Objective To investigate the correlation between epicardial fat thickness and non dipper hypertension.Methods A total of 150 subjects was included in the study,of which 50 were in the non dipper hypertension group,the same in the non dipper hypertension group and the healthy control group.History collection and routine laboratory tests,ultrasonic measurement of epicardial fat thickness,and 24 hour ambulatory blood pressure monitoring were carried on all subjects.Epicardial fat thickness between groups was compared to primarily analyze the correlation of epicardial fat thickness and non dipper type hypertension.The optimal screening positive value in epicardial fat thickness of non dipper type primary hypertension was obtained by receiver operating characteristic (ROC) curve and maximum Youden index.Results When non dipper hypertension group and non-dipper hypertension group were compared,epicardial fat thickness was significantly increased [(6.30 ± 0.94) mm vs (5.92 ± 0.75) mm,P ＜ 0.05],as compared dipper hypertension group to healthy group,the epicardial fat thickness was significantly increased [(5.92 ±0.75)mm vs (5.50 ±0.13)mm,P ＜0.05].Epicardial fat thickness and non dipper type primary hypertension were linearly related (r =0.43,P ＜ 0.05),and epicardial fat thickness in diagnosis of non dippers primary hypertension optimal screening positive value was 6.01 mm.Conclusions There is a close relationship of epicardial fat thickness and non dipper hypertension.

[Objective] To observe the effect of computer-aided detection (CAD) system in improving lung nodule detection sensitivity and inter-observer variation.[Methods] 300 PA digital radiographs including 100 normal cases and 200 cases with pulmonary nodules confirmed by CT were enrolled.Two senior chest radiologists referenced CT images and marked the sizes and locations of all nodules with consensus as the gold standards.Four senior radiologists and four junior radiologists interpreted the digital chest radiographs independently without and with CADand recordtheir results.Pair t test and coefficient of variation (CV) was used to compare the difference of lung nodule detection sensitivity and inter-observer variation between withoutand with CAD.[Results] The mean lung nodule detection sensitivity of senior and junior radiologists withoutand with CAD were (41.1 ± 2.0)％,(28.0 ± 2.0)％ and (45.0 ± 1.8)％,(39.2 ± 0.9)％,respectively,statistical analysis showed there was statistically significant difference.Moreover,CV of all radiologists without and with CAD were 20.9％ and 8.1％.[Conclusion] Both lung nodule detection sensitivity and inter-observer variation of senior and junior radiologists can be improved by CAD.

This article introduces the contents of the latest edition Risk of Bias in Non-randomized Studies-of Exposure (ROBINS-E) published in June 2022 [ROBINS-E (2022)], and gives some examples about its usage. ROBINS-E is a tool for assessing the risk of bias in non-randomized studies-of exposure. Compared with ROBINS-E (2019), ROBINS-E (2022) adds more bias for observational studies, covers a more comprehensive range of bias, and adds the assessment of the external authenticity of the study. ROBINS-E (2022) adds a preliminary evaluation process to improve the efficiency of evaluation. In addition, ROBINS-E (2022) visualizes and instrumentalizes the use of signal problems in the form of path graph, making it more convenient to use. ROBINS-E (2022), although more consideration has been given to the issue of co-exposure, still does not address the problem of effect modification in co-exposure, and there is still room to expand the applicable research.