INTRODUCTION: An echocardiographic calcium score (ECS) predicts cardiovascular disease (CVD) in the general population. Its utility in peritoneal dialysis (PD) patients is unknown. METHODS: This cross-sectional study assessed 125 patients on PD. The ECS (range 0-8) was compared between subjects with CVD and those without. RESULTS: Among the subjects, 54 had CVD and 71 did not. Subjects with CVD were older (69 years vs. 56 years, P < 0.001) and had a higher prevalence of diabetes mellitus (DM) (81.5% vs. 45.1%, P < 0.001). They had lower diastolic blood pressure (72 mmHg vs. 81 mmHg, P < 0.001), lower phosphate (1.6 mmol/L vs. 1.9 mmol/L, P = 0.002), albumin (30 g/L vs. 32 g/L, P = 0.001), parathyroid hormone (34.4 pmol/L vs. 55.8 pmol/L, P = 0.002), total cholesterol (4.5 vs. 4.9, P = 0.047), LDL cholesterol (2.4 mmol/L vs. 2.8 mmol/L, P = 0.019) and HDL cholesterol (0.8 mmol/L vs. 1.1 mmol/L, P = 0.002). The ECS was found to be higher in subjects with CVD than in those without (2 vs. 1, P = 0.001). On multivariate analysis, only DM and age were independently associated with CVD. CONCLUSION The ECS was significantly higher in PD patients with CVD than in those without, reflecting a higher vascular calcification burden in the former. It is a potentially useful tool to quantify vascular calcification in PD patients.
Humans ; Cardiovascular Diseases/diagnostic imaging* ; Cross-Sectional Studies ; Calcium ; Peritoneal Dialysis/adverse effects* ; Vascular Calcification/epidemiology* ; Echocardiography

Objective: To determine the causal association between long-term Nitrogen dioxide (NO₂) exposure and the risk of cardiovascular hospitalization. Methods: Based on a sub-cohort of a community-based prospective cohort study, a total of 36 271 participants were recruited from 35 communities randomly selected in Guangzhou in 2015. The annual average exposure of NO₂, demographic characteristics, lifestyle factors, and information on the causes of hospitalization was collected. We applied marginal structural Cox models to investigate the effect of NO₂ on cardiovascular hospitalization. Demographic and behavioral factors also stratified results. Results: The mean age of participants in the present study was (50.9±17.8) years, and the cardiovascular admission rate was 8.7%, with 203 822 person-years of follow-up. The annual mean NO₂ concentration was 48.7 μg/m³ during 2015-2020. For each 10 μg/m³ increase in NO₂ concentrations, the HRs (95%CIs) of total cardiovascular hospitalization, cardiovascular hospitalization, and cerebrovascular hospitalization were 1.33 (1.16-1.52), 1.36 (1.16-1.60) and 1.25 (1.00-1.55), respectively. Participants who were never married/married, with secondary education, high exercise frequency, or non-smokers/current smokers may be more susceptible than their counterparts. Conclusion: Long-term exposure to NO₂ significantly increased hospitalization risk for cardiovascular disease.
Humans ; Adult ; Middle Aged ; Aged ; Nitrogen Dioxide ; Prospective Studies ; Cardiovascular Diseases/epidemiology* ; Causality ; Hospitalization

Risk prediction models play an important role in the primary prevention of cardiovascular diseases (CVD) in the elderly population. There are fifteen papers about CVD risk prediction models developed for the elderly domestically and internationally, of which the definitions of disease outcome vary widely. Ten models were reported with insufficient information about study methods or results. Ten models were at high risk of bias. Thirteen models presented moderate discrimination in internal validation, and only four models have undertaken external validation. The CVD risk prediction models for the elderly differed from those for the general population in terms of model algorithm and the effect size of association between predictor and outcome, and the prediction performance of the models for the elderly attenuated. In the future, high-quality external validation researches are necessary to provide more solid evidence. Different ways, including adding new predictors, using competing risk model algorithms, machine learning methods, or joint models, and altering the prediction time horizon, should be explored to optimize the current models.
Humans ; Aged ; Cardiovascular Diseases/epidemiology* ; Algorithms ; Machine Learning

Objective: To assess the cardiovascular health status of adults in China by using the "Life's Essential 8" score, and provide reference for the development and improvement of cardiovascular disease prevention and control policies and measures. Methods: Chronic Disease and Nutrition Surveillance was conducted in 298 counties/districts in 2015 in 31 provinces (autonomous regions, municipalities) across China, multi-stage stratified cluster random sampling was used to select 45 households in each village or neighborhood, and 20 households were further selected to conduct dietary surveys. In this study, a total of 70 093 adults aged ≥20 years who completed the dietary survey and had complete information were included, their cardiovascular health status were assessed by using the "Life's Essential 8" score, a cardiovascular health scoring standard released by the American Heart Association in 2022. All results were adjusted using complex design-based sampling weights to achieve a better estimate of the population. Results: In 2015, the overall cardiovascular health score of Chinese adults aged ≥20 years was 73.3±12.6, the score was significantly higher in women (77.9±11.6) than in men (68.7±11.8), and higher in urban area (74.5±12.8) than in rural area (71.9±12.2), the differences were significant (P<0.001). It was estimated that about 0.25% (95%CI: 0.16%-0.33%) of adults in China had cardiovascular health score of 100, and 33.0% (95%CI: 31.6%-34.3%), 63.2% (95%CI: 62.1%-64.3%), and 3.9% (95%CI: 3.5%-4.2%) of adults had high, moderate and low cardiovascular health scores, respectively. The proportion of those with high cardiovascular health scores was relatively low in men, those with low education level, those with low income, those living in rural areas, and those living in southwest China (P<0.001). Of the eight factors, diet had the lowest mean score (46.0, 95%CI: 44.7-47.3), followed by blood pressure (59.4, 95%CI: 58.2-60.6) and tobacco exposure (61.4, 95%CI: 60.6-62.2). Conclusions: The cardiovascular health status of two-thirds of adult population in China needs to be improved. Diet, tobacco exposure, and blood pressure are the factors affecting the cardiovascular health of Chinese population, to which close attention needs to be paid, and men, rural residents, and those with lower socioeconomic status are key groups in cardiovascular health promotion.
Adult ; Female ; Humans ; Male ; Asian People ; Cardiovascular Diseases/prevention & control* ; China/epidemiology* ; Diet ; East Asian People ; Health Status ; Risk Factors ; United States ; Young Adult ; Health Status Indicators

OBJECTIVE: To explore joint association of depression symptoms and 10-year risk of ischemic cardiovascular disease (CVD) in middle-aged and elderly people in China. METHODS: Based on China Health and Retirement Longitudinal Study(CHARLS)database using 2011 baseline data and the follow-up cohort data of 2013, 2015 and 2018, describe the distribution characteristics of baseline depressive symptoms and 10-year risk of ischemic cardiovascular disease in 2011. Cox survival analysis model was used to analyze the individual, independent and joint association of depression symptoms and 10-year risk of ischemic cardiovascular disease with cardiovascular disease. RESULTS: A total of 9 412 subjects were enrolled. The detection rate of depressive symptoms at baseline was 44.7%, and the 10-year middle and high risk of ischemic cardiovascular disease was 13.62%. During an average follow-up of 6.19 (6.19±1.66) years, 1 401 cases of cardiovascular disease were diagnosed in 58 258 person-years, revealing an overall incidence density of 24.048/1 000 person-years. After adjusting the factors, in terms of individual impact, the participants with depressive symptoms had a higher risk of developing CVD (HR=1.263, 95%CI: 1.133-1.408), while medium to high risk of ischemic cardiovascular disease had a higher risk of developing CVD (HR=1.892, 95%CI: 1.662-2.154). Among independent influences, participants with depressive symptoms had a higher risk of developing CVD (HR=1.269, 95% CI: 1.138-1.415), while medium to high risk of 10-year risk of ischemic cardiovascular disease had a higher risk of developing CVD (HR=1.898, 95%CI: 1.668-2.160). Joint impact result showed the incidence of cardiovascular disease in the low risk of 10-year risk of ischemic cardiovascular disease with depressive symptoms group, middle and high risk of 10-year risk of ischemic cardiovascular disease without depressive symptoms group, and 10-year middle and high risk of ischemic cardiovascular disease with depressive symptoms group were 1.390, 2.149, and 2.339 times higher than that of low risk of 10-year risk of ischemic cardiovascular disease without depressive symptoms (P < 0.001). CONCLUSION The superimposed depression symptoms of the middle and high-risk population at the 10-year risk of ischemic cardiovascular disease will aggravate the risk of cardiovascular disease in middle-aged and elderly people. In combination with the actual lifestyle intervention and physical index health management, attention should be paid to mental health intervention.
Aged ; Middle Aged ; Humans ; Cardiovascular Diseases/epidemiology* ; Longitudinal Studies ; Depression/epidemiology* ; Risk Factors ; China/epidemiology*

OBJECTIVE: To develop and validate a three-year risk prediction model for new-onset cardiovascular diseases (CVD) among female patients with breast cancer. METHODS: Based on the data from Inner Mongolia Regional Healthcare Information Platform, female breast cancer patients over 18 years old who had received anti-tumor treatments were included. The candidate predictors were selected by Lasso regression after being included according to the results of the multivariate Fine & Gray model. Cox proportional hazard model, Logistic regression model, Fine & Gray model, random forest model, and XGBoost model were trained on the training set, and the model performance was evaluated on the testing set. The discrimination was evaluated by the area under the curve (AUC) of the receiver operator characteristic curve (ROC), and the calibration was evaluated by the calibration curve. RESULTS: A total of 19 325 breast cancer patients were identified, with an average age of (52.76±10.44) years. The median follow-up was 1.18 [interquartile range (IQR): 2.71] years. In the study, 7 856 patients (40.65%) developed CVD within 3 years after the diagnosis of breast cancer. The final selected variables included age at diagnosis of breast cancer, gross domestic product (GDP) of residence, tumor stage, history of hypertension, ischemic heart disease, and cerebrovascular disease, type of surgery, type of chemotherapy and radiotherapy. In terms of model discrimination, when not considering survival time, the AUC of the XGBoost model was significantly higher than that of the random forest model [0.660 (95%CI: 0.644-0.675) vs. 0.608 (95%CI: 0.591-0.624), P < 0.001] and Logistic regression model [0.609 (95%CI: 0.593-0.625), P < 0.001]. The Logistic regression model and the XGBoost model showed better calibration. When considering survival time, Cox proportional hazard model and Fine & Gray model showed no significant difference for AUC [0.600 (95%CI: 0.584-0.616) vs. 0.615 (95%CI: 0.599-0.631), P=0.188], but Fine & Gray model showed better calibration. CONCLUSION It is feasible to develop a risk prediction model for new-onset CVD of breast cancer based on regional medical data in China. When not considering survival time, the XGBoost model and the Logistic regression model both showed better performance; Fine & Gray model showed better performance in consideration of survival time.
Humans ; Female ; Adult ; Middle Aged ; Adolescent ; Breast Neoplasms/epidemiology* ; Cardiovascular Diseases/etiology* ; Proportional Hazards Models ; Logistic Models ; China/epidemiology*

OBJECTIVE: To compare the expected population impact of benefit and risk of aspirin treatment strategies for the primary prevention of cardiovascular diseases recommended by different guidelines in the Chinese Electronic Health Records Research in Yinzhou (CHERRY) study. METHODS: A decision-analytic Markov model was used to simulate and compare different strategies of aspirin treatment, including: Strategy ①: Aspirin treatment for Chinese adults aged 40-69 years with a high 10-year cardiovascular risk, recommended by the 2020 Chinese Guideline on the Primary Prevention of Cardiovascular Diseases; Strategy ②: Aspirin treatment for Chinese adults aged 40-59 years with a high 10-year cardiovascular risk, recommended by the 2022 United States Preventive Services Task Force Recommendation Statement on Aspirin Use to Prevent Cardiovascular Disease; Strategy ③: Aspirin treatment for Chinese adults aged 40-69 years with a high 10-year cardiovascular risk and blood pressure well-controlled (< 150/90 mmHg), recommended by the 2019 Guideline on the Assessment and Management of Cardio-vascular Risk in China. The high 10-year cardiovascular risk was defined as the 10-year predicted risk over 10% based on the 2019 World Health Organization non-laboratory model. The Markov model simulated different strategies for ten years (cycles) with parameters mainly from the CHERRY study or published literature. Quality-adjusted life year (QALY) and the number needed to treat (NNT) for each ischemic event (including myocardial infarction and ischemic stroke) were calculated to assess the effectiveness of the different strategies. The number needed to harm (NNH) for each bleeding event (including hemorrhagic stroke and gastrointestinal bleeding) was calculated to assess the safety. The NNT for each net benefit (i.e., the difference of the number of ischemic events could be prevented and the number of bleeding events would be added) was also calculated. One-way sensitivity analysis on the uncertainty of the incidence rate of cardiovascular diseases and probabilistic sensitivity analysis on the uncertainty of hazard ratios of interventions were conducted. RESULTS: A total of 212 153 Chinese adults, were included in this study. The number of people who were recommended for aspirin treatment Strategies ①-③ was 34 235, 2 813, and 25 111, respectively. The Strategy ③ could gain the most QALY of 403 [95% uncertainty interval (UI): 222-511] years. Compared with Strategy ①, Strategy ③ had similar efficiency but better safety, with the extra NNT of 4 (95%UI: 3-4) and NNH of 39 (95%UI: 19-132). The NNT per net benefit was 131 (95%UI: 102-239) for Strategy ①, 256 (95%UI: 181-737) for Strategy ②, and 132 (95%UI: 104-232) for Strategy ③, making Strategy ③ the most favorable option with a better QALY and safety, along with similar efficiency in terms of net benefit. The results were consistent in the sensitivity analyses. CONCLUSION The aspirin treatment strategies recommended by the updated guidelines on the primary prevention of cardiovascular diseases showed a net benefit for high-risk Chinese adults from developed areas. However, to balance effectiveness and safety, aspirin is suggested to be used for primary prevention of cardiovascular diseases with consideration for blood pressure control, resulting in better intervention efficiency.
Adult ; Humans ; Aspirin/therapeutic use* ; Cardiovascular Diseases/epidemiology* ; Gastrointestinal Hemorrhage ; Myocardial Infarction/prevention & control* ; Primary Prevention/methods* ; Middle Aged ; Aged

BACKGROUND: Sex- and age-specific impacts of cardiovascular risk factors on the development of dementia have not been well evaluated. We investigated these impacts of smoking, overweight/obesity, hypertension, and diabetes mellitus on the risk of disabling dementia. METHODS: The study participants were 25,029 (10,134 men and 14,895 women) Japanese aged 40-74 years without disabling dementia at baseline (2008-2013). They were assessed on smoking status (non-current or current), overweight/obesity (body mass index ≥25 kg/m² and ≥30 kg/m², respectively), hypertension (systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg or any antihypertensive medication use), and diabetes mellitus (a fasting serum glucose ≥126 mg/dL, non-fasting glucose ≥200 mg/dL, hemoglobin A1c ≥6.5% by the National Glycohemoglobin Standardization Program or glucose-lowering medication use) at baseline. Disabling dementia was identified as the level of care required ≥1 and cognitive disability grade ≥IIa according to the National Long-term Care Insurance Database. We used a Cox proportional regression model to estimate hazard ratios and 95% confidence intervals (95% CIs) of disabling dementia according to the cardiovascular risk factors and calculated the population attributable fractions (PAFs). RESULTS: During a median follow-up of 9.1 years, 1,322 (606 men and 716 women) developed disabling dementia. Current smoking and hypertension were associated with a higher risk of disabling dementia in both sexes, whereas overweight or obesity was not associated with the risk in either sex. Diabetes mellitus was associated with a higher risk only in women (p for sex interaction = 0.04). The significant PAFs were 13% for smoking and 14% for hypertension in men and 3% for smoking, 12% for hypertension, and 5% for diabetes mellitus in women. The total PAFs of the significant risk factors were 28% in men and 20% in women. When stratified by age, hypertension in midlife (40-64 years) was associated with the increased risk in men, while diabetes mellitus in later-life (65-74 years) was so in women. CONCLUSIONS A substantial burden of disabling dementia was attributable to smoking, and hypertension in both sexes and diabetes mellitus in women, which may require the management of these cardiovascular risk factors to prevent dementia.
Male ; Humans ; Female ; Adult ; Middle Aged ; Overweight/complications* ; East Asian People ; Cardiovascular Diseases/epidemiology* ; Hypertension/etiology* ; Diabetes Mellitus/etiology* ; Obesity/etiology* ; Smoking/epidemiology* ; Risk Factors ; Age Factors ; Dementia/etiology*

BACKGROUND: Previous cardiovascular risk prediction models in Japan have utilized prospective cohort studies with concise data. As the health information including health check-up records and administrative claims becomes digitalized and publicly available, application of large datasets based on such real-world data can achieve prediction accuracy and support social implementation of cardiovascular disease risk prediction models in preventive and clinical practice. In this study, classical regression and machine learning methods were explored to develop ischemic heart disease (IHD) and stroke prognostic models using real-world data. METHODS: IQVIA Japan Claims Database was searched to include 691,160 individuals (predominantly corporate employees and their families working in secondary and tertiary industries) with at least one annual health check-up record during the identification period (April 2013-December 2018). The primary outcome of the study was the first recorded IHD or stroke event. Predictors were annual health check-up records at the index year-month, comprising demographic characteristics, laboratory tests, and questionnaire features. Four prediction models (Cox, Elnet-Cox, XGBoost, and Ensemble) were assessed in the present study to develop a cardiovascular disease risk prediction model for Japan. RESULTS: The analysis cohort consisted of 572,971 invididuals. All prediction models showed similarly good performance. The Harrell's C-index was close to 0.9 for all IHD models, and above 0.7 for stroke models. In IHD models, age, sex, high-density lipoprotein, low-density lipoprotein, cholesterol, and systolic blood pressure had higher importance, while in stroke models systolic blood pressure and age had higher importance. CONCLUSION Our study analyzed classical regression and machine learning algorithms to develop cardiovascular disease risk prediction models for IHD and stroke in Japan that can be applied to practical use in a large population with predictive accuracy.
Humans ; Cardiovascular Diseases/epidemiology* ; Prognosis ; Prospective Studies ; Japan/epidemiology* ; Stroke/etiology* ; Myocardial Ischemia/epidemiology* ; Risk Assessment/methods*

OBJECTIVE: The main aim of this study is to investigate whether acupuncture could be an effective complementary treatment for reducing the risk of macrovascular complications in diabetic patients currently taking antidiabetic medications using a nationwide population-based database. METHODS: We conducted a retrospective cohort study to assess the efficacy of acupuncture on cardiovascular complications in diabetic patients using data from patients between 40 and 79 years of age, newly diagnosed with diabetes between 2003 and 2006, found in the National Health Insurance Service-National Sample Cohort (NHIS-NSC) in Korea. From the data, we identified 21,232 diabetic patients who were taking antidiabetic medication between 2003 and 2006. The selected patients were divided into two groups-those who received acupuncture at least three times and those who received no acupuncture (non-acupuncture) in the year following their diagnosis of diabetes. After 1:1 propensity score matching (PSM), each group had 3350 patients, and the observation ceased at the occurrence of a major adverse cardiovascular event (MACE), which was defined as either myocardial infarction, stroke, or death due to cardiovascular cause. RESULTS: After PSM, the acupuncture group had a lower incidence of MACE (hazard ratio [HR]: 0.87; 95% confidence interval [CI]: 0.81-0.94; P = 0.0003) and all-cause mortality (HR: 0.77; 95% CI: 0.70-0.84; P < 0.0001) than the non-acupuncture group; the HRs for stroke-related mortality (HR: 0.75; 95% CI: 0.56-1.00; P = 0.0485), ischemic heart disease mortality (HR: 0.53; 95% CI: 0.34-0.84; P = 0.006) and circulatory system disease mortality (HR: 0.67; 95% CI: 0.55-0.82; P < 0.0001) were lower in the acupuncture group than in the non-acupuncture group in the secondary analysis. CONCLUSION Our results indicate that diabetic patients receiving acupuncture treatment might have a lower risk of MACE, all-cause mortality and cardiovascular mortality. This population-based retrospective study suggests beneficial effects of acupuncture in preventing macrovascular complications associated with diabetes. These findings call for further prospective cohort or experimental studies on acupuncture treatment for cardiovascular complications of diabetes. Please cite this article as: Jung H, Won T, Kim GY, Jang J, Yeo S, Lim S. Efficacy of acupuncture on cardiovascular complications in patients with diabetes mellitus in Korea: A nationwide retrospective cohort. J Integr Med. 2023; 21(2): 176-183.
Humans ; Retrospective Studies ; Cardiovascular Diseases/etiology* ; Diabetes Mellitus, Type 2/drug therapy* ; Hypoglycemic Agents/therapeutic use* ; Stroke/complications* ; Acupuncture Therapy ; Republic of Korea/epidemiology*