Brit J Hosp Med
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Aims/Background Diabetes is a chronic lifelong condition that requires consistent self-care and daily lifestyle adjustments. Effective disease management involves regular blood glucose monitoring and ongoing nursing support. Inadequate education and poor self-management are key factors contributing to increased mortality among diabetic individuals. ⋯ Fasting plasma glucose (FPG) levels were also significantly reduced in the intervention group compared to baseline and the control group (p < 0.05). 3 months post-intervention, the intervention group demonstrated significantly higher adherence rates to dietary recommendations, healthy lifestyle practices, and treatment compliance compared to the control group (p < 0.05). Conclusion The "Internet+"-based Omaha System continuous nursing model significantly enhances self-health management capabilities, stabilizes glycemic control, and promotes adherence to healthy behaviors among patients with T2DM. These findings highlight the potential of the model for broader clinical application in diabetes management.
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Aims/Background Artificial intelligence (AI), with advantages such as automatic feature extraction and high data processing capacity and being unaffected by fatigue, can accurately analyze images obtained from colonoscopy, assess the quality of bowel preparation, and reduce the subjectivity of the operating physician, which may help to achieve standardization and normalization of colonoscopy. In this study, we aimed to explore the value of using an AI-driven intestinal image recognition model to evaluate intestinal preparation before colonoscopy. Methods In this retrospective analysis, we analyzed the clinical data of 98 patients who underwent colonoscopy in Nantong First People's Hospital from May 2023 to October 2023. ⋯ The incidence of adverse reactions in the AI group (3.92%) was lower than that in the Regular group (10.64%), but the difference was not statistically significant (p > 0.05). The satisfaction rate of intestinal preparation in the AI group (96.08%) was comparable to that of the Regular group (82.98%) (p > 0.05). Conclusion Compared with the assessment based solely on the intestinal preparation map and the last fecal characteristics, the application of AI intestinal image recognition model in intestinal preparation before colonoscopy can shorten the time of colonoscopy and improve intestinal cleanliness, but with comparable patient satisfaction and safety.
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Aims/Background Hypertension (HT) is a prevalent medical condition showing an increasing incidence rate in various populations over recent years. Long-term hypertension increases the risk of the occurrence of hypertensive nephropathy (HTN), which is also a health-threatening disorder. Given that very little is known about the pathogenesis of HTN, this study was designed to identify disease biomarkers, which enable early diagnosis of the disease, through the utilization of high-throughput untargeted metabolomics strategies. ⋯ LASSO regression analysis results indicated that 4-hydroxyphenylacetic acid, bilirubin, uracil, and iminodiacetic acid are potential biomarkers for HTN or HT. Conclusion With untargeted metabolomics analysis, we successfully identified differential metabolites in HTN. A further LASSO regression analysis revealed that four key metabolites, namely 4-hydroxyphenylacetic acid, bilirubin, uracil, and iminodiacetic acid, hold promise for the diagnosis of early-stage HTN.
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Aims/Background Research evidence has demonstrated a significant association between hypertrophic cardiomyopathy (HCM) and atrial fibrillation (AF), but the causality and pattern of this link remain unexplored. Therefore, this study investigated the causal relationship between HCM and AF using a two-sample and bidirectional Mendelian randomization (MR) approach. Additionally, this assessed the role of cardiovascular proteins (CPs) associated with cardiovascular diseases between HCM and AF by applying a two-step MR analysis. ⋯ Moreover, Two-step MR analyses indicated that 5 CPs were causally associated with HCM; 12 CPs with AF and 1 CP (Melusin) with both HCM and AF. Additionally, Melusin was observed as a protective factor for both HCM and AF and may serve as a mediator variable for these two conditions (mediation effect 0.0004, mediation ratio 5.5178%, 95% CI: 5.4624-5.5731). Conclusion HCM may increase the risk of developing AF, with Melusin serving as a mediator for this risk.
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Aims/Background Epidemiological studies indicate that the involvement of the immune system in the pathogenesis of infections associated with chronic obstructive pulmonary disease (COPD), asthma, and interstitial lung disease (ILD) remains unclear. This study aims to assess the potential causal link between infections associated with COPD, asthma, or ILD and immune system function. Methods We conducted a two-sample Mendelian randomization analysis using publicly available genome-wide association study (GWAS) datasets. ⋯ The causal effect of COPD/asthma/ILD-related infections on Immunoglobulin D (IgD) expression in IgD+ CD38br and transitional B cells was estimated to be 0.64 (95% CI: 0.49-0.83, p = 0.00091) and 0.70 (95% CI: 0.54-0.91, p = 0.00727), respectively. Additionally, COPD/asthma/ILD-related infections demonstrated a significant causal effect on several B cell and T cell subpopulations: IgD+ CD38- % B cells, IgD+ CD38- AC, CD4+ CD8dim AC, IgD+ CD38- % lymphocyte, and TD CD4+ AC, with the OR 1.54 (95% CI: 1.19-2.00, p = 0.00113), 1.56 (95% CI: 1.16-2.10, p = 0.00340), 1.60 (95% CI: 1.15-2.22, p = 0.00478), 1.47 (95% CI: 1.12-1.92, p = 0.00483) and 1.63 (95% CI: 1.14-2.34, p = 0.00725), respectively. Conclusion Our study reveals a causal association between altered circulating blood cell counts and specific immunophenotypes with the susceptibility to respiratory infections related to COPD, asthma, and ILD.