ABSTRACT
This study systematically reviewed the application of large language models (LLMs) in medicine, analyzing 550 selected studies from a vast literature search. LLMs like ChatGPT transformed healthcare by enhancing diagnostics, medical writing, education, and project management. They assisted in drafting medical documents, creating training simulations, and streamlining research processes. Despite their growing utility in assisted diagnosis and improving doctor-patient communication, challenges persisted, including limitations in contextual understanding and the risk of over-reliance. The surge in LLM-related research indicated a focus on medical writing, diagnostics, and patient communication, but highlighted the need for careful integration, considering validation, ethical concerns, and the balance with traditional medical practice. Future research directions suggested a focus on multimodal LLMs, deeper algorithmic understanding, and ensuring responsible, effective use in healthcare.
ABSTRACT
OBJECTIVE: 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. RESEARCH DESIGN AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
ABSTRACT
Background: The remnant-like particle cholesterol (RLP-C) has been demonstrated to be associated with residual cardiovascular risk. The meta-analysis aimed to evaluate the impact of baseline RLP-C on the incidence of major cardiovascular adverse events (MACEs) in patients with coronary artery disease (CAD). Methods: A systematic literature search was performed in PubMed and Embase electronic databases from the inception of the databases through 1 October 2022. Studies evaluating the association between baseline RLP-C and the risk of MACEs in patients with CAD were included. Hazard ratios (HRs) with 95% confidence intervals (CIs) were pooled by a random-effect method (RLP-C analyzed as a categorical variable) and a fixed-effects model (RLP-C analyzed as a continuous variable). Results: Ten studies including 18,053 subjects were finally included in this meta-analysis. In our pooled analysis, compared to CAD patients with the lowest RLP-C category, the CAD patients with the highest RLP-C category had a significantly higher risk of future MACEs during follow-up (HR 1.79, 95% CI, 1.42−2.26, I2 = 60.31%, p < 0.01), which was consistent with outcomes of meta-analysis with the RLP-C analyzed as a continuous variable (HR 1.40, 95% CI, 1.28−1.53, I2 = 38.20%, p < 0.01). The sensitivity analysis confirmed the robustness of the results, and no significant publication bias was identified. Conclusion: The present meta-analysis suggests that the RLP-C was associated with an increased risk of long-term MACEs in patients with CAD at baseline. It is necessary to conduct randomized controlled trials to explore whether reducing the RLP-C level is conducive to reducing residual cardiovascular risk, even coronary plaque regression.