cohort over a similar period. The Harrell's C-index, calibration curve, decision curve analyses (DCA) were performed to assess the model. Results: 528 patients formed the development cohort, and 97 patients formed the external validation cohort. The model initially incorporated 10 baseline variables, while 5 variables were estimated in the nomogram at last: history of prior second-trimester loss, use of in-vitro fertilization (IVF), cervical dilation at cerclage, C-reactive protein (CRP) and platelet-lymphocyte ratio (PLR). The nomogram achieved good concordance indexes of 0.82(95%CI 0.77-0.88), 0.80(95%CI 0.72-0.88) and 0.79 (95%CI 0.68-0.90) in the training, internal and external validation cohort, respectively. And the nomogram had well-fitted calibration curves. Decision curve analysis demonstrated that the nomogram was clinically useful. Conclusions: The well-performed nomogram graphically represents the risk factors and a pre-operative predicted model in predicting the risk of preterm birth at <28 weeks in singleton pregnant women undergoing cervical cerclage. The model can provide a useful guide for clinicians and patients in making appropriate clinical decisions.