Objective:To construct a risk prediction model of hyperuricemia (HUA) for community-dwelling residents.Methods:This cross-sectional study was conducted from March to November 2020. A total of 1 967 residents in the Nanzhai community of Taiyuan city were selected by stratified sampling method as study subjects, among whom 1 555 (80%) subjects served as the training set and the remaining 412 (20%) as the validation set. Blood uric acid was measured in all subjects and level>420 mmol/L was defined as HUA. The risk factors of HUA were determined with multivariate logistic regression analysis, and a risk prediction model was constructed. The Hosmer-Lemeshow goodness-of-fit test and the receiver operating characteristic (ROC) curve were used to evaluate the predictive performance of the model.Results:Among the 1 555 residents in the training set, HUA was detected in 285 cases (18.3%). The detection rate in men was significantly higher than that in women [29.8% (220/739) vs. 8.0% (65/816), χ 2=123.17, P<0.05]. Compared to non-HUA group, the waist circumference and BMI, and the proportion of smoking, drinking, staying up late, and prevalence of hypertension and dyslipidemia were significant higher in HUA group. There was significant difference in the frequency of drinking tea, coffee, milk, and eating fruits, as well as the amount of beverages consumed between the two groups ( P<0.05). Multivariate logistic regression analysis showed that high BMI ( OR=1.132, 95 %CI:1.070-1.197, P<0.001), coffee consumption ( OR=1.337, 95 %CI:1.027-1.742, P=0.032), and dyslipidemia ( OR=1.479, 95 %CI:1.049-2.086, P=0.025) were risk factors of HUA, while female sex ( OR=0.213, 95 %CI:0.146-0.390, P<0.001) was protective factor of HUA. When all factors were included in the logistic regression model, gender, BMI, coffee consumption, beverage intake, sodium salt intake, sleep quality, and dyslipidemia ( OR=0.213, 1.113, 1.353, 0.788, 1.320, 0.788, 1.651) were important components of the HUA prediction model. By substituting the constant, these factors, and the regression coefficients into the logistic regression equation, the Logit(P) formula was obtained: Logit(P)=-1.530-1.547×gender+0.107×BMI+0.303×coffee consumption frequency-0.238×sodium salt intake+0.278×beverage intake-0.238×sleep quality+0.502×dyslipidemia. The ROC curve showed an area under the curve ( AUC) of 0.750. The Hosmer-Lemeshow goodness-of-fit test: P=0.632, indicating a satisfactory fit. When the formula was applied to the validation set for internal validation, the AUC was 0.745. Conclusion:The occurrence of HUA is influenced by multiple factors. The prediction model constructed in this study has good prediction performance,which may be used to predict the risk of HUA in primary care settings for community-dwelling residents.

Objective:To construct a risk prediction model of hyperuricemia (HUA) for community-dwelling residents.Methods:This cross-sectional study was conducted from March to November 2020. A total of 1 967 residents in the Nanzhai community of Taiyuan city were selected by stratified sampling method as study subjects, among whom 1 555 (80%) subjects served as the training set and the remaining 412 (20%) as the validation set. Blood uric acid was measured in all subjects and level>420 mmol/L was defined as HUA. The risk factors of HUA were determined with multivariate logistic regression analysis, and a risk prediction model was constructed. The Hosmer-Lemeshow goodness-of-fit test and the receiver operating characteristic (ROC) curve were used to evaluate the predictive performance of the model.Results:Among the 1 555 residents in the training set, HUA was detected in 285 cases (18.3%). The detection rate in men was significantly higher than that in women [29.8% (220/739) vs. 8.0% (65/816), χ 2=123.17, P<0.05]. Compared to non-HUA group, the waist circumference and BMI, and the proportion of smoking, drinking, staying up late, and prevalence of hypertension and dyslipidemia were significant higher in HUA group. There was significant difference in the frequency of drinking tea, coffee, milk, and eating fruits, as well as the amount of beverages consumed between the two groups ( P<0.05). Multivariate logistic regression analysis showed that high BMI ( OR=1.132, 95 %CI:1.070-1.197, P<0.001), coffee consumption ( OR=1.337, 95 %CI:1.027-1.742, P=0.032), and dyslipidemia ( OR=1.479, 95 %CI:1.049-2.086, P=0.025) were risk factors of HUA, while female sex ( OR=0.213, 95 %CI:0.146-0.390, P<0.001) was protective factor of HUA. When all factors were included in the logistic regression model, gender, BMI, coffee consumption, beverage intake, sodium salt intake, sleep quality, and dyslipidemia ( OR=0.213, 1.113, 1.353, 0.788, 1.320, 0.788, 1.651) were important components of the HUA prediction model. By substituting the constant, these factors, and the regression coefficients into the logistic regression equation, the Logit(P) formula was obtained: Logit(P)=-1.530-1.547×gender+0.107×BMI+0.303×coffee consumption frequency-0.238×sodium salt intake+0.278×beverage intake-0.238×sleep quality+0.502×dyslipidemia. The ROC curve showed an area under the curve ( AUC) of 0.750. The Hosmer-Lemeshow goodness-of-fit test: P=0.632, indicating a satisfactory fit. When the formula was applied to the validation set for internal validation, the AUC was 0.745. Conclusion:The occurrence of HUA is influenced by multiple factors. The prediction model constructed in this study has good prediction performance,which may be used to predict the risk of HUA in primary care settings for community-dwelling residents.

Juvenile idiopathic arthritis（JIA）is a pediatric rheumatic disease with chronic arthritis as its main manifestation.With the popularization of the treat-to-target（T2T）strategy and the wide use of biologic disease modifying anti-rheumatic drugs in clinical practice，the prognosis of JIA has been significantly improved.In recent years，with the increasing practice of musculoskeletal ultrasound（MSUS）and magnetic resonance imaging（MRI）in clinical diagnosis and treatment，more and more studies have confirmed that they provide clinicians with more sensitive and objective methods in the diagnosis and treatment of JIA，but the more comprehensive and scientific understanding of imaging examination needs to be further improved.This article reviews the application value and progress of MSUS and MRI in making early diagnosis，monitoring disease activity，predicting flare and reaching the T2T of JIA in recent years，so as to facilitate precision medicine approaches and improve prognosis.

Objective:To explore the association between cardiovascular health behaviors and hyperuricemia (HUA) among community residents of different age groups.Methods:It was a cross-sectional study. A total of 2 138 community residents aged (47.1±11.6) years with 1 012 males (47.3%) were selected by cluster sampling method as study subjects in Taiyuan Nanzhai Community from March to November 2020. There were 104 cases aged 8-18 years (underage group), 868 cases aged 19-44 years (youth group), 625 cases aged 45-59 years (middle-aged group), 375 cases aged 60-74 years (young elderly group), and 166 cases aged≥75 years (elderly group). Blood uric acid was measured and>420 μmol/L was defined as HUA, there were 385 cases with high uric acid level (HUA group) and 1 753 cases with normal uric acid levels (control group). The general information was collected by questionnaires, and general ergonomic indicators were measured on-site by medical personnel. The cardiovascular health behaviors included smoking, exercise, diet, and sleep in study subjects were documented. Multivariate logistic regression model was used to analyze the related factors of HUA.Results:Among 2 138 participants, 1 161 (54.3%) had never smoked (up to standard), and the order of proportion of non-smokers from high to low was underage group, elderly group, young elderly group, young group and middle-aged group ( P<0.001); 486(22.7%) people met the dietary standards, and the order of proportion of meeting the dietary standards from high to low was underage group, elderly group, young elderly group, middle-aged group, and young group ( P<0.001); 554(25.9%) people achieved physical fitness standards, and the order of the proportion of achieving physical fitness standards from high to low was young elderly group, middle-aged group, elderly group, underage group, and young group ( P<0.001); 783 (36.6%) people met the sleep standards, and the order of proportion meeting the sleep standards from high to low was underage group, youth group, middle-aged group, young elderly group, and elderly group ( P<0.001). Among the participants, only 39 (1.8%) met the standards for all 4 types of behaviors; 485 (22.7%), 1 229 (57.5%), and 424 (19.8%) had low, medium, and high total scores for ideal cardiovascular health behaviors, respectively. The total score of ideal cardiovascular health behaviors ranked from high to low was elderly group, young elderly group, underage group, middle-aged group, and young group ( P<0.001). The multivariate logistic regression analysis showed that body mass index (BMI) ( OR=1.125, 95% CI: 1.086-1.165) was positively correlated with HUA, while female ( OR=0.241, 95% CI: 0.182-0.320), total score of cardiovascular health behaviors (compared to lower level, intermediate level: OR=0.186, 95% CI: 0.127-0.273, high level: OR=0.038, 95% CI: 0.020-0.072), and number of achieved healthy behavior items ( OR=0.757, 95% CI: 0.621-0.922) were negatively correlated with HUA. Conclusions:The underage group has the highest number of people who meet the smoking, dietary, and sleep standards, the young and elderly group has the highest number of people who meet the exercise standards, and the elderly group has the highest total score for ideal cardiovascular health behaviors. There is a positive correlation between BMI and HUA, while there is a negative correlation of HUA with female, the total score and number of achieved items of cardiovascular health behaviors.

Time in range (TIR) refers to the time or percentage of time within 24 h that glucose levels are in the target range; or the time that blood glucose levels are higher and lower the target range. TIR is a core parameter of continuous glucose monitoring (CGM) and an important indicator for the evaluation of blood glucose in treatment of diabetic patients. Recent studies have confirmed that TIR is closely related to cardiovascular complications of diabetes, and it may become a key indicator for predicting the risk of cardiovascular complications in the future. This article reviews the research progress on the relationship between TIR and cardiovascular complications in diabetic patients, and discusses the value of TIR in the integrated management of diabetes and cardiovascular diseases.

With the increasing prevalence of obesity and diabetes mellitus, the incidence rate of metabolic dysfunction-associated steatotic liver disease (MASLD) is on the rise. MASLD has become the most common chronic liver disease, affecting more than 30% of the global population and causing serious social and economic burden. Numerous studies have shown that the development of MASLD is associated with an increased risk of heart and blood vessel disease (CVD). In 2010, the American Heart Association proposed the concept of ideal cardiovascular health (ICH); in 2022, the scoring criteria were updated with the introduction of the Life′s Essential 8 (LE8), comprising 4 ideal cardiovascular behaviors (optimal diet, exercise, no smoking, mean sleep 7-9 h/d) and 4 ideal cardiovascular conditions (blood pressure<120/80 mmHg (1 mmHg=0.133 kPa) with no medication, no history of diabetes mellitus and fasting blood glucose<5.6 mmol/L or HbA1c<5.7%, non-high density lipoprotein cholesterol<3.36 mmol/L, body mass index<25 kg/m 2). It aims to provide clear, actionable goals for CVD prevention by providing a direct, simple way to quantify health behaviors. A growing number of studies also confirm that the higher level of LE8 metrics is closely associated with the lower risk of MASLD. This article reviews the latest research progress on ICH metrics for reducing risk of MASLD, in order to provide references for early and effective prevention and comprehensive management of MASLD patients.

Diabetes has become a global public health problem due to its high incidence, severe complications and prolonged illness. The ideal cardiovascular health behaviors and factors provide a straightforward and simple way to quantify important health behaviors and factors, and clear and operable targets for cardiovascular disease prevention. A growing number of studies confirm that having more ideal cardiovascular health behaviors and factors is also associated with a lower risk of diabetes. This article reviews the relationship between ideal cardiovascular health behaviors and factors and the occurrence and development of diabetes and its complications, and explores the value of ideal cardiovascular health behaviors and factors in the primary, secondary and tertiary prevention of diabetes.

Objective:To explore the relationship between different components of metabolic syndrome (MS) and their combinations with hyperuricemia (HUA) in community residents.Methods:A cross-sectional survey was conducted from March to November 2020 among 10% residents aged 18 and above selected by cluster sampling method from Nanzhai Community of Taiyuan City. According to serum uric acid levels, the selected individuals were divided into HUA group and non HUA group. The general clinical data of the selected subjects was collected, and routine physical examination and laboratory tests were performed. The serum uric acid levels were detected in fasting blood samples. The association of 5 components (hypertension, hyperglycemia, abdominal obesity, hypertriglyceridemia (TG), and low high-density lipoprotein cholesterol (HDL-C)) of MS and their combinations with HUA was analyzed by multivariate logistic regression model.Results:A total of 2 167 community residents were included in the survey, there were 385 cases of HUA with the age of (49.1±15.8) years old, and 297 males (77.1%); 1 782 subjects without HUA and with the age of (48.2±16.2) years old, and 695 males (39.0%). Compared with the non HUA group, the HUA group had a higher proportion of males, smoking, alcohol consumption, and gout attacks, higher abdominal circumference and body mass index (all P<0.05). The proportion of hypertension, hypertriglyceridemia, and abdominal obesity of MS patients in the HUA group was higher, while the proportion of low HDL-C syndrome was lower (all P<0.05). However, there was no significant difference in the proportion of hyperglycemia between the two groups ( P>0.05). After adjusting for smoking, drinking alcohol, taking antihypertensive and hypoglycemic drugs, multivariate logistic regression analysis showed that except for hyperglycemia, all other components of MS were independently associated with HUA. low HDL-C was negatively associated with HUA ( OR=0.408, 95% CI: 0.231-0.721, P=0.002), and high TG was strongly associated with HUA ( OR=1.834, 95% CI: 1.339-2.513, P<0.001). Multivariate logistic regression analysis also showed that 9 out of 31 combinations of MS components were associated with HUA (all P<0.05), and abdominal obesity+hypertriglyceridemia had the strongest association with HUA ( OR=4.379, 95% CI: 2.184-8.780, P<0.001). Conclusion:Except hyperglycemia, all components of MS and their combinations are significantly associated with HUA, the association between hyper-TG and HUA is the strongest one.

In recent years, it is noted clinically that the low level of serum uric acid is closely related to the adverse outcomes of cardiovascular and cerebrovascular diseases. Recent studies have shown that low uric acid levels not only boost the incidence of arrhythmia and cardiovascular events, but also increase mortality. It also has adverse effects on the development and prognosis of cerebrovascular diseases, including intracerebral hemorrhage and stroke. This article reviews research advances in the adverse effects of low uric acid on cardiovascular diseases andcerebrovascular diseases.

Saliva, like blood, urine, and other body fluids, contains extremely rich substances, among which salivary uric acid has a good correlation with serum uric acid, and could replace serum uric acid to a certain extent. In recent years, it has been found that salivary uric acid has a unique clinical value that serum uric acid does not have, and it is related to the occurrence and development of adolescent hypertension, adolescent body fat accumulation and preeclampsia, etc., so it is speculated that salivary uric acid has a certain application prospect. The aim of this review is to provide an update on the research of salivary uric acid and its future prospect.