OBJECTIVES: This study sought to examine the different prognostic effects of revascularization strategies according to the diabetes status from the randomized BEST (Randomized Comparison of Coronary Artery Bypass Surgery and Everolimus-Eluting Stent Implantation in the Treatment of Patients With Multivessel Coronary Artery Disease) trial.
METHODS: Patients (n = 880) with MVD were randomly assigned to undergo PCI with an everolimus-eluting stent vs CABG stratified by diabetics (n = 363) and nondiabetics (n = 517). The primary endpoint was the composite of death, myocardial infarction, or target vessel revascularization during a median follow-up of 11.8 years (IQR: 10.6-12.5 years).
RESULTS: In diabetics, the primary endpoint rate was significantly higher in the PCI group than in the CABG group (43% and 32%; HR: 1.53; 95% CI: 1.12-2.08; P = 0.008). However, in nondiabetics, no significant difference was found between the groups (PCI group, 29%; CABG group, 29%; HR: 0.97; 95% CI: 0.67-1.39; P = 0.86; Pinteraction= 0.009). Irrespective of the presence of diabetes, no significant between-group differences were found in the rate of a safety composite of death, myocardial infarction, or stroke and mortality rate. However, the rate of any repeat revascularization was significantly higher in the PCI group than in the CABG group.
CONCLUSIONS: In diabetics with MVD, CABG was associated with better clinical outcomes than PCI. However, the mortality rate was similar between PCI and CABG irrespective of diabetes status during an extended follow-up. (Ten-Year Outcomes of Randomized Comparison of Coronary Artery Bypass Surgery and Everolimus-Eluting Stent Implantation in the Treatment of Patients With Multivessel Coronary Artery Disease [BEST Extended], NCT05125367; Randomized Comparison of Coronary Artery Bypass Surgery and Everolimus-Eluting Stent Implantation in the Treatment of Patients With Multivessel Coronary Artery Disease [BEST], NCT00997828).
METHODS: Data for this study came from the four waves of the China Health and Retirement Longitudinal Survey. A latent growth model was used to analyze the functional disability of 5044 older adults aged 60 and over in 2011 who survived to 2018.
RESULTS: Pathologies are closely associated with functional disability trajectories, and higher numbers of comorbidities relate to more disabilities. Risk factors and intra- and extra-individual factors affect functional disability trajectories and work through independent and shared mechanisms. The effects of risk factors can be traced to childhood conditions, and higher childhood and adulthood socioeconomic status is related to fewer functional disabilities.
CONCLUSION: Functional disability trajectories are dynamic processes related to pathologies, intra-, and extra-individual factors, and life-course risk factors, and thus prevention and control measures should focus on both childhood and adulthood. Promoting working in later life and improving childhood socioeconomic status deserve prompt attention. Geriatr Gerontol Int 2023; 23: 817-829.
METHODS: In contrast, ViTs have demonstrated proficiency in capturing global signal patterns. In light of these observations, we propose a novel approach to enhance AD risk assessment. Our proposition involves a hybrid architecture, merging the strengths of CNNs and ViTs to compensate for their respective feature extraction limitations. Our proposed Dual-Branch Feature Fusion Network (DBN) leverages both CNN and ViT components to acquire texture features and global semantic information from EEG signals. These elements are pivotal in capturing dynamic electrical signal changes in the cerebral cortex. Additionally, we introduce Spatial Attention (SA) and Channel Attention (CA) blocks within the network architecture. These attention mechanisms bolster the model's capacity to discern abnormal EEG signal patterns from the amalgamated features. To make well-informed predictions, we employ a two-factor decision-making mechanism. Specifically, we conduct correlation analysis on predicted EEG signals from the same subject to establish consistency.
RESULTS: This is then combined with results from the Clinical Neuropsychological Scale (MMSE) assessment to comprehensively evaluate the subject's susceptibility to AD. Our experimental validation on the publicly available OpenNeuro database underscores the efficacy of our approach. Notably, our proposed method attains an impressive 80.23% classification accuracy in distinguishing between AD, Frontotemporal dementia (FTD), and Normal Control (NC) subjects.
DISCUSSION: This outcome outperforms prevailing state-of-the-art methodologies in EEG-based AD prediction. Furthermore, our methodology enables the visualization of salient regions within pathological images, providing invaluable insights for interpreting and analyzing AD predictions.