Triglyceride-glucose index predicts postoperative delirium in elderly patients with type 2 diabetes mellitus: a retrospective cohort study.

BACKGROUND: Postoperative delirium (POD) is more prevalent among elderly patients with type 2 diabetes mellitus (T2DM). Insulin resistance (IR) can be assessed using the triglyceride-glucose (TyG) index, a novel biomarker. This study aims to investigate the predictive potential of the TyG index for POD in elderly patients with T2DM. MATERIALS AND METHODS: Elderly patients (≥ 65) with T2DM who underwent non-neurosurgery and non-cardiac surgery were enrolled. Univariate and multivariate logistic regression analyses were conducted to assess the association between the TyG index and POD. Additionally, subgroup analyses were performed to compare the sex-specific differences in the predictive ability of the TyG index for POD. RESULTS: A total of 4566 patients were included in this retrospective cohort. The receiver operating characteristic (ROC) curve analysis determined the optimal cut-off value for the TyG index to be 8.678. In the univariate model, a TyG index > 8.678 exhibited an odds ratio (OR) of 1.668 (95% CI: 1.210-2.324, P = 0.002) for predicting POD. In the multivariate regression models, the ORs were 1.590 (95% CI: 1.133-2.252, P < 0.008), 1.661 (95% CI: 1.199-2.325, P < 0.003), and 1.603 (95% CI: 1.137-2.283, P = 0.008) for different models. Subgroup analyses demonstrated that the predictive ability of the TyG index was more pronounced in females compared to males. CONCLUSION: The TyG index shows promise as a novel biomarker for predicting the occurrence of POD in elderly surgical patients with T2DM.

High body mass index is associated with elevated risk of perioperative ischemic stroke in patients who underwent noncardiac surgery: A retrospective cohort study.

BACKGROUND: Body mass index (BMI) serves as a global metric for assessing obesity and overall health status. However, the impact of BMI, treated as a continuous variable, on the risk of perioperative stroke remains poorly understood. This retrospective cohort study aimed to elucidate the association between BMI and the risk of perioperative ischemic stroke in patients undergoing non-cardiovascular surgery. METHODS: A cohort of 223,415 patients undergoing noncardiac surgery at the First Medical Center of Chinese PLA General Hospital between January 1, 2008 and August 31, 2019 was screened. Preoperative high BMI, defined as BMI >22.64 kg/m2, was the primary exposure, and the outcome of interest was the new diagnosis of perioperative ischemic stroke within 30 days post-surgery. Robust controls for patient and intraoperative factors were implemented to minimize residual confounding. Logistic regression and propensity score matching were employed, and patients were stratified into subgroups for further investigation. RESULTS: The overall incidence of perioperative ischemic stroke was 0.23% (n = 525) in the cohort. After adjusting for patient-related variables (OR 1.283; 95% CI, 1.04-1.594; p < 0.05), surgery-related variables (OR 1.484; 95% CI, 1.2-1.849; p < 0.001), and all confounding variables (OR 1.279; 95% CI, 1.025-1.607; p < 0.05), patients with BMI >22.64 kg/m2 exhibited a significantly increased risk of perioperative ischemic stroke. This association persisted in the propensity score matched cohort (OR 1.577; 95% CI, 1.203-2.073; p < 0.01). Subgroup analyses indicated that preoperative BMI >22.64 kg/m2 correlated with an elevated risk of perioperative ischemic stroke in female patients, those with coronary heart disease, peripheral vascular diseases, and individuals undergoing neurosurgery. CONCLUSION: We first identified BMI >22.64 kg/m2 as a substantial and independent risk factor for perioperative ischemic stroke in Chinese noncardiac surgery patients. Normal BMI may not suffice as a universal preventive standard. Instead, a more stringent perioperative weight management approach is recommended, particularly for specific subgroups such as female patients, those with coronary heart disease and peripheral vascular disease, and individuals scheduled for neurosurgery.

Insulin attenuates LPS-induced cognitive impairment and ferroptosis through regulation of glucose metabolism in hippocampus.

AIMS: Neuroinflammation is a recognized contributor to cognitive disorders like Alzheimer's disease, with ferroptosis emerging as a novel mechanism underlying cognitive dysfunction associated with neuroinflammation. Insulin, pivotal in the central nervous system, holds promise for cognitive function enhancement. This study aimed to establish a cognitive impairment model through intracerebroventricular injection of lipopolysaccharide (LPS) and explore the impact of intracerebroventricular insulin injection on cognitive function in mice. METHODS: We employed diverse experimental techniques, including animal behavior testing, molecular assays, targeted metabolomics, nuclear medicine, and electron microscopy, to assess neurodegenerative changes, brain insulin resistance (IR), glucose uptake and metabolism, and ferroptosis. The model of cognitive impairment was induced via intracerebroventricular injection of LPS, followed by intracerebroventricular administration of insulin to evaluate its effects. RESULTS: Insulin treatment effectively mitigated LPS-induced cognitive decline and safeguarded against neuronal degeneration. Furthermore, insulin alleviated LPS-induced insulin resistance, enhanced glucose uptake in the hippocampus, and promoted the Pentose Phosphate Pathway (PPP) and nicotinamide adenine dinucleotide phosphate (NADPH) production. Additionally, insulin activated the glutathione (GSH)-glutathione peroxidase 4 (GPX4) pathway, reducing lipid peroxidation, and mitochondrial damage characteristic of LPS-induced ferroptosis in the hippocampus. CONCLUSION: Our findings underscore the therapeutic potential of insulin in alleviating LPS-induced cognitive impairment and ferroptosis by modulating glucose metabolism. This study offers a promising avenue for future interventions targeting cognitive decline.