Large language models (LLMs) are rapidly advancing medical artificial intelligence, offering revolutionary changes in health care. These models excel in natural language processing (NLP), enhancing clinical support, diagnosis, treatment, and medical research. Breakthroughs, like GPT-4 and BERT (Bidirectional Encoder Representations from Transformer), demonstrate LLMs’ evolution through improved computing power and data. However, their high hardware requirements are being addressed through technological advancements. LLMs are unique in processing multimodal data, thereby improving emergency, elder care, and digital medical procedures. Challenges include ensuring their empirical reliability, addressing ethical and societal implications, especially data privacy, and mitigating biases while maintaining privacy and accountability. The paper emphasizes the need for human-centric, bias-free LLMs for personalized medicine and advocates for equitable development and access. LLMs hold promise for transformative impacts in health care.

This study aimed to investigate the relationship between the TyG (Triglyceride-glucose index) and the prognosis of patients with HOCM (hypertrophic obstructive cardiomyopathy) without diabetes. A total of 713 eligible patients with HOCM were enrolled in this study and divided into two groups based on treatment: an invasive treatment group (n = 461) and a non-invasive treatment group (n = 252). The patients in both two groups were then divided into three groups based on their TyG index levels. The primary endpoints of this study were Cardiogenic death during long-term follow-up. Kaplan–Meier analysis was used to study the cumulative survival of different groups. Restricted cubic spline was used to model nonlinear relationships between the TyG index and primary endpoints. Myocardial perfusion imaging/Myocardial metabolic imaging examinations were performed to assess glucose metabolism in the ventricular septum of the HOCM patients. The follow-up time of this study was 41.47 ± 17.63 months. The results showed that patients with higher TyG index levels had better clinical outcomes (HR, 0.215; 95% CI 0.051,0.902; P = 0.036, invasive treatment group; HR, 0.179; 95% CI 0.063,0.508; P = 0.001, non-invasive treatment group). Further analysis showed that glucose metabolism in the ventricular septum was enhanced in HOCM patients. The findings of this study suggest that the TyG index may serve as a potential protective factor for patients with HOCM without diabetes. The enhanced glucose metabolism in the ventricular septum of HOCM patients may provide a potential explanation for the relationship between the TyG index and HOCM prognosis.

Background: It remains uncertain whether a novel composite indicator, the high sensitivity C‐reactive protein (CRP) (hsCRP)‐to‐body mass index (BMI) ratio (CBR), is associated with unfavourable events in subjects who have undergone drug‐eluting stent (DES) implantation. Therefore, we conducted a prospective cohort study to evaluate the associations between the CBR and adverse outcome occurrences. Methods: From January 2013 to December 2013, a total of 9810 subjects who underwent DES implantation were enrolled in the study. The participants were divided into three groups on the basis of the CBR. We defined the primary endpoint as the occurrence of major adverse cardiovascular and cerebrovascular events (MACCEs), and the secondary endpoints included the occurrence of all‐cause death, myocardial infarction(MI), stroke or target vessel revascularization (TVR). Kaplan‒Meier (K‒M) analysis and Cox regression analysis were performed to assess the discrepancy in the risk of adverse outcomes between the different CBR groups. Results: Over an average follow‐up period of 26.7 months, 1022 MACCEs were recorded, which included 122 deaths, 392 MIs, 156 strokes and 461 instances of TVR. The results from the K‒M analysis suggested that the rates of MACCEs and MI increased with increasing tertiles of the CBR. Furthermore, Cox regression analysis demonstrated that there were significant associations between a high CBR and increased MACCE and MI risk. Conclusion: In subjects who underwent DES implantation, a higher CBR was significantly related to increased long‐term MACCE and MI risk.

Background: G1, a specific agonist targeting the G protein–coupled receptor 30 (GPR30), has demonstrated significant involvement in combating obesity and regulating glucose homeostasis. Nevertheless, the beneficial effects of G1 treatment have solely been investigated in animal models under normal feeding conditions, leaving its therapeutic potential in high‐fat feeding scenarios unexplored.Material and Methods: To address this gap, our study employed an ovariectomized high‐fat diet mouse model to assess the therapeutic effects of G1 in combating obesity and metabolic dysfunction.Results: The findings revealed that G1 treatment resulted in weight loss, but concurrently led to increased blood glucose levels and insulin resistance. Treatment with G1 resulted in an amplification of fat mobilization and an enhancement of pyruvate carboxylase activity in mice fed a high‐fat diet. Moreover, the combined impact of G1 treatment and a high‐fat diet on pyruvate metabolism, as well as the regulation of crucial gluconeogenesis enzymes such as pyruvate dehydrogenase kinase 4 (PDK4), phosphoenolpyruvate carboxykinase (PEPCK), and glucose transporter 2 (GLUT2), expedites the elevation of blood glucose and the progression of insulin resistance.Conclusions: These findings indicate that G1 treatment is influenced by a high‐fat diet, potentially disrupting glucolipid metabolism and promoting insulin resistance alongside its antiobesity effects. Consequently, further investigation is imperative to thoroughly explore this potential toxic side effect of G1 therapy.

Recently, studies have suggested the use of the cardiometabolic index (CMI) to reflect the risk of cardiometabolic disease. However, the association between the CMI and the risk of mortality remains unclear. The aim of the present study was to assess the associations between the CMI and the risk of mortality in the National Health and Nutrition Examination Survey (NHANES) population. This present study analyzed data from the entire 1999 to 2018 NHANES cycle and ultimately included 20,570 individuals. All individuals were classified into 3 groups based on their CMI tertile, which was calculated by multiplying the waist-to-height ratio (WHtR) by the triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio. The study endpoints included all-cause mortality, cardiovascular mortality, and diabetes-related mortality. Kaplan‒Meier survival and Cox regression analyses were performed to determine the association between the CMI and mortality risk. A total of 2660 (12.9%) individuals experienced all-cause death. Kaplan‒Meier survival curves suggested significant differences in mortality risk among the 3 groups (log-rank P < .001). According to the multivariate Cox regression analysis, the CMI was significantly associated with diabetes-related mortality risk (hazard ratio: 1.75, 95% CI: 1.38-2.22, P < .001) but not all-cause mortality or cardiovascular disease (CVD) mortality after adjusting for confounding risk factors. A higher CMI was independently associated with an increased risk of diabetes-related mortality but not all-cause mortality or CVD mortality in the NHANES population.