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Original Article

Nomogram to predict the risk of preterm birth before 37 weeks and 34 weeks in pregnant women with a short cervix

, , , , , & show all
Pages 4653-4662 | Received 07 Jun 2020, Accepted 04 Dec 2020, Published online: 15 Dec 2020
 

Abstract

Objectives

This study investigated the potential factors that predict the risk of preterm birth (PTB) in pregnancies with a short cervix. These factors were used to create nomogram, which might be highly sensitive tools to predict the incidence of PTB.

Methods

This retrospective cohort study enrolled pregnancies with a short cervix from 1 January 2017 to 1 January 2018. The primary outcomes were preterm birth <37 and 34 weeks. Logistic regression model was used to identify potential predictors of PTB. The identified risk factors were used to establish nomograms, which were validated using the receiver operating characteristic (ROC) curve and calibration curve.

Results

In the multivariate analysis, overweight or obesity, parity ≧3 times, twin pregnancy, in vitro fertilization and embryo transfer (IVF-ET), gestational age at first observation of short cervix, cervical length (CL) at first observation of short cervix, history of PTB, and autoimmune disease were found to be predictors of PTB <37 weeks, while twin pregnancy, gestational age at first observation of short cervix, CL of short cervix, history of PTB, and prepregnancy hypertension were predictors of PTB <34 weeks. The area under the ROC curve of the nomogram predicting PTB <37 weeks and PTB <34 weeks were 0.803 and 0.771, respectively. Both models showed good discrimination

Conclusions

Gestational age at first observation of short cervix, CL of short cervix and other factors are strong predictors of PTB in pregnancies with a short cervix. Both nomograms showed good discrimination and calibration, and hence might be effective in predicting PTB for this population.

Acknowledgments

The authors thank Liu Luo for assistance in data management and programming.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was supported by the Major Program of the National Natural Science Foundation of China [Grant No. 81490745] and the State Key Development Program for Basic Research of China [Grant No.2015CB943304], both to HY.

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