Peripheral PD-1+NK cells could predict the 28-day mortality in sepsis patients.

Background: Unbalanced inflammatory response is a critical feature of sepsis, a life-threatening condition with significant global health burdens. Immune dysfunction, particularly that involving different immune cells in peripheral blood, plays a crucial pathophysiological role and shows early warning signs in sepsis. The objective is to explore the relationship between sepsis and immune subpopulations in peripheral blood, and to identify patients with a higher risk of 28-day mortality based on immunological subtypes with machine-learning (ML) model. Methods: Patients were enrolled according to the sepsis-3 criteria in this retrospective observational study, along with age- and sex-matched healthy controls (HCs). Data on clinical characteristics, laboratory tests, and lymphocyte immunophenotyping were collected. XGBoost and k-means clustering as ML approaches, were employed to analyze the immune profiles and stratify septic patients based on their immunological subtypes. Cox regression survival analysis was used to identify potential biomarkers and to assess their association with 28-day mortality. The accuracy of biomarkers for mortality was determined by the area under the receiver operating characteristic (ROC) curve (AUC) analysis. Results: The study enrolled 100 septic patients and 89 HCs, revealing distinct lymphocyte profiles between the two groups. The XGBoost model discriminated sepsis from HCs with an area under the receiver operating characteristic curve of 1.0 and 0.99 in the training and testing set, respectively. Within the model, the top three highest important contributions were the percentage of CD38+CD8+T cells, PD-1+NK cells, HLA-DR+CD8+T cells. Two clusters of peripheral immunophenotyping of septic patients by k-means clustering were conducted. Cluster 1 featured higher proportions of PD1+ NK cells, while cluster 2 featured higher proportions of naïve CD4+T cells. Furthermore, the level of PD-1+NK cells was significantly higher in the non-survivors than the survivors (15.1% vs 8.6%, P<0.01). Moreover, the levels of PD1+ NK cells combined with SOFA score showed good performance in predicting the 28-day mortality in sepsis (AUC=0.91,95%CI 0.82-0.99), which is superior to PD1+ NK cells only(AUC=0.69, sensitivity 0.74, specificity 0.64, cut-off value of 11.25%). In the multivariate Cox regression, high expression of PD1+ NK cells proportion was related to 28-day mortality (aHR=1.34, 95%CI 1.19 to 1.50; P<0.001). Conclusion: The study provides novel insights into the association between PD1+NK cell profiles and prognosis of sepsis. Peripheral immunophenotyping could potentially stratify the septic patients and identify those with a high risk of 28-day mortality.

Prevalence, cessation, and geographical variation of smoking among middle-aged and elderly adults in China: A population-based study.

INTRODUCTION: Smoking significantly burdens human health, contributing to an increasing incidence of mortality and morbidity. This study aims to explore the prevalence of smoking, cessation, and the association between various risk factors and smoking intensity measured in pack-years among Chinese adults. METHODS: During 2020-2021, the China Stroke High-risk Population Screening and Intervention Program (CSHPSIP) invited participants aged ≥40 years from 31 provinces in mainland China. This cross-sectional study presents the standardized prevalence of smoking and cessation across various demographics, including age, sex, residence, income, education level, BMI, and geographical region of residence. Multivariable logistic regression was used to examine the associations between smoking pack-years and related factors. RESULTS: Among 524741 participants (mean age: 61.9 ± 10.9 years; 41.1% male; 58.9% female), standardized smoking prevalence was 19.3% (95% CI: 19.2-19.4), with men (37.2%; 95% CI: 37.0-37.4) displaying significantly higher rates than women (1.3%; 95% CI: 1.2-1.3). Smoking cessation rate stood at 11.2% (95% CI: 11.0-11.4), with 11.3% (95% CI: 11.1-11.5) for men and 8.4% (95% CI: 7.5-9.2) for women. Urban residents and those with advanced education had lower smoking rates and higher cessation rates. Additionally, the dose-response relationship indicated a more pronounced association between higher smoking pack-years and elevated health risks, including hypertension (AOR=1.30; 95% CI: 1.24-1.36), diabetes (AOR=1.26; 95% CI: 1.20-1.33), hyperlipidemia (AOR=1.22; 95% CI: 1.16-1.28), heart disease (AOR=1.40; 95% CI: 1.26-1.54), and stroke (AOR=1.23; 95% CI: 1.10-1.36). CONCLUSIONS: This comprehensive study emphasizes the profound impact of smoking on health in Chinese adults, indicating the critical need for tailored cessation programs, particularly for middle-aged individuals, men, rural residents, and those with lower level of education.

Identifying subtypes of type 2 diabetes mellitus with machine learning: development, internal validation, prognostic validation and medication burden in linked electronic health records in 420 448 individuals.

INTRODUCTION: None of the studies of type 2 diabetes (T2D) subtyping to date have used linked population-level data for incident and prevalent T2D, incorporating a diverse set of variables, explainable methods for cluster characterization, or adhered to an established framework. We aimed to develop and validate machine learning (ML)-informed subtypes for type 2 diabetes mellitus (T2D) using nationally representative data. RESEARCH DESIGN AND METHODS: In population-based electronic health records (2006-2020; Clinical Practice Research Datalink) in individuals ≥18 years with incident T2D (n=420 448), we included factors (n=3787), including demography, history, examination, biomarkers and medications. Using a published framework, we identified subtypes through nine unsupervised ML methods (K-means, K-means++, K-mode, K-prototype, mini-batch, agglomerative hierarchical clustering, Birch, Gaussian mixture models, and consensus clustering). We characterized clusters using intracluster distributions and explainable artificial intelligence (AI) techniques. We evaluated subtypes for (1) internal validity (within dataset; across methods); (2) prognostic validity (prediction for 5-year all-cause mortality, hospitalization and new chronic diseases); and (3) medication burden. RESULTS: Development: We identified four T2D subtypes: metabolic, early onset, late onset and cardiometabolic. Internal validity: Subtypes were predicted with high accuracy (F1 score >0.98). Prognostic validity: 5-year all-cause mortality, hospitalization, new chronic disease incidence and medication burden differed across T2D subtypes. Compared with the metabolic subtype, 5-year risks of mortality and hospitalization in incident T2D were highest in late-onset subtype (HR 1.95, 1.85-2.05 and 1.66, 1.58-1.75) and lowest in early-onset subtype (1.18, 1.11-1.27 and 0.85, 0.80-0.90). Incidence of chronic diseases was highest in late-onset subtype and lowest in early-onset subtype. Medications: Compared with the metabolic subtype, after adjusting for age, sex, and pre-T2D medications, late-onset subtype (1.31, 1.28-1.35) and early-onset subtype (0.83, 0.81-0.85) were most and least likely, respectively, to be prescribed medications within 5 years following T2D onset. CONCLUSIONS: In the largest study using ML to date in incident T2D, we identified four distinct subtypes, with potential future implications for etiology, therapeutics, and risk prediction.

Association of Blood Selenium Levels with Diabetes and Heart Failure in American General Adults: a Cross-sectional Study of NHANES 2011-2020 pre.

Selenium is an essential trace element closely related to human health; however, the relationship between blood selenium levels, diabetes, and heart failure remains inconclusive. Therefore, this study aimed to explore the relationship between blood selenium levels and the prevalence of diabetes as well as heart failure in American general adults aged 20 years or older. This study utilized data from four survey cycles from NHANES 2011-2020 pre. Blood selenium levels were considered as both a continuous variable and quartiles, and logistic regression was employed to investigate the associations between blood selenium levels with diabetes and heart failure. Nonlinear relationships were examined by restricted cubic spline regression. The analysis included a total of 16311 participants aged 20 years or older. After adjustment for all potential confounder, we found when the blood selenium levels increased by 10 ug/L, the average risk of diabetes increased by 4.2% (95% CI: 1.5%, 7.0%), and the average risk of heart failure decreased by 5.0% (95% CI: 0.1%, 9.8%). In addition, compared with the lowest reference group, blood selenium levels were significantly positively associated with risk of diabetes in participants in the fourth quartile (OR=1.458, 95% CI: 1.173, 1.812), while significantly negatively associated with the risk of heart failure in participants in the second, third and fourth quartiles (Q2, OR=0.677, 95% CI: 0.471, 0.974) (Q3, OR=0.609, 95% CI: 0.426, 0.870) (Q4, OR=0.653, 95% CI: 0.443, 0.961). There was a nonlinear and reverse L-shaped association between blood selenium and diabetes, while a negative dose-response association between blood selenium and heart failure. Furthermore, the association between blood selenium levels and heart failure was more pronounced in participants with poor glycemic control, rather than diabetic patients. High blood selenium levels may be positively related to diabetes, while low blood selenium levels may be associated to heart failure. Appropriate blood selenium levels may help prevent diabetes and heart failure.

Effect of Isoflavones on Blood Lipid Alterations in Postmenopausal Females: A Systematic Review and Meta-Analysis of Randomized Trials.

The effects of isoflavones on postmenopausal female's blood lipid profile have yielded conflicting results in previous studies. Further investigation is necessary to determine the potential benefits of isoflavone therapy in managing cardiovascular health in this population. This meta-analysis aimed to assess the effects of isoflavones on blood lipid concentrations in postmenopausal females. A comprehensive search was conducted in major databases for randomized controlled trials published between 2000 and 2023. Eighteen studies were included in the analysis, which examined the impact of isoflavone intake on blood lipids in postmenopausal females. Isoflavone consumption resulted in a significant reduction in triacylglycerol (TG) concentrations (-12.50 mg/dL; 95% CI: -23.09, -1.91) and a modest increase in high-density lipoprotein cholesterol (HDL cholesterol) concentrations (1.83 mg/dL; 95% CI: 0.03, 3.64). Subgroup analysis showed that isoflavones significantly decreased TG (-15.79 mg/dL; 95% CI: -28.36, -3.22) and increased HDL cholesterol (2.49 mg/dL; 95% CI: 1.80, 3.19) in postmenopausal females under 65 y old. No significant effects were observed in females over 65 y old. Both low (≤80 mg/d) and high (>80 mg/d) doses of isoflavones exhibited TG-lowering effects, whereas only the high dose increased HDL cholesterol. Longer treatment duration (≥24 wk) was associated with a significant reduction in TG, whereas HDL cholesterol improvement occurred during the early period (<24 wk) of supplementation. The consumption of isoflavones resulted in a significant reduction in TG concentrations and an increase in HDL cholesterol concentrations among postmenopausal females under 65 y of age.

Prestroke Metformin Use on the 1-Year Prognosis of Intracerebral Hemorrhage Patients with Type 2 Diabetes.

BACKGROUND: Although recent studies have focused on the use of metformin in treating ischemic stroke, there is little literature to support whether it can treat intracerebral hemorrhage (ICH). Therefore, this study is aimed at evaluating the possible effects of prestroke metformin (MET) on ICH patients with type 2 diabetes. METHODS: From January 2010 to December 2019, all first-ever ICH patients with type 2 diabetes from our hospitals were included. All discharged patients would receive a one-time follow-up at 1 year after admission. Death, disability, and recurrence events were recorded. RESULTS: We included 730 patients for analysis (the median age: 65 [IQR, 56-72] years and 57.7% was men). Of those patients, 281 (38.5%) had received MET before ICH (MET+), whereas 449 (61.5%) had not (MET-). MET (+) patients had a lower median baseline hematoma volume than did MET (-) patients (9.6 ml [IQR, 5.3-22.4 ml] vs. 14.7 ml [IQR, 7.9-28.6 ml]; P < 0.001). The inhospital mortality events were not significantly reduced in the MET (+) group compared with the MET (-) group (6.4% vs 8.9%, respectively; absolute difference, -2.5% [95% CI, -3.9% to -0.7%]; OR, 0.70 [95% CI, 0.39 to 1.27]; P = 0.22). The 1-year mortality events were not significantly reduced in the MET (+) group compared with the MET (-) group (14.1% vs 17.4%, respectively; absolute difference, -3.3% [95% CI, -5.1% to -1.8%]; OR, 0.73 [95% CI, 0.47 to 1.14]; P = 0.16). The 1-year disability events were not significantly reduced in the MET (+) group compared with the MET (-) group (28.4% vs 34.1%, respectively; absolute difference, -5.7% [95% CI, -8.2% to -3.3%]; OR, 0.77 [95% CI, 0.52 to 1.13]; P = 0.18). Finally, the recurrence rates in those two groups were not significantly different (MET [+] vs. MET [-]: 6.4% vs. 5.9%; absolute difference, 0.5% [95% CI, 0.2% to 1.3%]; OR, 1.08 [95% CI, 0.51 to 2.28]; P = 0.84). CONCLUSIONS: Pre-ICH metformin use was not associated with inhospital mortality and 1-year prognosis in diabetic ICH patients.

C-Reactive Protein Levels and Clinical Prognosis in LAA-Type Stroke Patients: A Prospective Cohort Study.

METHODS: We prospectively included 200 patients with LAA-type AIS and tested their CRP levels on admission. We followed these patients consecutively. The primary outcome was an adverse event, defined as a modified Rankin Scale score of 2-6 at months 3, 6, and 12 after discharge. A logistic regression model was used to analyze the relationship between CRP and the functional outcome of LAA stroke. RESULTS: We divided 200 patients into 3 groups evenly based on CRP level. After adjustment for gender, age, smoking history, drinking history, history of hyperlipidemia, history of diabetes, lipid levels, and blood glucose levels, logistic regression showed that the incidence of LAA-type AIS poor outcome was positively associated with CRP level at admission, whether it was 3 months, 6 months, or 12 months after discharge, respectively (OR: 2.574, 95% CI: 1.213-5.463; OR: 2.806, 95% CI: 1.298-6.065; OR: 2.492, 95% CI: 1.167-5.321. In the highest tertile vs. the lowest tertile as a reference), and both were statistically different. CONCLUSIONS: High CRP level predicts poor functional outcome in LAA-type AIS patients, which provides a strong basis for clinicians to make treatment decisions for these patients.