Objective To investigate the endometrial thickness and echo patterns of healthy women, so as to provide a basis for the formulation of a standard to define normal endometrium in Chinese women. Method A total of 1872 married healthy women in Yongchuan District received transvaginal ultrasound examination. The endometrial sonograph was observed and endometrial thickness was measured for statistical analyses. Results In pre-menopausal women of different age groups, the endometrial thickness was increased and the endometrial echo was enhanced from the proliferative phase, ovulatory phase and secretory phase. The endometrial thickness varied significantly among different menstrual cycles, while no significant difference was observed in the endometrial thickness of a same menstrual cycle among women of different age groups. Pre-menopausal women had significantly different endometrial thickness when compared with post-menopausal women. Conclusion Through a general survey of women by transvaginal ultrasound, a large sample database can be established, which may contribute to the formulation of a standard to define normal endometrium in Chinese women and to help identify abnormal endometrium.
Objective When making causal inferences in observational studies, in order to improve the robustness of the results of observational studies, statistical analysis techniques are often used to estimate the impact of unmeasured potential confounding factors. By systematically reviewing the application progress of the E-value, one of the sensitivity analysis methods, the advantages and limitations of using the E-value were discussed, to provide references for the application, reporting and interpretation of the E-value. Methods In the PubMed database, E-value was used as a keyword for title, abstract and key paper citation retrieval, and the literature that used the E-value analysis method for sensitivity analysis during 2016-2021 was screened. Results The E-value was widely used not only in cohort studies (n=215) and case-control studies (n=15), but also in cross-sectional studies (n=28), randomized controlled trials (n=6) and meta-analysis (n=16). The E-value was often combined with other sensitivity analysis methods, such as hierarchical analysis, instrumental variables, and multiple statistical regression models that correct different covariates, to further explore the reliability and robustness of the results. Conclusion When the E-value is used to evaluate the confounding factors in observational studies, the confidence interval and P value can be combined to evaluate the sensitivity of the results more comprehensively.