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.

Longitudinal association of remnant cholesterol with joint arteriosclerosis and atherosclerosis progression beyond LDL cholesterol.

BACKGROUND: Arteriosclerosis and atherosclerosis are closely related with cardiovascular disease (CVD) risk. Remnant cholesterol (RC) could predict CVD. However, its effect on joint arteriosclerosis and atherosclerosis progression remains unclear. This study aims to evaluate the association of RC with joint arteriosclerosis and atherosclerosis progression trajectories in the general population. METHODS: This study collected data across five biennial surveys of the Beijing Health Management Cohort from 2010 to 2019. Multi-trajectory model was used to determine the joint arteriosclerosis and atherosclerosis progression patterns by brachial-ankle pulse wave velocity (baPWV) and ankle brachial index (ABI). We also performed discordance analyses for RC vs. low density lipoprotein cholesterol (LDL-C) using ordinal logistics model. RESULTS: A total of 3186 participants were included, with three clusters following distinct arteriosclerosis and atherosclerosis progression patterns identified using a multi-trajectory model. In the multivariable-adjusted ordinal logistics analyses, RC was significantly associated with baPWV and ABI progression (OR: 1.20; 95% CI: 1.13-1.28, per 10 mg/dL). For the discordance analyses, the discordant low RC group was associated with decreased risk compared to the concordant group (OR: 0.73; 95% CI: 0.60-0.89). People with a high RC level were at an increased risk of joint arteriosclerosis and atherosclerosis progression, even with optimal LDL-C. CONCLUSIONS: RC is independently associated with joint arteriosclerosis and atherosclerosis progression beyond LDL-C. RC could be an earlier risk factor than LDL-C of arteriosclerosis and atherosclerosis in the general population.

Association of impaired sensitivity to thyroid hormones with hyperuricemia through obesity in the euthyroid population.

BACKGROUND: Impaired sensitivity to thyroid hormones is a newly proposed clinical entity associated with hyperuricemia in the subclinical hypothyroid population. However, it is unknown whether the association exists in the euthyroid population. This study aimed to explore the association of impaired sensitivity to thyroid hormones (assessed by the thyroid feedback quantile-based index [TFQI], parametric thyroid feedback quantile-based index [PTFQI], thyrotrophic thyroxine resistance index [TT4RI] and thyroid-stimulating hormone index [TSHI]) with hyperuricemia and quantify the mediating effect of body mass index BMI in the euthyroid population. METHODS: This cross-sectional study enrolled Chinese adults aged ≥ 20 years who participated in the Beijing Health Management Cohort (2008-2019). Adjusted logistic regression models were used to explore the association between indices of sensitivity to thyroid hormones and hyperuricemia. Odds ratios [OR] and absolute risk differences [ARD] were calculated. Mediation analyses were performed to estimate direct and indirect effects through BMI. RESULTS: Of 30,857 participants, 19,031 (61.7%) were male; the mean (SD) age was 47.3 (13.3) years; and 6,515 (21.1%) had hyperuricemia. After adjusting for confounders, individuals in the highest group of thyroid hormone sensitivity indices were associated with an increased prevalence of hyperuricemia compared with the lowest group (TFQI: OR = 1.18, 95% CI 1.04-1.35; PTFQI: OR = 1.20, 95% CI 1.05-1.36; TT4RI: OR = 1.17, 95% CI 1.08-1.27; TSHI: OR = 1.12, 95% CI 1.04-1.21). BMI significantly mediated 32.35%, 32.29%, 39.63%, and 37.68% of the associations of TFQI, PTFQI, TT4RI and TSHI with hyperuricemia, respectively. CONCLUSIONS: Our research revealed that BMI mediated the association between impaired sensitivity to thyroid hormones and hyperuricemia in the euthyroid population. These findings could provide useful evidence for understanding the interaction between impaired sensitivity to thyroid hormone and hyperuricemia in euthyroid individuals and suggest the clinical implications of weight control in terms of impaired thyroid hormones sensitivity.

Intraindividual difference in estimated GFR by creatinine and cystatin C, cognitive trajectories and motoric cognitive risk syndrome.

BACKGROUND: Intraindividual differences between estimated glomerular filtration rate (eGFR) based on cystatin C (eGFRcys) and creatinine (eGFRcr) can convey important clinical information regarding the health status. However, the clinical implications of these differences (eGFRdiff) for risk of cognitive decline and motoric cognitive risk syndrome (MCR) remains unclear. We aimed to investigate the longitudinal associations of eGFRdiff with cognitive trajectories and incident MCR. METHODS: Based on the China Health and Retirement Longitudinal Study, we identified two study sub-cohorts: one for cognitive trajectory follow-up (6423 participants; years:2011-2018) and another for incident MCR follow-up (2477 participants; years:2011-2015). The eGFRdiff was defined as eGFRcys minus eGFRcr. Adjusted ordinal and binary logistics regression models were separately used to assess the associations of eGFRdiff with cognitive trajectories and incident MCR. We also performed discordance analyses for eGFRdiff vs eGFRcys, eGFRcr or eGFR based on both creatinine and cystatin C (eGFRcys-cr). RESULTS: In the first sub-cohort, four distinct 7-year cognitive trajectories were identified. Each 1-SD higher eGFRdiff (value for eGFRcys minus eGFRcr) was associated with a lower risk of poorer cognitive trajectories (OR: 0.909, 95% CI: 0.877-0.942). In the second sub-cohort, 121 participants developed incident MCR after a 4-year follow-up. Each 1-SD higher eGFRdiff (value for eGFRcys minus eGFRcr) was linked with a 25.3% (95%CI: 16.6%-33.2%) decreased risk for MCR. The above associations persisted in individuals with normal kidney function. Additionally, the risk for cognitive decline and incident MCR was more strongly associated with eGFRcys than eGFRcr and eGFRcys-cr. For the discordance analyses, 'discordantly high eGFRdiff/low eGFR' group, but not 'discordantly low eGFRdiff/high eGFR', exhibited a significantly lower risk of poorer cognitive trajectories and MCR compared to the concordant group. CONCLUSIONS: A large negative difference between eGFRcys and eGFRcr (eGFRcys lower than eGFRcr) was associated with higher risk of cognitive decline and incident MCR. The eGFRdiff could capture additional valuable risk information beyond eGFRcys, eGFRcr, and eGFRcys-cr.

Bidirectional relationship between nonalcoholic fatty liver disease and serum creatinine-to-body weight ratio as a proxy for skeletal muscle mass index.

BACKGROUND AND AIM: Although an association between skeletal muscle mass index and nonalcoholic fatty liver disease (NAFLD) has previously been demonstrated, the causal direction remains unclear. Herein, we investigated the directional association between NAFLD and the serum creatinine-to-body weight ratio (sCr/bw), a surrogate marker of the muscle mass index, using longitudinal data. METHODS: We recruited 9662 participants in 2017 and performed follow-up over 4 years. We evaluated whether sCr/bw was related to NAFLD development (Analysis I) and whether NAFLD was associated with a low sCr/bw incidence (Analysis II) using logistic regression models. Furthermore, a random intercept cross-lagged panel model was applied to evaluate the bidirectional association between sCr/bw ratio and NAFLD (Analysis III). RESULTS: Analysis I demonstrated an association between sCr/bw and incident NAFLD (odds ratio [OR] = 0.160, 95% confidence interval [CI]:0.107-0.232). Analysis II indicated a relationship between NAFLD and subsequent low sCr/bw ratio (OR = 1.524, 95% CI: 1.258-1.846). Analysis III indicated that the standard regression coefficient from sCr/bw to subsequent hepatic steatosis (HS) was -0.053 for ßsCr/bw2017 â†’ HS2019 and -0.060 for ßsCr/bw2019 â†’ HS2021 and the coefficient from HS to subsequent sCr/bw was -0.093 for ßHS2017 â†’ sCr/bw2019 and -0.112 for ßHS2019 â†’ sCr/bw2021 (all P < 0.05). CONCLUSIONS: This study indicated mutual causality between sCr/bw and NAFLD. Considering that sCr/bw is a surrogate marker of muscle mass index, the findings emphasize that NAFLD and low muscle mass form a vicious cycle, which should be taken seriously in clinical practice.

Long-term effects of PM2.5 components on hypertension: A national analysis in China.

BACKGROUND: Evidence is less about the associations between fine particulate matter (PM2.5) components and hypertension. We aimed to examine the long-term effects of PM2.5 components on prevalence of hypertension, diastolic blood pressure (DBP) and systolic blood pressure (SBP). METHODS: We included participants between March 1, and July 31, 2021, from 13 provinces in China. Geocoded residential address was used for exposure assignment. Mixed-effect regression was used to assess 3-year average concentrations of PM2.5 and its components (black carbon, organic matter, nitrate, ammonium, and sulfate) on prevalence of hypertension, DBP and SBP with covariate-adjusted. SHapley Additive exPlanation was used to compare the contribution of PM2.5 components to hypertension, DBP, and SBP. Sex and age subgroup were also analyzed. RESULTS: We enrolled a total of 113,159 participants aged ≥18 years. Long-term exposure to PM2.5 and its components (black carbon, organic matter, nitrate, ammonium, and sulfate) had associations with prevalence of hypertension, with the Odds Ratios and 95% confidence interval (CI) of 1.06 (95%CI: 1.03-1.09), 1.07 (95%CI: 1.04-1.09), 1.07 (95%CI: 1.04-1.10), 1.05 (95%CI: 1.01-1.08), 1.03 (95%CI: 1.00-1.06), and 1.03 (95%CI: 1.00-1.04), respectively. Effects of that except for black carbon on DBP with per interquartile upticks of concentration were 0.23 (95%CI: 0.11-0.35), 0.17 (95%CI: 0.04-0.29), 0.35 (95%CI: 0.21-0.48), 0.40 (95%CI: 0.28-0.52), and 0.25 (95%CI: 0.13-0.26), respectively. Ammonium was associated with SBP, corresponding to an increase of 0.18 (95%CI: 0.01-0.35). Males had higher risks of DBP (Z = 2.54-6.08, P < 0.001). Older people were substantially more affected by PM2.5 and its components. Nitrate showed the highest contribution to hypertension, DBP and SBP compared with other components. CONCLUSIONS: Long-term exposure to PM2.5 and its components had adverse consequences on prevalence of hypertension, DBP and SBP, especially for males and older people. Nitrate contributed the highest to hypertension, DBP and SBP. Findings may have implications for pollution and hypertension control.

Causal effect of PM1 on morbidity of cause-specific respiratory diseases based on a negative control exposure.

BACKGROUND: Extensive studies have linked PM2.5 and PM10 with respiratory diseases (RD). However, few is known about causal association between PM1 and morbidity of RD. We aimed to assess the causal effects of PM1 on cause-specific RD. METHODS: Hospital admission data were obtained for RD during 2014 and 2019 in Beijing, China. Negative control exposure and extreme gradient boosting with SHapley Additive exPlanation was used to explore the causality and contribution between PM1 and RD. Stratified analysis by gender, age, and season was conducted. RESULTS: A total of 1,183,591 admissions for RD were recorded. Per interquartile range (28 µg/m3) uptick in concentration of PM1 corresponded to a 3.08% [95% confidence interval (CI): 1.66%-4.52%] increment in morbidity of total RD. And that was 4.47% (95% CI: 2.46%-6.52%) and 0.15% (95% CI: 1.44%-1.78%), for COPD and asthma, respectively. Significantly positive causal associations were observed for PM1 with total RD and COPD. Females and the elderly had higher effects on total RD, COPD, and asthma only in the warm months (Z = 3.03, P = 0.002; Z = 4.01, P < 0.001; Z = 3.92, P < 0.001; Z = 2.11, P = 0.035; Z = 2.44, P = 0.015). Contribution of PM1 ranked first, second and second for total RD, COPD, and asthma among air pollutants. CONCLUSION: PM1 was causally associated with increased morbidity of total RD and COPD, but not causally associated with asthma. Females and the elderly were more vulnerable to PM1-associated effects on RD.

Associations of time-weighted individual exposure to ambient particulate matter with carotid atherosclerosis in Beijing, China.

BACKGROUND: Time-location information (time spent on commuting, indoors and outdoors around residential and work places and physical activity) and infiltrated outdoor pollution was less considered estimating individual exposure to ambient air pollution. Studies investigating the association between individual exposure to particulate matter (PM) with aerodynamic diameter < 10 µm (PM10) and < 2.5 µm (PM2.5) and carotid atherosclerosis presented inconsistent results. Moreover, combined effect of pollutants on carotid atherosclerosis was not fully explored. We aimed to investigate the association between long-term individual time-weighted average exposure to PM2.5 and PM10 and the risk of carotid atherosclerosis, and further explore the overall effect of co-exposure to pollutants on carotid atherosclerosis. METHODS: The study population included 3069 participants derived from the Beijing Health Management Cohort (BHMC) study. Daily concentration of ambient air pollutants was estimated by land-use regression model at both residential and work addresses, and one- and two-year time-weighted average individual exposure was calculated by further considering personal activity pattern and infiltration of ambient air pollution indoors. We explored the association of PM2.5 and PM10 with carotid atherosclerosis and pooled the overall effect of co-exposure to ambient air pollutants by quantile g-computation. RESULTS: A significant association between time-weighted average exposure to PM2.5 and PM10 and carotid atherosclerosis was observed. Per interquartile range increase in two-year exposure to PM2.5 (Hazard ratio (HR): 1.322, 95% confidence interval (CI): 1.219-1.434) and PM10 (HR:1.213, 95% CI: 1.116-1.319) showed the strongest association with carotid atherosclerosis, respectively. Individuals in higher quartiles of pollutants were at higher risk for carotid atherosclerosis compared with those in the lowest quartile group. Concentration response functions documented the nearly linear and nonlinear relationship and interpreted the upward trends of the risk for carotid atherosclerosis with increasing level of pollutant concentrations. Moreover, effect estimates for the mixture of pollutants and carotid atherosclerosis were larger than any of the individual pollutants (HR (95% CI) was 1.510 (1.338-1.704) and 1.613 (1.428-1.822) per quartile increase for one-year and two-year time-weighted average exposure, respectively). CONCLUSIONS: Individual time-weighted average exposure to PM2.5 and PM10 was associated with carotid atherosclerosis. Co-exposure to ambient air pollution was also positively associated with carotid atherosclerosis.

Distinct hyperuricemia trajectories are associated with different risks of incident diabetes: A prospective cohort study.

BACKGROUND AND AIM: Conflicting results suggest a link between serum uric acid and diabetes and previous studies ignored the effect of continuous exposure of serum uric acid on diabetes risk. This study aims to characterize hyperuricemia trajectories in middle-aged adults and to examine its potential impact on diabetes risk, considering the role of obesity, dyslipidemia, and hypertension. METHODS AND RESULTS: The cohort included 9192 participants who were free of diabetes before 2013. The hyperuricemia trajectories during 2009-2013 were identified by latent class growth models. Incident diabetes during 2014-2018 was used as the outcome. Modified Poisson regression models were used to assess the association of trajectories with diabetes. Furthermore, marginal structural models were used to estimate the mediating effects of the relationship between hyperuricemia trajectories and diabetes. We identified three discrete hyperuricemia trajectories: high-increasing (n = 5794), moderate-stable (n = 2049), and low-stable (n = 1349). During 5 years of follow-up, we documented 379 incident diabetes cases. Compared with the low-stable pattern, the high-increasing pattern had a higher risk of developing diabetes (RR, 1.42; 95% CI: 1.09-1.84). In addition, the percentages of total effect between the high-increasing hyperuricemia pattern and diabetes mediated by obesity, dyslipidemia, and hypertension were 24.41%, 18.26%, and 6.29%. However, the moderate-stable pattern was not associated with an increased risk of diabetes. CONCLUSIONS: These results indicate that the high-increasing hyperuricemia trajectory is significantly associated with an increased risk of diabetes. Furthermore, obesity, dyslipidemia, and hypertension play mediating roles in the relationship between the high-increasing hyperuricemia pattern and increased diabetes risk.

Deep-Learning Model of ResNet Combined with CBAM for Malignant-Benign Pulmonary Nodules Classification on Computed Tomography Images.

Background and Objectives: Lung cancer remains a leading cause of cancer mortality worldwide. Accurately classifying benign pulmonary nodules and malignant ones is crucial for early diagnosis and improved patient outcomes. The purpose of this study is to explore the deep-learning model of ResNet combined with a convolutional block attention module (CBAM) for the differentiation between benign and malignant lung cancer, based on computed tomography (CT) images, morphological features, and clinical information. Methods and materials: In this study, 8241 CT slices containing pulmonary nodules were retrospectively included. A random sample comprising 20% (n = 1647) of the images was used as the test set, and the remaining data were used as the training set. ResNet combined CBAM (ResNet-CBAM) was used to establish classifiers on the basis of images, morphological features, and clinical information. Nonsubsampled dual-tree complex contourlet transform (NSDTCT) combined with SVM classifier (NSDTCT-SVM) was used as a comparative model. Results: The AUC and the accuracy of the CBAM-ResNet model were 0.940 and 0.867, respectively, in test set when there were only images as inputs. By combining the morphological features and clinical information, CBAM-ResNet shows better performance (AUC: 0.957, accuracy: 0.898). In comparison, a radiomic analysis using NSDTCT-SVM achieved AUC and accuracy values of 0.807 and 0.779, respectively. Conclusions: Our findings demonstrate that deep-learning models, combined with additional information, can enhance the classification performance of pulmonary nodules. This model can assist clinicians in accurately diagnosing pulmonary nodules in clinical practice.

Association of visceral adiposity index with incident nephropathy and retinopathy: a cohort study in the diabetic population.

BACKGROUND: The association between visceral adiposity index (VAI) and diabetic complications has been reported in cross-sectional studies, while the effect of VAI on complication development remains unclear. This study aims to evaluate the longitudinal association of VAI and Chinese VAI (CVAI) with the incidence of diabetic nephropathy and retinopathy using a Chinese cohort. METHODS: A total of 8 948 participants with type 2 diabetes from Beijing Health Management Cohort were enrolled during 2013-2014, and followed until December 31, 2019. Nephropathy was confirmed by urine albumin/creatinine ratio and estimated glomerular filtration rate; retinopathy was diagnosed using fundus photograph. RESULTS: The mean (SD) age was 53.35 (14.66) years, and 6 154 (68.8%) were men. During a median follow-up of 4.82 years, 467 participants developed nephropathy and 90 participants developed retinopathy. One-SD increase in VAI and CVAI levels were significantly associated with an increased risk of nephropathy, and the adjusted hazard ratios (HR) were 1.127 (95% CI 1.050-1.210) and 1.165 (95% CI 1.003-1.353), respectively. On contrary, VAI and CVAI level were not associated with retinopathy after adjusting confounding factors. CONCLUSION: VAI and CVAI are independently associated with the development of nephropathy, but not retinopathy in Chinese adults with diabetes.

Combined evaluation of arterial stiffness, glycemic control and hypertension for macrovascular complications in type 2 diabetes.

BACKGROUND: Arterial stiffness, glycemic control and blood pressure are risk factors of macrovascular complications in type 2 diabetes. This study aimed to investigate the combined association of arterial stiffness, glycemic control and hypertension status with the occurrence of diabetic macrovascular complication. METHODS: A total of 1870 patients of diabetes were enrolled from Beijing Health Management Cohort between 2008 and 2018 as baseline, and then followed for macrovascular complication onset. We proposed a composite risk score (0-4) by arterial stiffness severity, pool glycemic control and hypertension status. Cox model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI). RESULTS: The mean age (SD) of this population was 59.90 (12.29) years. During a median follow-up of 4.0 years, 359 (19.2%) patients developed macrovascular complication. Compared to the normal arterial stiffness and good glycemic control group, patients with severe arterial stiffness and pool glycemic control had the highest risk of macrovascular complications (HR: 2.73; 95% CI: 1.42-5.25). Similarly, those of severe arterial stiffness and hypertension had the highest risk (HR: 2.69; 95% CI: 1.61-4.50). Patients of the composite score > 2 had a significantly increased risk of macrovascular complication. CONCLUSION: This study suggested the clinical importance of combined evaluation of arterial stiffness, glycemic control and hypertension status for the risk stratification and management of macrovascular complication of type 2 diabetes.

Establishment of dynamic nomogram and risk score models for T2DM: a retrospective cohort study in Beijing.

BACKGROUND: Health interventions can delay or prevent the occurrence and development of diabetes. Dynamic nomogram and risk score (RS) models were developed to predict the probability of developing type 2 diabetes mellitus (T2DM) and identify high-risk groups. METHODS: Participants (n = 44,852) from the Beijing Physical Examination Center were followed up for 11 years (2006-2017); the mean follow-up time was 4.06 ± 2.09 years. Multivariable Cox regression was conducted in the training cohort to identify risk factors associated with T2DM and develop dynamic nomogram and RS models using weighted estimators corresponding to each covariate derived from the fitted Cox regression coefficients and variance estimates, and then undergone internal validation and sensitivity analysis. The concordance index (C-index) was used to assess the accuracy and reliability of the model. RESULTS: Of the 44,852 individuals at baseline, 2,912 were diagnosed with T2DM during the follow-up period, and the incidence density rate per 1,000 person-years was 16.00. Multivariate analysis indicated that male sex (P < 0.001), older age (P < 0.001), high body mass index (BMI, P < 0.05), high fasting plasma glucose (FPG, P < 0.001), hypertension (P = 0.015), dyslipidaemia (P < 0.001), and low serum creatinine (sCr, P < 0.05) at presentation were risk factors for T2DM. The dynamic nomogram achieved a high C-index of 0.909 in the training set and 0.905 in the validation set. A tenfold cross-validation estimated the area under the curve of the nomogram at 0.909 (95% confidence interval 0.897-0.920). Moreover, the dynamic nomogram and RS model exhibited acceptable discrimination and clinical usefulness in subgroup and sensitivity analyses. CONCLUSIONS: The T2DM dynamic nomogram and RS models offer clinicians and others who conduct physical examinations, respectively, simple-to-use tools to assess the risk of developing T2DM in the urban Chinese current or retired employees.

Research on prediction of daily admissions of respiratory diseases with comorbid diabetes in Beijing based on long short-term memory recurrent neural network.

To compare the performance of generalized additive model (GAM) and long short-term memory recurrent neural network (LSTM-RNN) on the prediction of daily admissions of respiratory diseases with comorbid diabetes. Daily data on air pollutants, meteorological factors and hospital admissions for respiratory diseases from Jan 1st, 2014 to Dec 31st, 2019 in Beijing were collected. LSTM-RNN was used to predict the daily admissions of respiratory diseases with comorbid diabetes, and the results were compared with those of GAM. The evaluation indexes were calculated by five-fold cross validation. Compared with the GAM, the prediction errors of LSTM-RNN were significantly lower [root mean squared error (RMSE): 21.21±3.30 vs. 46.13±7.60, <0.01; mean absolute error (MAE): 14.64±1.99 vs. 36.08±6.20, <0.01], and the value was significantly higher (0.79±0.06 vs. 0.57±0.12, <0.01). In gender stratification, RMSE, MAE and values of LSTM-RNN were better than those of GAM in predicting female admission (all <0.05), but there were no significant difference in predicting male admission between two models (all >0.05). In seasonal stratification, RMSE and MAE of LSTM-RNN were lower than those of GAM in predicting warm season admission (all <0.05), but there was no significant difference in value (>0.05). There were no significant difference in RMSE, MAE and between the two models in predicting cold season admission (all >0.05). In the stratification of functional areas, the RMSE, MAE and values of LSTM-RNN were better than those of GAM in predicting core area admission (all <0.05). has lower prediction errors and better fitting than the GAM, which can provide scientific basis for precise allocation of medical resources in polluted weather in advance.

Association of TyG index and TG/HDL-C ratio with arterial stiffness progression in a non-normotensive population.

BACKGROUND: Cross-sectional studies have reported that insulin resistance (IR) is associated with arterial stiffness. However, the relationship between IR and arterial stiffness progression remains unclear. This study aims to evaluate the association of triglyceride glucose (TyG) index and triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio with arterial stiffness progression in a non-normotensive population. METHODS: A total of 1895 prehypertensive (systolic pressure 120-139 mmHg or diastolic pressure 80-90 mmHg) or hypertensive (systolic pressure ≥ 140 mmHg or diastolic pressure ≥ 90 mmHg or using antihypertensive medication) participants were enrolled in 2013 and 2014, and followed until December 31, 2019. Arterial stiffness progression was measured by brachial-ankle pulse wave velocity (baPWV) change (absolute difference between baseline and last follow-up), baPWV change rate (change divided by following years), and baPWV slope (regression slope between examination year and baPWV). RESULTS: During a median follow-up of 4.71 years, we observed an increasing trend of baPWV in the population. There were linear and positive associations of the TyG index and TG/HDL-C ratio with the three baPWV parameters. The difference (95% CI) in baPWV change (cm/s) comparing participants in the highest quartile versus the lowest of TyG index and TG/HDL-C ratio were 129.5 (58.7-200.0) and 133.4 (52.0-214.9), respectively. Similarly, the evaluated baPWV change rates (cm/s/year) were 37.6 (15.3-60.0) and 43.5 (17.8-69.2), while the slopes of baPWV were 30.6 (9.3-51.8) and 33.5 (9.0-58.0). The observed association was stronger in the hypertensive population. CONCLUSION: Our study indicates that the TyG index and TG/HDL-C ratio are significantly associated with arterial stiffness progression in hypertensive population, not in prehypertensive population.

Histologic subtype classification of non-small cell lung cancer using PET/CT images.

PURPOSES: To evaluate the capability of PET/CT images for differentiating the histologic subtypes of non-small cell lung cancer (NSCLC) and to identify the optimal model from radiomics-based machine learning/deep learning algorithms. METHODS: In this study, 867 patients with adenocarcinoma (ADC) and 552 patients with squamous cell carcinoma (SCC) were retrospectively analysed. A stratified random sample of 283 patients (20%) was used as the testing set (173 ADC and 110 SCC); the remaining data were used as the training set. A total of 688 features were extracted from each outlined tumour region. Ten feature selection techniques, ten machine learning (ML) models and the VGG16 deep learning (DL) algorithm were evaluated to construct an optimal classification model for the differential diagnosis of ADC and SCC. Tenfold cross-validation and grid search technique were employed to evaluate and optimize the model hyperparameters on the training dataset. The area under the receiver operating characteristic curve (AUROC), accuracy, precision, sensitivity and specificity was used to evaluate the performance of the models on the test dataset. RESULTS: Fifty top-ranked subset features were selected by each feature selection technique for classification. The linear discriminant analysis (LDA) (AUROC, 0.863; accuracy, 0.794) and support vector machine (SVM) (AUROC, 0.863; accuracy, 0.792) classifiers, both of which coupled with the ℓ2,1NR feature selection method, achieved optimal performance. The random forest (RF) classifier (AUROC, 0.824; accuracy, 0.775) and ℓ2,1NR feature selection method (AUROC, 0.815; accuracy, 0.764) showed excellent average performance among the classifiers and feature selection methods employed in our study, respectively. Furthermore, the VGG16 DL algorithm (AUROC, 0.903; accuracy, 0.841) outperformed all conventional machine learning methods in combination with radiomics. CONCLUSION: Employing radiomic machine learning/deep learning algorithms could help radiologists to differentiate the histologic subtypes of NSCLC via PET/CT images.

Risk factors for esophageal squamous cell carcinoma and its histological precursor lesions in China: a multicenter cross-sectional study.

BACKGROUND: Despite research efforts, the causative factors that contribute to esophageal squamous cell carcinoma (ESCC) in high-risk areas have not yet been understood. In this study, we, therefore, aimed to describe the risk factors associated with ESCC and its precursor lesions. METHODS: We performed an endoscopic examination of 44,857 individuals aged 40-69 years from five high incidence regions of China in 2017-2018. Participants were classified as 4 groups of normal control, esophagitis, low-grade intraepithelial neoplasia (LGIN) and high-grade intraepithelial neoplasia/esophageal squamous cell carcinoma (HGIN/ESCC) using an unconditional logistic regression determine risk factors. RESULTS: We identified 4890 esophagitis, 1874 LGIN and 437 HGIN/ESCC cases. Crude odds ratios (ORs) and adjusted odds ratios were calculated using unconditional logistic regression. Drinking well and surface water, salty diet, and positive family history of cancer were the common risk factors for esophagitis, LGIN and HGIN/ESCC. History of chronic hepatitis/cirrhosis was the greatest risk factor of esophagitis (adjusted OR 2.96, 95%CI 2.52-3.47) and HGIN/ESCC (adjusted OR 1.91, 95%CI 1.03-3.22). Pesticide exposure (adjusted OR 1.20, 95%CI 1.05-1.37) was essential risk factor of LGIN. CONCLUSIONS: Among individuals aged 40-69 years in high incidence regions of upper gastrointestinal cancer, the results provided important epidemiological evidence for the prevention of different precancerous lesions of ESCC.

Long-term effects of fine particulate matter exposure on the progression of arterial stiffness.

BACKGROUND: Prior studies have investigated the association of PM2.5 exposure with arterial stiffness measured by ankle-brachial index (ABI) and brachial-ankle pulse wave velocity (baPWV), of which conclusions are inconsistent. Moreover, limited evidence is available on the contributory role of PM2.5 exposure on the arterial stiffness index. METHODS: We used the population data from the Beijing Health Management Cohort and conducted a longitudinal analysis. The annual average concentration of PM2.5 for 35 air pollutant monitoring sites in Beijing from 2014 to 2018 was used to estimate individual exposure by different interpolation methods. Multivariate logistic regression and linear regression were conducted to assess the association of annual average PM2.5 concentration with the incidence of higher baPWV, the progression of ABI, and baPWV, respectively. RESULTS: The association between PM2.5 exposure and incidence of higher baPWV was not significant (OR = 1.11, 95% CI: 0.82-1.50, P = 0.497). There was - 0.16% (95% CI: - 0.43-0.11%) decrease in ABI annually and 1.04% (95% CI: 0.72-1.37%) increase in baPWV annually with each increment of 10 µg/m3 average PM2.5 concentration. CONCLUSIONS: Long-term exposure to PM2.5 was associated with the progression of arterial stiffness in Beijing. This study suggests that improvement of air quality may help to prevent arterial stiffness.

Triglyceride glucose index and carotid atherosclerosis incidence in the Chinese population: A prospective cohort study.

BACKGROUND AND AIMS: The association of the triglyceride glucose (TyG) index with carotid atherosclerosis has not been reported in longitudinal studies. The present study aimed to investigate whether the TyG index increases the risk of carotid atherosclerosis incidence. METHODS AND RESULTS: This study included data from the Beijing Health Management Cohort (BHMC; n = 6955) and the Beijing Physical Examination Cohort (BPEC; n = 8473). Participants without a history of carotid atherosclerosis who underwent health examination in 2011 or 2012 were annually followed until 2019. The TyG index was denoted as ln [triglycerides (mmol/L)∗fasting glucose (mmol/L)/2]. During a median follow-up of 5.02 years and 5.36 years, 1441 individuals in the BHMC group and 2181 individuals in the BPEC group developed carotid plaque, respectively. The adjusted hazard ratios (HRs) of the continuous TyG index were 1.253 (95% CI, 1.044 to 1.505) and 1.252 (95% CI, 1.091 to 1.437) for the BHMC and BPEC groups, respectively. Individuals in the highest quartile of the TyG index were associated with an increased risk of carotid plaque compared with those in the lowest quartile (BHMC: HR, 1.366; 95% CI, 1.101 to 1.695, P for trend = 0.010; BPEC: HR, 1.379; 95% CI, 1.196 to 1.591, P for trend = 0.013). CONCLUSION: These findings suggested that a higher TyG index increases the risk of carotid atherosclerosis incidence in the general population.

Dose-response relationship between distinct serum uric acid trajectories and metabolic syndrome risk: A 5-year prospective cohort study.

BACKGROUND AND AIMS: Although high serum uric acid (SUA) at baseline has been linked to increased risk for metabolic syndrome (MetS), the association of longitudinal SUA changes with MetS risk is unclear. We aimed to examine the effect of distinct SUA trajectories on new-onset MetS risk by sex in a Chinese cohort. METHODS AND RESULTS: A total of 2364 women and 2770 men who were free of MetS in 2013 were enrolled in this study and followed up to 2018. Group-based trajectory modeling was applied to identify SUA trajectories. Cox proportional hazards model was used to evaluate the association between SUA trajectory and new-onset MetS. The dose-response relationship between SUA trajectories and MetS risk was examined by treating trajectory groups as a continuous variable. During a median follow-up of 48.0 months, 311 (13.16%) women and 950 (34.30%) men developed MetS. SUA trajectories (2013-2018) were defined as four distinct patterns in both women and men: "low", "moderate", "moderate-high", and "high". Compared with "low" SUA trajectory, the adjusted hazard ratio for incident MetS among participants with "moderate", "moderate-high" and "high" trajectory was in a dose-response manner: 1.75 (95% CI: 1.08-2.82), 1.94 (95% CI: 1.20-3.14), and 3.05 (95% CI: 1.81-5.13), respectively, for women; 1.20 (95% CI: 0.97-1.49), 1.48 (95% CI: 1.19-1.85), and 1.66 (95% CI: 1.25-2.21), respectively, for men. CONCLUSIONS: Elevated SUA trajectories are associated with increased risk for new-onset MetS in women and men. Monitoring SUA trajectories may assist in identifying subpopulations at higher risk for MetS.