Identification of circRNA biomarkers in osteosarcoma: An updated systematic review and meta-analysis.

Circular RNAs (circRNAs) play a crucial role in cancer development and progression. This study aimed to identify potential circRNA biomarkers for osteosarcoma. Articles published from January 2010 to September 2023 were searched across eight databases to compare circRNA expression profiles in osteosarcoma and control samples (human, animal and cell lines). Meta-analysis was conducted under a random effects model. Subgroup analysis of circRNAs in different samples and tissues was performed. Diagnostic value was evaluated using receiver operator characteristic curves. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis explored functions of circRNA host genes. A circRNA-miRNA-mRNA axis depicted the regulatory mechanism in osteosarcoma. Among 1356 circRNAs with differential expression were identified across 226 original studies, only 74 were reported in at least three published sub-studies. Meta-analysis identified 58 dysregulated circRNAs (52 upregulated and 6 downregulated). Eleven circRNAs consistently showed dysregulation in tissues and cell lines, with hsa_circ_0005721 showing potential as a circulating biomarker in osteosarcoma. Sensitivity analysis demonstrated 97 % consistency. The overall area under the curve was 0.87 (95 % CI, 0.83-0.89). GO and KEGG enrichment analyses revealed host gene involvement in cancer. The circRNA-miRNA-mRNA axis revealed the regulatory axis and interactions within osteosarcoma specifically. This study demonstrates circRNAs as potential diagnostic biomarkers for osteosarcoma. Consistently reported dysregulated circRNAs are potential biomarkers in osteosarcoma pathogenesis, with hsa_circ_0005721 as a potential circulating biomarker for diagnosis and treatment.

Intestinal microbiota and metabolome perturbations in ischemic and idiopathic dilated cardiomyopathy.

BACKGROUND: Various clinical similarities are present in ischemic (ICM) and idiopathic dilated cardiomyopathy (IDCM), leading to ambiguity on some occasions. Previous studies have reported that intestinal microbiota appeared dysbiosis in ICM, whether implicating in the IDCM remains unclear. The aim of this study was to assess the alterations in intestinal microbiota and fecal metabolites in ICM and IDCM. METHODS: ICM (n = 20), IDCM (n = 22), and healthy controls (HC, n = 20) were enrolled in this study. Stool samples were collected for 16S rRNA gene sequencing and gas chromatography-mass spectrometry (GC-MS) analysis. RESULTS: Both ICM and IDCM exhibited reduced alpha diversity and altered microbial community structure compared to HC. At the genus level, nine taxa including Blautia, [Ruminococcus]_torques_group, Christensenellaceae_R-7_group, UCG-002, Corynebacterium, Oceanobacillus, Gracilibacillus, Klebsiella and Citrobacter was specific to ICM, whereas one taxa Alistipes uniquely altered in IDCM. Likewise, these changes were accompanied by significant metabolic differences. Further differential analysis displayed that 18 and 14 specific metabolites uniquely changed in ICM and IDCM, respectively. The heatmap was generated to display the association between genera and metabolites. Receiver operating characteristic curve (ROC) analysis confirmed the predictive value of the distinct microbial-metabolite features in disease status. The results showed that microbial (area under curve, AUC = 0.95) and metabolic signatures (AUC = 0.84) were effective in discriminating ICM from HC. Based on the specific microbial and metabolic features, the patients with IDCM could be separated from HC with an AUC of 0.80 and 0.87, respectively. Furthermore, the gut microbial genus (AUC = 0.88) and metabolite model (AUC = 0.89) were comparable in predicting IDCM from ICM. Especially, the combination of fecal microbial-metabolic features improved the ability to differentiate IDCM from ICM with an AUC of 0.96. CONCLUSION: Our findings highlighted the alterations of gut microbiota and metabolites in different types of cardiomyopathies, providing insights into the pathophysiological mechanisms of myocardial diseases. Moreover, multi-omics analysis of fecal samples holds promise as a non-invasive tool for distinguishing disease status.

Association of immunoglobulin G N-glycosylation with carotid atherosclerotic plaque phenotypes and actual clinical cardiovascular events: a study protocol for a longitudinal prospective cohort study.

INTRODUCTION: Immune-inflammatory response plays a key role in the pathogenesis of atherosclerosis. IgG N-glycosylation is reported to be associated with the 10-year atherosclerotic cardiovascular disease risk score and subclinical atherosclerosis. However, the relationship of IgG glycosylation with actual clinical cardiovascular disease (CVD) events and plaque phenotypes has rarely been investigated. Therefore, this study aims to understand whether IgG glycosylation traits are correlated with actual clinical CVD events and plaque phenotypes. METHODS AND ANALYSIS: Designed to verify the efficacy of IgG glycosylation as a risk for CVD events and screen potential biomarkers of CVD to prevent atherosclerosis occurrence, this longitudinal prospective cohort study will be conducted at the First Affiliated Hospital of Shantou University Medical College, China. In total, 2720 participants routinely examined by carotid ultrasound will be divided into different groups according to plaque phenotype characteristics. Ultra-performance liquid chromatography will be performed to separate and detect IgG N-glycans in serum collected at baseline and at the end of the first, second and third years. The primary outcome is the actual clinical CVD composite events, including non-fatal myocardial infarction, death due to coronary heart disease, and fatal or non-fatal stroke. ETHICS AND DISSEMINATION: The Clinical Ethics Committee of the First Affiliated Hospital of Shantou University Medical College approved this study (number: B-2021-127). Findings of this study will be submitted for publication in peer-reviewed journals. TRIAL REGISTRATION NUMBER: ChiCTR2100048740.

Breakthrough of glycobiology in the 21st century.

As modern medicine began to emerge at the turn of the 20th century, glycan-based therapies advanced. DNA- and protein-centered therapies became widely available. The research and development of structurally defined carbohydrates have led to new tools and methods that have sparked interest in the therapeutic applications of glycans. One of the latest omics disciplines to emerge in the contemporary post-genomics age is glycomics. In addition, to providing hope for patients and people with different health conditions through a deeper understanding of the mechanisms of common complex diseases, this new specialty in system sciences has much to offer to communities involved in the development of diagnostics and therapeutics in medicine and life sciences.This review focuses on recent developments that have pushed glycan-based therapies into the spotlight in medicine and the technologies powering these initiatives, which we can take as the most significant success of the 21st century.

All around suboptimal health - a joint position paper of the Suboptimal Health Study Consortium and European Association for Predictive, Preventive and Personalised Medicine.

First two decades of the twenty-first century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The time-frame between onset of SHS and clinical manifestation of associated disorders is the operational area for an application of reliable risk assessment tools and predictive diagnostics followed by the cost-effective targeted prevention and treatments tailored to the person. This article demonstrates advanced strategies in bio/medical sciences and healthcare focused on suboptimal health conditions in the frame-work of Predictive, Preventive and Personalised Medicine (3PM/PPPM). Potential benefits in healthcare systems and for society at large include but are not restricted to an improved life-quality of major populations and socio-economical groups, advanced professionalism of healthcare-givers and sustainable healthcare economy. Amongst others, following medical areas are proposed to strongly benefit from PPPM strategies applied to the identification and treatment of suboptimal health conditions:Stress overload associated pathologiesMale and female healthPlanned pregnanciesPeriodontal healthEye disordersInflammatory disorders, wound healing and pain management with associated complicationsMetabolic disorders and suboptimal body weightCardiovascular pathologiesCancersStroke, particularly of unknown aetiology and in young individualsSleep medicineSports medicineImproved individual outcomes under pandemic conditions such as COVID-19.

Associated Factors of Suboptimal Health Status Among Adolescents in China: A Cross-Sectional Study.

PURPOSE: Suboptimal health status (SHS) is a state between health and disease, has several adverse effects, although, its main underlying mechanism is still unclear. This study aimed to investigate SHS and its associated factors of adolescents. METHODS: A community-based cross-sectional study was conducted in the three different geographic locations of China (Shanxi, Guangzhou, and Tibet). A multidimensional sub-health questionnaire of adolescent (MSQA) is used to evaluate SHS. Independent two-sample K-S test was performed for the quantitative data as the non-parametric test, whereas Chi-square test method was applied to explore the difference of discrete variables data between groups. Then finally, multiple logistic regression analysis was applied to analyze the influential factors of SHS. RESULTS: Among 1461 respondents (between 15 and 18 years old), females proportion (56.47%) was higher than males (43.53%) where SHS was higher in Shanxi followed by Tibet and then Guangdong. The rural area, grade, lack of sleep time, home visit in a week, lack of exercise, a heavy burden of study, smoking, drinking, and fewer friends were the risk factors of SHS, while families living status, seeking help and extroversion were the protective factors. CONCLUSION: SHS is significantly associated with behavior and lifestyle-related factors. For comprehensively prevention and control of the SHS, it is urgently needed to reduce the risk factors and enhance the protective factors among adolescents.

Assessment on the Impact on Human Health, Environment, Water and Soil by Disposing Household Expired Drugs: A Cross-Sectional Study in China.

BACKGROUND: The household expired drugs disposal has been a huge public issue in many countries, including China, which may affect various side and toxic effects on human health and environment, water resources, and soil too. This paper explores the knowledge, attitude, and practice of Guangzhou city residents regarding household expired drugs and their effect on human health and provided the scientific pieces of evidence to carry out the long-term recovery mechanism for expired medicines. METHODS: An observational, cross-sectional study was conducted using a self-structured questionnaire. Descriptive analysis, including univariate and unconditional logistic regression models, was carried out to analyze the data. RESULTS: A total of 613 community residents with a 99.4% response rate enrolled for the study. More than half 60.2% of residents stated that expired drugs pollute the environment, soil, and water resources, where 81.2% of respondents knew that it would produce side effects or toxic effects. However, still, 71.6% of respondents disposed of directly into the trash bin or sink, and, only 24.8% had good practice that they use a designed recycling bin. Likewise, only 8.3% of respondents placed expired drugs into collection points nearly 3-5 times in a year, while 65.1% of participants never disposed of in the collection point, which found a worse practice. CONCLUSION: Overall, the knowledge, attitude, and practice of Guangzhou residents regarding household expired drugs disposal were not ideal. To improve the resident's awareness about family expired drugs disposal, ensure the financial support for the recycling process, establish an accessible and acceptable recycling point, and introduce relevant laws and regulations for the long-term mechanism.

A comprehensive intervention on feasibility, efficacy, and safety between TAE combined with multi-applicator ablation therapy and TACE in the treatment of large hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common tumors in recent days with high mortality and low early diagnosis rate, resulting in the fourth leading cause of deaths globally. This study aimed to evaluate the feasibility, efficacy, and safety between transcatheter arterial embolization (TAE) therapy followed by multi-applicator ablation and transarterial chemoembolization (TACE) for the treatment of large HCC. METHODS: An intervention study conducted at the Cancer Center of Sun Yat-sen University, Guangzhou, China, with whom had large HCC. A comparison between the two groups (intervention and control group) was evaluated at different time dimensions by repeated-measures analysis of variance, Mann-Whitney U rank-sum test, where Kaplan-Meier and log-rank test calculated for the overall survival (OS), tumor response (TR), and progression-free survival (PFS). RESULTS: This study found the improved survival rate (SR) and PFS after 1-year treatment in the observation group (Group-I) by 56.4% and 12.8%, compared to 38.3% and 8.5% in the control group (Group-II). Likewise, 1- and 2-year OS rates (OSRs) in Group-I were 66.7% and 51.4%, wherein Group-II were 48.9% and 30.0%, respectively. The short-term efficacy of Group-I, such as complete response (CR), partial response (PR), stable disease (SD), progressive disease (PD) were 28.21%, 56.41%, 0, 15.38%, while in Group-II was 2.13%, 68.79%, 6.38% 22.70% respectively, which were significant. The short-term efficacy was more excellent in the Group-I than Group-II. The quality of life (QOL) was better in Group-I than that of Group-II. CONCLUSIONS: TAE combined with multi-applicator ablation therapy is safer, effective with prolonged survival, and less severe adverse reactions compared to TACE therapy for the treatment of large HCC.

Automatic epileptic seizure classification in multichannel EEG time series with linear discriminant analysis.

BACKGROUND: An electroencephalogram (EEG) is the most dominant method for detecting epileptic seizures. However, the existing techniques use single-channel EEGs from public databases and the sample size is small. OBJECTIVE: This study proposes a strategy to distinguish multichannel EEGs for health control, particularly the interictal and ictal multichannel EEGs of epileptic patients. METHOD: We calculated five features (variance, Pearson correlation coefficient, Hoeffding's D measure, Shannon entropy, inter-quartile range), which are based on maximal overlap discrete wavelet transform. These features were then fed into linear discriminant analysis for classification purposes. Finally, the proposed method was tested on data on 34 healthy people, 21 interictal patients and 30 ictal patients taken from a hospital. RESULTS: Our experimental results show that the accuracy between healthy and epileptic seizures was 96.88% and the area under the curve (AUC) is 1. The accuracy between interictal and epileptic seizures was 94.12% and the AUC was 0.97. We also obtained an accuracy and AUC equal to 1 for discrimination of interictal EEGs from normal. Finally, we obtained an AUC of 0.83 and an accuracy of 85.88% for discrimination in these three classes. Therefore, our study achieves sufficient performance. CONCLUSIONS: Our proposed method can serve as an auxiliary tool for clinicians who wish to make clinical decisions and reduces the burden of detecting epileptic seizures.

A novel approach to determine two optimal cut-points of a continuous predictor with a U-shaped relationship to hazard ratio in survival data: simulation and application.

BACKGROUND: In clinical and epidemiological researches, continuous predictors are often discretized into categorical variables for classification of patients. When the relationship between a continuous predictor and log relative hazards is U-shaped in survival data, there is a lack of a satisfying solution to find optimal cut-points to discretize the continuous predictor. In this study, we propose a novel approach named optimal equal-HR method to discretize a continuous variable that has a U-shaped relationship with log relative hazards in survival data. METHODS: The main idea of the optimal equal-HR method is to find two optimal cut-points that have equal log relative hazard values and result in Cox models with minimum AIC value. An R package 'CutpointsOEHR' has been developed for easy implementation of the optimal equal-HR method. A Monte Carlo simulation study was carried out to investigate the performance of the optimal equal-HR method. In the simulation process, different censoring proportions, baseline hazard functions and asymmetry levels of U-shaped relationships were chosen. To compare the optimal equal-HR method with other common approaches, the predictive performance of Cox models with variables discretized by different cut-points was assessed. RESULTS: Simulation results showed that in asymmetric U-shape scenarios the optimal equal-HR method had better performance than the median split method, the upper and lower quantiles method, and the minimum p-value method regarding discrimination ability and overall performance of Cox models. The optimal equal-HR method was applied to a real dataset of small cell lung cancer. The real data example demonstrated that the optimal equal-HR method could provide clinical meaningful cut-points and had good predictive performance in Cox models. CONCLUSIONS: In general, the optimal equal-HR method is recommended to discretize a continuous predictor with right-censored outcomes if the predictor has an asymmetric U-shaped relationship with log relative hazards based on Cox regression models.

Association between plasma homocysteine and hypertension: Results from a cross-sectional and longitudinal analysis in Beijing's adult population from 2012 to 2017.

Plasma homocysteine (Hcy) levels are associated with elevated blood pressure. However, the causal association between Hcy levels and the risk of hypertension remains ambiguous. Taking the study design effect into consideration, this study aimed to investigate this issue through a cross-sectional and longitudinal analysis. Data were obtained from the Beijing Health Management Cohort study, which conducted routine health check-ups from 2012 to 2017. Multivariate logistic regression was used for the cross-sectional analysis, and a quadratic inference function approach was performed for the longitudinal analysis. A total of 30 376 subjects (mean age = 50.0 years) were included in the cross-sectional analysis, and a subgroup of 3913 subjects without hypertension at baseline was included in the longitudinal analysis. After adjusting for potential confounders, the risk of hypertension increased with Hcy levels in the cross-sectional analysis using the traditional definition of hypertension (OR = 1.262, 95% CI: 1.155-1.378, Q2 vs Q1; OR = 1.458, 95% CI: 1.335-1.593, Q3 vs Q1; OR = 1.520, 95% CI: 1.388-1.664, Q4 vs Q1) and the 2017 hypertension definition (OR = 1.159, 95% CI: 1.067-1.259, Q2 vs Q1; OR = 1.328, 95% CI: 1.221-1.445, Q3 vs Q1; OR = 1.328, 95% CI: 1.217-1.449, Q4 vs Q1). The longitudinal analysis showed that hypertension risk increased in the third quartile of Hcy (OR = 1.268, 95% CI: 1.030-1.560, Q3 vs Q1). Elevated total plasma Hcy may be used as a predictive biomarker for hypertension. Attention should be paid to gender-specific mechanisms when issuing precise precautions.

Contourlet-based hippocampal magnetic resonance imaging texture features for multivariant classification and prediction of Alzheimer's disease.

The study is aimed to assess whether the addition of contourlet-based hippocampal magnetic resonance imaging (MRI) texture features to multivariant models improves the classification of Alzheimer's disease (AD) and the prediction of mild cognitive impairment (MCI) conversion, and to evaluate whether Gaussian process (GP) and partial least squares (PLS) are feasible in developing multivariant models in this context. Clinical and MRI data of 58 patients with probable AD, 147 with MCI, and 94 normal controls (NCs) were collected. Baseline contourlet-based hippocampal MRI texture features, medical histories, symptoms, neuropsychological tests, volume-based morphometric (VBM) parameters based on MRI, and regional CMgl measurement based on fluorine-18 fluorodeoxyglucose-positron emission tomography were included to develop GP and PLS models to classify different groups of subjects. GPR1 model, which incorporated MRI texture features and was based on GPG, performed better in classifying different groups of subjects than GPR2 model, which used the same algorithm and had the same data as GPR1 except that MRI texture features were excluded. PLS model, which included the same variables as GPR1 but was based on the PLS algorithm, performed best among the three models. GPR1 accurately predicted 82.2% (51/62) of MCI convertors confirmed during the 2-year follow-up period, while this figure was 53 (85.5%) for PLS model. GPR1 and PLS models accurately predicted 58 (79.5%) vs. 61 (83.6%) of 73 patients with stable MCI, respectively. For seven patients with MCI who converted to NCs, PLS model accurately predicted all cases (100%), while GPR1 predicted six (85.7%) cases. The addition of contourlet-based MRI texture features to multivariant models can effectively improve the classification of AD and the prediction of MCI conversion to AD. Both GPR and LPS models performed well in the classification and predictive process, with the latter having significantly higher classification and predictive accuracies. Advances in knowledge: We combined contourlet-based hippocampal MRI texture features, medical histories, symptoms, neuropsychological tests, volume-based morphometric (VBM) parameters, and regional CMgl measurement to develop models using GP and PLS algorithms to classify AD patients.

Socio-Economic Predictors and Distribution of Tuberculosis Incidence in Beijing, China: A Study Using a Combination of Spatial Statistics and GIS Technology.

Evidence shows that multiple factors, such as socio-economic status and access to health care facilities, affect tuberculosis (TB) incidence. However, there is limited literature available with respect to the correlation between socio-economic/health facility factors and tuberculosis incidence. This study aimed to explore the relationship between TB incidence and socio-economic/health service predictors in the study settings. A retrospective spatial regression analysis was carried out based on new sputum smear-positive pulmonary TB cases in Beijing districts. Global Moran's I analysis was adopted to detect the spatial dependency followed by spatial regression models (spatial lag model, and spatial error model) along with the ordinary least square model were applied to examine the correlation between TB incidence and predictors. A high incidence of TB was seen in densely populated districts in Beijing, e.g., Haidian, Mentougou, and Xicheng. After comparing the R², log-likelihood, and Akaike information criterion (AIC) values among three models, the spatial error model (R² = 0.413; Log Likelihood = -591; AIC = 1199.76) identified the best model fit for the spatial regression model. The study showed that the number of beds in health institutes (p < 0.001) and per capita gross domestic product (GDP) (p = 0.025) had a positive effect on TB incidence, whereas population density (p < 0.001) and migrated population (p < 0.001) had an adverse impact on TB incidence in the study settings. High TB incidence districts were detected in urban and densely populated districts in Beijing. Our findings suggested that socio-economic predictors influence TB incidence. These findings may help to guide TB control programs and promote targeted intervention.

The Association between Environmental Factors and Scarlet Fever Incidence in Beijing Region: Using GIS and Spatial Regression Models.

(1) Background: Evidence regarding scarlet fever and its relationship with meteorological, including air pollution factors, is not very available. This study aimed to examine the relationship between ambient air pollutants and meteorological factors with scarlet fever occurrence in Beijing, China. (2) Methods: A retrospective ecological study was carried out to distinguish the epidemic characteristics of scarlet fever incidence in Beijing districts from 2013 to 2014. Daily incidence and corresponding air pollutant and meteorological data were used to develop the model. Global Moran's I statistic and Anselin's local Moran's I (LISA) were applied to detect the spatial autocorrelation (spatial dependency) and clusters of scarlet fever incidence. The spatial lag model (SLM) and spatial error model (SEM) including ordinary least squares (OLS) models were then applied to probe the association between scarlet fever incidence and meteorological including air pollution factors. (3) Results: Among the 5491 cases, more than half (62%) were male, and more than one-third (37.8%) were female, with the annual average incidence rate 14.64 per 100,000 population. Spatial autocorrelation analysis exhibited the existence of spatial dependence; therefore, we applied spatial regression models. After comparing the values of R-square, log-likelihood and the Akaike information criterion (AIC) among the three models, the OLS model (R² = 0.0741, log likelihood = -1819.69, AIC = 3665.38), SLM (R² = 0.0786, log likelihood = -1819.04, AIC = 3665.08) and SEM (R² = 0.0743, log likelihood = -1819.67, AIC = 3665.36), identified that the spatial lag model (SLM) was best for model fit for the regression model. There was a positive significant association between nitrogen oxide (p = 0.027), rainfall (p = 0.036) and sunshine hour (p = 0.048), while the relative humidity (p = 0.034) had an adverse association with scarlet fever incidence in SLM. (4) Conclusions: Our findings indicated that meteorological, as well as air pollutant factors may increase the incidence of scarlet fever; these findings may help to guide scarlet fever control programs and targeting the intervention.

A competing-risk-based score for predicting twenty-year risk of incident diabetes: the Beijing Longitudinal Study of Ageing study.

Few risk tools have been proposed to quantify the long-term risk of diabetes among middle-aged and elderly individuals in China. The present study aimed to develop a risk tool to estimate the 20-year risk of developing diabetes while incorporating competing risks. A three-stage stratification random-clustering sampling procedure was conducted to ensure the representativeness of the Beijing elderly. We prospectively followed 1857 community residents aged 55 years and above who were free of diabetes at baseline examination. Sub-distribution hazards models were used to adjust for the competing risks of non-diabetes death. The cumulative incidence function of twenty-year diabetes event rates was 11.60% after adjusting for the competing risks of non-diabetes death. Age, body mass index, fasting plasma glucose, health status, and physical activity were selected to form the score. The area under the ROC curve (AUC) was 0.76 (95% Confidence Interval: 0.72-0.80), and the optimism-corrected AUC was 0.78 (95% Confidence Interval: 0.69-0.87) after internal validation by bootstrapping. The calibration plot showed that the actual diabetes risk was similar to the predicted risk. The cut-off value of the risk score was 19 points, marking mark the difference between low-risk and high-risk patients, which exhibited a sensitivity of 0.74 and specificity of 0.65.

Prediction of the 20-year incidence of diabetes in older Chinese: Application of the competing risk method in a longitudinal study.

The competing risk method has become more acceptable for time-to-event data analysis because of its advantage over the standard Cox model in accounting for competing events in the risk set. This study aimed to construct a prediction model for diabetes using a subdistribution hazards model.We prospectively followed 1857 community residents who were aged ≥ 55 years, free of diabetes at baseline examination from August 1992 to December 2012. Diabetes was defined as a self-reported history of diabetes diagnosis, taking antidiabetic medicine, or having fasting plasma glucose (FPG) ≥ 7.0 mmol/L. A questionnaire was used to measure diabetes risk factors, including dietary habits, lifestyle, psychological factors, cognitive function, and physical condition. Gray test and a subdistribution hazards model were used to construct a prediction algorithm for 20-year risk of diabetes. Receiver operating characteristic (ROC) curves, bootstrap cross-validated Wolber concordance index (C-index) statistics, and calibration plots were used to assess model performance.During the 20-year follow-up period, 144 cases were documented for diabetes incidence with a median follow-up of 10.9 years (interquartile range: 8.0-15.3 years). The cumulative incidence function of 20-year diabetes incidence was 11.60% after adjusting for the competing risk of nondiabetes death. Gray test showed that body mass index, FPG, self-rated heath status, and physical activity were associated with the cumulative incidence function of diabetes after adjusting for age. Finally, 5 standard risk factors (poor self-rated health status [subdistribution hazard ratio (SHR) = 1.73, P = 0.005], less physical activity [SHR = 1.39, P = 0.047], 55-65 years old [SHR = 4.37, P < 0.001], overweight [SHR = 2.15, P < 0.001] or obesity [SHR = 1.96, P = 0.003], and impaired fasting glucose [IFG] [SHR = 1.99, P < 0.001]) were significantly associated with incident diabetes. Model performance was moderate to excellent, as indicated by its bootstrap cross-validated discrimination C-index (0.74, 95% CI: 0.70-0.79) and calibration plot.Poor self-rated health, physical inactivity, being 55 to 65 years of age, overweight/obesity, and IFG were significant predictors of incident diabetes. Early prevention with a goal of achieving optimal levels of all risk factors should become a key element of diabetes prevention.

An association of platelet indices with blood pressure in Beijing adults: Applying quadratic inference function for a longitudinal study.

The quadratic inference function (QIF) method becomes more acceptable for correlated data because of its advantages over generalized estimating equations (GEE). This study aimed to evaluate the relationship between platelet indices and blood pressure using QIF method, which has not been studied extensively in real data settings.A population-based longitudinal study was conducted in Beijing from 2007 to 2012, and the median of follow-up was 6 years. A total of 6515 cases, who were aged between 20 and 65 years at baseline and underwent routine physical examinations every year from 3 Beijing hospitals were enrolled to explore the association between platelet indices and blood pressure by QIF method. The original continuous platelet indices were categorized into 4 levels (Q1-Q4) using the 3 quartiles of P25, P50, and P75 as a critical value. GEE was performed to make a comparison with QIF.After adjusting for age, usage of drugs, and other confounding factors, mean platelet volume was negatively associated with diastolic blood pressure (DBP) (Equation is included in full-text article.)in males and positively linked with systolic blood pressure (SBP) (Equation is included in full-text article.). Platelet distribution width was negatively associated with SBP (Equation is included in full-text article.). Blood platelet count was associated with DBP (Equation is included in full-text article.)in males.Adults in Beijing with prolonged exposure to extreme value of platelet indices have elevated risk for future hypertension and evidence suggesting using some platelet indices for early diagnosis of high blood pressure was provided.