Epidemiology of uterine rupture among pregnant women in China and development of a risk prediction model: analysis of data from a multicentre, cross-sectional study

Abstract

Objectives: To describe the epidemiology of uterine rupture in China from 2015 to 2016 and to build a prediction model for uterine rupture in women with a scarred uterus.

Setting: A multicentre cross-sectional survey conducted in 96 hospitals across China in 2015-2016.

Participants: Our survey initially included 77 789 birth records from hospitals with 1000 or more deliveries per year. We excluded 2567 births less than 24 gestational weeks or unknown and 1042 births with unknown status of uterine rupture, leaving 74 180 births for the final analysis.

Primary and secondary outcome measures: Complete and incomplete uterine rupture and the risk factors, and a prediction model for uterine rupture in women with scarred uterus (assigned each birth a weight based on the sampling frame).

Results: The weighted incidence of uterine rupture was 0.18% (95% CI 0.05% to 0.23%) in our study population during 2015 and 2016. The weighted incidence of uterine rupture in women with scarred and intact uterus was 0.79% (95% CI 0.63% to 0.91%) and 0.05% (95% CI 0.02% to 0.13%), respectively. Younger or older maternal age, prepregnancy diabetes, overweight or obesity, complications during pregnancy (hypertensive disorders in pregnancy and gestational diabetes), low education, repeat caesarean section (≥2), multiple abortions (≥2), assisted reproductive technology, placenta previa, induce labour, fetal malpresentation, multiple pregnancy, anaemia, high parity and antepartum stillbirth were associated with an increased risk of uterine rupture. The prediction model including eight variables (OR >1.5) yielded an area under the curve (AUC) of 0.812 (95% CI 0.793 to 0.836) in predicting uterine rupture in women with scarred uterus with sensitivity and specificity of 77.2% and 69.8%, respectively.

Conclusions: The incidence of uterine rupture was 0.18% in this population in 2015-2016. The predictive model based on eight easily available variables had a moderate predictive value in predicting uterine rupture in women with scarred uterus. Strategies based on predictions may be considered to further reduce the burden of uterine rupture in China.

Keywords: epidemiology; maternal medicine; public health.