Ectopic pregnancy in China during 2011-2020: a single-centre retrospective study of 9499 cases.

BACKGROUND: Previous studies have shown that the incidence of ectopic pregnancy (EP) is increasing in China. It is unclear, however, whether the incidence of EP has changed after the implementation of the universal two-child policy in the context of China's aging population and declining fertility rate. METHODS: Data concerning EP from January 2011 to December 2020 were collected from the hospital's electronic medical records, which included the annual number of delivery, caesarean section rate, ectopic pregnancies, treatment of tubal pregnancy, and average costs and length of hospitalization. Trends of the EP incidence were analysed and annual percentage change (APC) was calculated using connected point regression analyses. RESULTS: A total of 9499 cases of EP were collected, among which caesarean scar pregnancy (CSP) accounts for the second highest (6.73%). The EP per 100 deliveries revealed a downward trend, from 7.60% in 2011 to 4.28% in 2020 with an APC of -1.87 (P < 0.05). The maternal age was increased, especially after the implementation of the universal two-child policy. The constituent ratio for the advanced maternal age (≥ 35) and the caesarean section rate, but not the CSP, were also increased. Laparoscopic salpingectomy was the main surgical method, whereas the adoption of laparotomy and laparoscopic salpingostomy was decreasing year by year. CONCLUSIONS: Although no obvious effect of the two-child policy on EP has been observed under the conditions of this study, the change in EP especially in advanced-age women after the policy implementation needs further evaluation. A decreased caesarean section rate, in primipara is beneficial to reducing the CSP.

Establishment of a nomogram model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia.

AIM: To establish a model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia in China. METHODS: We retrospectively collected the medical records of 896 pregnant women with preterm preeclampsia who were older than 35 years and delivered at the Affiliated Hospital of Qingdao University from June 2018 to December 2020. The pregnant women were divided into an adverse outcome group and a non-adverse outcome group according to the occurrence of adverse outcomes. The data were divided into a training set and a verification set at a ratio of 8:2. A nomogram model was developed according to a binary logistic regression model created to predict the adverse outcomes in advanced-age pregnant women with preterm preeclampsia. ROC curves and their AUCs were used to evaluate the predictive ability of the model. The model was internally verified by using 1000 bootstrap samples, and a calibration diagram was drawn. RESULTS: Binary logistic regression analysis showed that platelet count (PLT), uric acid (UA), blood urea nitrogen (BUN), prothrombin time (PT), and lactate dehydrogenase (LDH) were the factors that independently influenced adverse outcomes (P < 0.05). The AUCs of the internal and external verification of the model were 0.788 (95% CI: 0.737 ~ 0.764) and 0.742 (95% CI: 0.565 ~ 0.847), respectively. The calibration curve was close to the diagonal. CONCLUSIONS: The model we constructed can accurately predict the risk of adverse outcomes of pregnant women of advanced age with preterm preeclampsia, providing corresponding guidance and serving as a basis for preventing adverse outcomes and improving clinical treatment and maternal and infant prognosis.