Low Remnant Cholesterol and In-Hospital Bleeding Risk After Ischemic Stroke or Transient Ischemic Attack.

BACKGROUND: Bleeding risk brought by intensive lipid-lowering therapy and low low-density lipoprotein cholesterol is concerning, while evidence regarding the relationship between remnant cholesterol and bleeding is frightening. This study aimed to investigate the association between remnant cholesterol at admission and an in-hospital bleeding event after acute ischemic stroke or transient ischemic attack (TIA). METHODS AND RESULTS: A total of 3222 eligible patients admitted to Shanghai Huashan Hospital between 2015 and 2021 with complete lipid data were analyzed. Patients were classified into low (<20.0 mg/dL), moderate (20.0-29.9 mg/dL), and high (≥30 mg/dL) groups by remnant cholesterol. The mean age of patients was 63.0± 13.1 years, including 2301 (71.4%) men and 651 (20.2%) with TIA. The median (interquartile range) of remnant cholesterol was 18.6 (13.5-25.9) mg/dL. After adjustment for confounding variables, patients with low remnant cholesterol had a higher risk of bleeding events (odds ratio, 2.56 [95% CI, 1.12-6.67]) than those with moderate remnant cholesterol. The high remnant cholesterol group was not significantly associated with bleeding risk. Combined assessment of low-density lipoprotein cholesterol and remnant cholesterol further identified patients with the highest risk of bleeding events. CONCLUSIONS: Low remnant cholesterol levels were associated with bleeding events during the acute stage of ischemic stroke and TIA. The assessment of remnant cholesterol could inform the bleeding risk during hospitalization both for patients and physicians in clinical practice.

Greater variability in HDL-C was associated with an increased risk of cognitive decline in the middle- and elderly Chinese: A cohort study.

BACKGROUND: Previous studies into relationship between high-density lipoprotein cholesterol (HDL-C) and cognitive decline were constrained to a single measurement, leaving the association between HDL-C variability and risk of cognitive decline unclear. METHODS: We identified 5930 participants from the China Health and Retirement Longitudinal Study (CHARLS) who were devoid for stroke, dementia, and memory-related diseases at baseline and underwent a minimum of 2 sequential health examinations during 2011-2015. Variability in HDL-C was defined as (1) variability independent of the mean (VIM), (2) average real variability (ARV), and (3) standard deviation (SD) of HDL-C change from baseline and follow-up visits. Cognitive function was evaluated in 2018 by Mini-mental state examination (MMSE) in the Chinese version. Logistic regression was employed to explore the association between HDL-C variability and cognitive decline. Odd ratios (OR) and 95 % confidence intervals (CI) were reported. RESULTS: The study included participants from CHARLS, mean age of 57.84±8.44 years and 44 % male. After adjustment for covariates, the highest quartile of VIM was associated with an increased risk of cognitive decline [OR:1.049, 95 %CI: 1.014-1.086] compared to the lowest quartile. For each SD increment of VIM, the OR was 1.015 (95 %CI:1.003-1.027). Strong dose-response relationships were identified (P for trend: 0.005). Consistent results were obtained for other measures of HDL-C variability (ARV and SD). Similar patterns were identified in different dimensions of cognition. CONCLUSIONS: Elevated HDL-C variability was associated with increased cognitive decline risk. Strategies to reducing HDL-C variability may lower the risks of cognitive decline among the general population.

The Association between Dietary Nutrient Intake and Acceleration of Aging: Evidence from NHANES.

The acceleration of aging is a risk factor for numerous diseases, and diet has been identified as an especially effective anti-aging method. Currently, research on the relationship between dietary nutrient intake and accelerated aging remains limited, with existing studies focusing on the intake of a small number of individual dietary nutrients. Comprehensive research on the single and mixed anti-aging effects of dietary nutrients has not been conducted. This study aimed to comprehensively explore the effects of numerous dietary nutrient intakes, both singly and in combination, on the acceleration of aging. Data for this study were extracted from the 2015-2018 National Health and Nutrition Examination Surveys (NHANES). The acceleration of aging was measured by phenotypic age acceleration. Linear regression (linear), restricted cubic spline (RCS) (nonlinear), and weighted quantile sum (WQS) (mixed effect) models were used to explore the association between dietary nutrient intake and accelerated aging. A total of 4692 participants aged ≥ 20 were included in this study. In fully adjusted models, intakes of 16 nutrients were negatively associated with accelerated aging (protein, vitamin E, vitamin A, beta-carotene, vitamin B1, vitamin B2, vitamin B6, vitamin K, phosphorus, magnesium, iron, zinc, copper, potassium, dietary fiber, and alcohol). Intakes of total sugars, vitamin C, vitamin K, caffeine, and alcohol showed significant nonlinear associations with accelerated aging. Additionally, mixed dietary nutrient intakes were negatively associated with accelerated aging. Single dietary nutrients as well as mixed nutrient intake may mitigate accelerated aging. Moderately increasing the intake of specific dietary nutrients and maintaining dietary balance may be key strategies to prevent accelerated aging.

Associations between sleep duration trajectories and cognitive decline: A longitudinal cohort study in China.

OBJECT: The relationship between sleep duration trajectories and cognitive decline remains uncertain. This study aims to examine the connections between various patterns of sleep duration and cognitive function. METHODS: Group-based trajectory modeling (GBTM) was employed to identify longitudinal trajectories of sleep duration over four-year follow-up period, while considering age, sex and nap duration as adjustments. Logistic regression was utilized to analyze the association between sleep trajectories and cognition, with odds ratios (OR) and 95 % confidence intervals (CI) reported. Subgroup analyses based on various demographic characteristics were conducted to explore potential differences in sleep trajectories and cognitive decline across different population subgroups. RESULTS: A total of 5061 participants were followed for four years, and three sleep duration trajectories were identified: high increasing (n = 2101, 41.6 %), stable increasing (n = 2087, 40.7 %), and low decreasing (n = 873, 17.7 %). After adjustment for basic demographic information, health status, and baseline cognition, the high increasing trajectory was found to be associated with cognitive decline in terms of global cognition (OR:1.52,95 %CI:1.18-1.96), mental intactness (OR:1.36,95 %CI:1.07-1.73) and episodic memory (OR:1.33, 95 %CI:1.05-1.67), as compared to stable increasing trajectory. These associations were particularly prominent among the non-elderly population (≤65 years) and those without depressive symptoms. CONCLUSION: This study suggests that both high increasing and low decreasing sleep duration trajectories are linked to cognitive decline, as compared to the stable increasing trajectory. Long-term attention to changes in sleep duration facilitates early prevention of cognitive decline.

Development and external validation of a multimodal integrated feature neural network (MIFNN) for the diagnosis of malignancy in small pulmonary nodules (≤10 mm).

Objectives. Current lung cancer screening protocols primarily evaluate pulmonary nodules, yet often neglect the malignancy risk associated with small nodules (≤10 mm). This study endeavors to optimize the management of pulmonary nodules in this population by devising and externally validating a Multimodal Integrated Feature Neural Network (MIFNN). We hypothesize that the fusion of deep learning algorithms with morphological nodule features will significantly enhance diagnostic accuracy.Materials and Methods. Data were retrospectively collected from the Lung Nodule Analysis 2016 (LUNA16) dataset and four local centers in Beijing, China. The study includes patients with small pulmonary nodules (≤10 mm). We developed a neural network, termed MIFNN, that synergistically combines computed tomography (CT) images and morphological characteristics of pulmonary nodules. The network is designed to acquire clinically relevant deep learning features, thereby elevating the diagnostic accuracy of existing models. Importantly, the network's simple architecture and use of standard screening variables enable seamless integration into standard lung cancer screening protocols.Results. In summary, the study analyzed a total of 382 small pulmonary nodules (85 malignant) from the LUNA16 dataset and 101 small pulmonary nodules (33 malignant) obtained from four specialized centers in Beijing, China, for model training and external validation. Both internal and external validation metrics indicate that the MIFNN significantly surpasses extant state-of-the-art models, achieving an internal area under the curve (AUC) of 0.890 (95% CI: 0.848-0.932) and an external AUC of 0.843 (95% CI: 0.784-0.891).Conclusion. The MIFNN model significantly enhances the diagnostic accuracy of small pulmonary nodules, outperforming existing benchmarks by Zhanget alwith a 6.34% improvement for nodules less than 10 mm. Leveraging advanced integration techniques for imaging and clinical data, MIFNN increases the efficiency of lung cancer screenings and optimizes nodule management, potentially reducing false positives and unnecessary biopsies.Clinical relevance statement. The MIFNN enhances lung cancer screening efficiency and patient management for small pulmonary nodules, while seamlessly integrating into existing workflows due to its reliance on standard screening variables.

Remnant cholesterol traits and risk of stroke: A multivariable Mendelian randomization study.

Observational epidemiological studies have reported a relationship between remnant cholesterol and stroke. However, the results are inconclusive, and causality remains unclear due to confounding or reverse causality. Our objective in this study was to investigate the causal relevance of remnant cholesterol and the risk of stroke and its subtypes using the Mendelian randomization (MR) approach. Genome-wide association studies (GWASs) including 115,082 European individuals (UK Biobank) were used to identify instruments for remnant cholesterol, including intermediate-density lipoprotein (IDL) cholesterol and very-low-density lipoprotein (VLDL) cholesterol. Summary-level data for total stroke, intracerebral hemorrhage, subarachnoid hemorrhage, ischemic stroke (IS), and IS subtypes were obtained from GWAS meta-analyses conducted by the MEGASTROKE consortium. Univariable and multivariable MR analyses were performed. The GWAS identified multiple single-nucleotide polymorphisms after clumping for remnant cholesterol (n = 52), IDL cholesterol (n = 62), and VLDL cholesterol (n = 67). Assessed individually using MR, remnant cholesterol (weighted median: odds ratio [OR] 1.32 per 1-SD higher trait; 95% CI: 1.04-1.67; P = 0.024) had effect estimates consistent with a higher risk of LAS-IS, driven by IDL cholesterol (OR 1.32; 95% CI: 1.04-1.68; P = 0.022). In multivariable MR, IDL cholesterol (OR 1.46; 95% CI: 1.10-1.93; P = 0.009) retained a robust effect on LAS-IS after controlling for VLDL cholesterol and high-density lipoprotein cholesterol. The MR analysis did not indicate causal associations between remnant cholesterol and other stroke subtypes. This study suggests that remnant cholesterol is causally associated with the risk of LAS-IS driven by IDL cholesterol.

Temporal relationship between elevated serum uric acid levels and dyslipidemia: A 5-year cohort study using cross-lagged panel analysis.

BACKGROUND AND AIM: Previous studies have demonstrated an association between SUA and dyslipidemia. This study aims to explore the temporal relationship between SUA and dyslipidemia. METHODS AND RESULTS: Based on the Beijing Health Management Cohort conducted from 2013 to 2018, the data of a physical examination population was collected, including a total of 6630 study subjects. Cross-lagged panel analysis was employed to examine the temporal relationship between elevated SUA levels and dyslipidemia, indicated by either elevated TG or decreased HDL-C. The path coefficient and the 95 % CI from baseline TG to follow-up SUA were as follows: in the general population, men, women, and people with BMI ≥25 kg/m2were 0.027 (0.008-0.045), 0.024 (0.001-0.048), 0.032 (0.001-0.063) and 0.033 (0.006-0.059) (P < 0.05); however, the path coefficient from baseline SUA to follow-up TG and the 95 % CI were not statistically significant. Furthermore, the path coefficients and 95 % CIs between elevated SUA and decreased HDL-C were not statistically significant, both in the general population and in populations stratified by gender and BMI. CONCLUSIONS: We found a temporal relationship from elevated TG to elevated SUA in the general population and the populations stratified by gender and BMI (≥25 kg/m2). However, we did not observe a reverse relationship from elevated SUA to elevated TG. Additionally, we did not find a temporal relationship between decreased HDL-C and elevated SUA in both the general population and the stratified populations.

Association of Abnormal Lung Function and Its Subtypes With Arterial Stiffness: A Longitudinal Cohort Study.

BACKGROUND: Prior studies have reported the cross-sectional relationship between lung function and arterial stiffness, while the longitudinal association remains unclear to date. This study aimed to investigate whether abnormal lung function and its subtypes at baseline are associated with increased arterial stiffness using a cohort. METHODS AND RESULTS: This was a secondary analysis extracting 2461 participants from Beijing Health Management Cohort as baseline and annually followed for development of arterial stiffness. Abnormal lung function was defined by forced expiratory volume in 1s <80% of the predicted value, forced vital capacity of the predicted value, or forced expiratory volume in 1s/forced vital capacity ratio <70%. Increased arterial stiffness was determined by brachial-ankle pulse wave velocity ≥1400 cm/s. Cox proportional hazards model was used to calculate the hazard ratio and population attributable fraction. The mean age was 42.8±8.1 years, and 444 (18.0%) cases developed increased arterial stiffness during a median follow-up of 3.0 years. The adjusted hazard ratio (95% CI) of arterial stiffness was 1.47 (95% CI, 1.10-1.96) for abnormal lung function, with a population attributable fraction of 3.9% (95% CI, 0.8-7.1). Of subtypes, only obstructive ventilatory dysfunction was significantly associated with arterial stiffness (adjusted hazard ratio, 2.06 [95% CI, 1.27-3.36]), not restricted ventilatory dysfunction (adjusted hazard ratio, 0.95 [95% CI, 0.54-1.65]). Consistent results were observed on multiple sensitivity analyses. CONCLUSIONS: Our study indicated a longitudinal association of abnormal lung function with increased arterial stiffness using a large cohort, especially for the obstructive ventilatory dysfunction.