Brit J Hosp Med
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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 Lobar pneumonia is an acute inflammation with increasing incidence globally. Delayed treatment can lead to severe complications, posing life-threatening risks. Thus, it is crucial to determine effective treatment methods to improve the prognosis of children with lobar pneumonia. ⋯ However, 7 days after treatment, the CD3+, CD4+, and CD4+/CD8+ levels increased significantly in the observation group compared to the control group (p < 0.001). Additionally, there was no significant difference in the incidence of adverse reactions in both groups (p > 0.05). Conclusion Pidotimod-assisted erythromycin treatment can significantly improve the treatment efficiency in children with lobar pneumonia, improving clinical signs and symptoms and enhancing the cellular immune function without increasing the risk of adverse drug reactions.
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Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are emerging as an important class of drugs in the management of Type 2 Diabetes Mellitus (T2DM) and obesity. There are rising concerns of pulmonary aspiration with these medications due to drug-induced gastroparesis. While definitive association is uncertain, it is essential to be prudent and manage these patients as per the current evidence and recommendations.
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Editorial
Finerenone: Do We Really Need an Additional Therapy in Type 2 Diabetes Mellitus and Kidney Disease?
Patients with chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM) face considerable cardiorenal morbidity and mortality despite existing therapies. Recent clinical trials demonstrate the efficacy of finerenone, a novel non-steroidal mineralocorticoid receptor antagonist, in reducing adverse renal and cardiovascular outcomes. This editorial briefly reviews the evidence and its implications for clinical practice, advocating the use of finerenone in these high-risk patients in combination with currently established treatment agents.
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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.