ObjectiveTo systematically review the non-inferiority trials in the cardiovascular domain that utilize medical devices as interventions, and investigate its characteristics and threshold settings. MethodsThe PubMed, Embase, and CENTRAL databases were electronically searched to collect non-inferiority trials in the cardiovascular field involving medical devices from inception to July 26, 2023. Two reviewers independently screened literature and extracted data. The reported information included basic characteristics, features of non-inferiority trials, and threshold-setting features of the included studies. Data analysis was performed using Excel 2020 and R 4.2.1 software. ResultsA total of 214 studies were included, with 167 studies (78.0%) focusing on interventions related to coronary artery stents. The trials predominantly utilized a two-arm design (92.9%), with a prevalent use of non-inferiority absolute thresholds (96.7%) as the criteria for non-inferiority determination. In 150 studies (70.1%), non-inferiority thresholds were established based on estimated control group effect values, while 33 studies (15.4%) did not report the source of these values. The non-inferiority trial endpoint outcomes exhibited diversity, and there were substantial differences in threshold settings. The three most studied qualitative indicators were target lesion failure rates (2.1%-8.6%), target vessel failure rates (2.5%-19.6%), and major adverse cardiovascular events rates (2.1%-10.0%). Late lumen loss (0.1-0.4 mm) emerged as the most frequently studied quantitative indicator. After converting absolute non-inferiority thresholds for all indicators into relative thresholds, the range was 1.20-3.67. ConclusionSignificant variations in non-inferiority threshold settings are observed for identical endpoint outcomes across included studies, highlighting a lack of reporting on the rationale behind threshold settings.
ObjectiveTo investigate the network structure of comorbid depression and anxiety symptoms among medical staff and analyze differences across institutional types. MethodsA convenience sampling method was used to select medical staff from medical institutions at various levels in Guang'an City as participants between August 10 and 15, 2024. General demographic questionnaires, the Chinese version of the Patient Health Questionnaire (PHQ-9) for depression screening, and the Chinese version of the Generalized Anxiety Disorder Scale (GAD-7) were used to survey them. The study aimed to analyze the influencing factors of anxiety and depression and construct a network model. Predictability, bridging strength, and node strength were used to assess the network structure. The non-parametric bootstrap method was employed to evaluate the accuracy and stability of the network, and finally, a Network Comparison Test (NCT) was used to examine the impact of different levels of healthcare institutions on the network model. ResultsA total of 889 participants were included in the study. The analysis showed that the incidence of depressive symptoms (PHQ-9≥5) among healthcare workers was 44.88%, while the incidence of anxiety symptoms (GAD-7≥5) was 43.98%, with a comorbidity rate of 36.67%. Network analysis revealed that the top three symptoms with the highest node strength were difficulty relaxing (A4), excessive worry (A3), and fatigue (D4). The top three symptoms with the highest bridging strength were irritability/anger (A6), fatigue (D4), and worrying about terrible things happening (A7). The different levels of healthcare institutions did not have a significant impact on the network model. ConclusionThe central symptoms (such as difficulty relaxing, excessive worry, and fatigue) and key bridging symptoms (such as irritability/anger, fatigue, and worrying about terrible things happening) in the anxiety and depression symptom network can serve as potential intervention targets for healthcare workers at risk of depressive and anxiety symptoms.