Comparison Between Metabolic Syndrome and the Framingham Risk Score as Predictors of Cardiovascular Diseases Among Kazakhs in Xinjiang.
ABSTRACT: Metabolic syndrome (MS) and Framingham risk score (FRS) can be used for predicting the risk of developing cardiovascular diseases (CVD). Previous studies that compared FRS and MS have focused on high-income urban areas. This study focused on the comparison between FRS and MS when used in nomadic minorities in mountain areas. Moreover, an applicable tool for predicting the risk of developing CVD was identified. 2,286 participants who were recruited from the far west of China were followed-up for a median of 5.49 years. MS and FRS were compared in terms of their ability in predicting development of CVD using Cox regression and receiver operating characteristic curve. After each component of MS was appraised, its area under the curve (AUC) was 0.647. When age was included, the AUC of MS risk score increased from 0.647 to 0.758 (P?
Project description:INTRODUCTION:The Framingham risk score (FRS) is widely used to predict cardiovascular disease (CVD), but it neglects to account for social risk factors. Our study examined whether use of a cumulative social risk score in addition to the FRS improves prediction of CVD among South Korean adults. METHODS:We used nationally representative data on 19,147 adults aged 19 or older from the Korea National Health and Nutrition Examination Survey 2013-2016. We computed a cumulative social risk score (range, 0-3) based on 3 social risk factors: low household income, low level of education, and single-living status. CVD outcomes were stroke, myocardial infarction, and angina. Weighted logistic regression examined the associations between cumulative social risk, FRS, and CVD. McFadden pseudo-R2 and area under receiver operating characteristic curve (AUC) assessed model performance. We conducted mediation analyses to quantify the association between cumulative social risk score and CVD outcomes that is not mediated by the FRS. RESULTS:A unit increase in social risk was associated with 89.4% higher risk of stroke diagnosis, controlling for the FRS (P < .001). The FRS explained 8.0% of stroke diagnosis (R2) with fair discrimination (AUC = 0.728), and adding the cumulative social risk score enhanced R2 and AUC by 2.4% and 0.039. In the association between cumulative social risk and stroke, the proportion not mediated by the FRS was 65% (P < .001). We observed similar trends in myocardial infarction and angina, such that an increase in social risk was associated with increased relative risk of disease and improved disease diagnosis, and a large proportion of the association was not mediated by the FRS. CONCLUSION:Controlling for the FRS, cumulative social risks predicted stroke, myocardial infarction, and angina among adults in South Korea. Future research is needed to examine non-FRS mediators between cumulative social risk and CVD.
Project description:Background:Vascular age (VA) has recently emerged for CVD risk assessment and can either be computed using conventional risk factors (CRF) or by using carotid intima-media thickness (cIMT) derived from carotid ultrasound (CUS). This study investigates a novel method of integrating both CRF and cIMT for estimating VA [so-called integrated VA (IVA)]. Further, the study analyzes and compares CVD/stroke risk using the Framingham Risk Score (FRS)-based risk calculator when adapting IVA against VA. Methods:The system follows a four-step process: (I) VA using cIMT based using linear-regression (LR) model and its coefficients; (II) VA prediction using ten CRF using a multivariate linear regression (MLR)-based model with gender adjustment; (III) coefficients from the LR-based model and MLR-based model are combined using a linear model to predict the final IVA; (IV) the final step consists of FRS-based risk stratification with IVA as inputs and benchmarked against FRS using conventional method of CA. Area-under-the-curve (AUC) is computed using IVA and benchmarked against CA while taking the response variable as a standardized combination of cIMT and glycated hemoglobin. Results:The study recruited 648 patients, 202 were Japanese, 314 were Asian Indian, and 132 were Caucasians. Both left and right common carotid arteries (CCA) of all the population were scanned, thus a total of 1,287 ultrasound scans. The 10-year FRS using IVA reported higher AUC (AUC =0.78) compared with 10-year FRS using CA (AUC =0.66) by ~18%. Conclusions:IVA is an efficient biomarker for risk stratifications for patients in routine practice.
Project description:<h4>Backgrounds</h4>Cardiovascular disease (CVD) risk factors are individually associated with frailty. This study examined whether Framingham CVD risk score (FRS) as an aggregate measure of CVD risk is associated with incident frailty among Chinese older adults.<h4>Methods</h4>This study used data from the China Health and Retirement Longitudinal Study. A sample of 3,618 participants aged 60 to 95 years and without CVD at baseline were followed for four years. FRS was calculated at baseline. Frailty status was defined as not-frail (0-2 criteria) or frail (3-5 criteria) based on the physical frailty phenotype consisting of five binary criteria (weakness, slowness, exhaustion, low activity level, and weight loss). After excluding subjects who were frail (n = 248) at baseline, discrete-time Cox regression was used to evaluate the relationship between FRS and incident frailty.<h4>Results</h4>During a median follow-up of 4.0 years, 323 (8 %) participants developed CVD and 318 (11 %) subjects had frailty onset. Higher FRS was associated with greater risk of incident frailty (HR: 1.03, 95 % CI: 1.00 to 1.06) after adjusting for education, marital status, obesity, comorbidity burden, and cognitive function. This association however was no longer significant (HR: 1.00, 95 % CI: 0.97 to 1.03) after additionally adjusting for age. These findings remained essentially unchanged after excluding subjects with depression (n = 590) at baseline or incident CVD (n = 323) during the 4-year follow-up.<h4>Conclusions</h4>The FRS was not independently associated with incident frailty after adjusting for chronological age. More research is needed to assess the clinical utility of the FRS in predicting adverse health outcomes other than CVD in older adults.
Project description:<h4>Introduction</h4>To date, research is lacking on the development of a cardiovascular disease (CVD) risk assessment tool for people with diabetes mellitus, in general, and for Chinese patients with diabetes in particular. We have explored CVD risk assessment tools for Chinese patients with diabetes. Here, we report our investigation of cardiovascular risk assessment using the improved Framingham Risk Score (I-FRS) in patients with type 2 diabetes mellitus (T2DM) in Beijing communities.<h4>Methods</h4>A total of 3232 patients with T2DM attending Beijing community health centers were enrolled in this study. FRS were used to predict CVD risk in all patients at baseline using the following risk scores for glycated hemoglobin (HbA1c) categories: 0 = HbA1c ≤ 7.0%; 1 = 7.0% < HbA1c ≤ 7.9%; 2 = 8.0% < HbA1c ≤ 8.9%; and 3 = HbA1c > 9.0%. The I-FRS was use to stratify all patients into low (I-FRS < 10%), medium (I-FRS 10-20%), and high (I-FRS > 20%) FRS strata. All treatments administered in the Beijing Communities Diabetes Study were in accordance with national guidelines for T2DM in China, and patients regularly attended clinical consultations with professors in endocrinology, who were experts in their respective speciality, from top tier hospitals. After 10 years, patients were followed-up to assess the long-term effects of the multifactorial interventions. Statistical analysis was performed using SAS® software (SAS Institute, Inc., Cary, NC, USA).<h4>Results</h4>The receiver operating characteristic curve of the I-FRS showed significant prediction accuracy for the actual incidence of CVD events. At baseline, subjects in the high FRS stratum for diabetes were more prone to be elderly and to have a longer duration of T2DM, higher systolic blood pressure, and higher lipid profiles. Subjects in the medium and high FRS strata had a higher incidence of CVD events than those in the no-complications group (DM group with no blood pressure issues) (P < 0.001). The 10-year hazard ratios for CVD events in diabetic patients with I-FRS score > 20% was 12.5-fold higher than that of patients with I-FRS score < 10%. Multifactorial intervention significantly reduced the I-FRS of the three FRS strata in patients with T2DM. The post-intervention I-FRS for the hypertension and CVD groups of patients were significantly lower than the respective baseline I-FRS. Cox multivariate analyses revealed that patients in the medium and high FRS strata had higher incidences of endpoint events than those in the low FRS stratum.<h4>Conclusions</h4>The I-FRS plays an important role in predicting CVD in patients with T2DM. Multifactorial interventions for CVD risk factors over 10-year follow-up lowered the estimated 10-year risk for CVD events in persons with diabetes. We suggest the use of the I-FRS score to stratify a patient's risk of CVD when analyzing the efficacy of diabetes management. Aggressive risk reduction should be focused on those individuals with a high I-FRS score.<h4>Trial registration</h4>ChiCTR-TRC-13003978 and ChiCTR-OOC-15006090.
Project description:Inclusion of clinical parameters limits the application of most cardiovascular disease (CVD) prediction models to clinical settings. We developed and externally validated a non-clinical CVD risk score with a clinical extension and compared the performance to established CVD risk scores. We derived the scores predicting CVD (non-fatal and fatal myocardial infarction and stroke) in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (n = 25,992, cases = 683) using competing risk models and externally validated in EPIC-Heidelberg (n = 23,529, cases = 692). Performance was assessed by C-indices, calibration plots, and expected-to-observed ratios and compared to a non-clinical model, the Pooled Cohort Equation, Framingham CVD Risk Scores (FRS), PROCAM scores, and the Systematic Coronary Risk Evaluation (SCORE). Our non-clinical score included age, gender, waist circumference, smoking, hypertension, type 2 diabetes, CVD family history, and dietary parameters. C-indices consistently indicated good discrimination (EPIC-Potsdam 0.786, EPIC-Heidelberg 0.762) comparable to established clinical scores (thereof highest, FRS: EPIC-Potsdam 0.781, EPIC-Heidelberg 0.764). Additional clinical parameters slightly improved discrimination (EPIC-Potsdam 0.796, EPIC-Heidelberg 0.769). Calibration plots indicated very good calibration with minor overestimation in the highest decile of predicted risk. The developed non-clinical 10-year CVD risk score shows comparable discrimination to established clinical scores, allowing assessment of individual CVD risk in physician-independent settings.
Project description:The aim of this study was to compare the QRISKII, an electronic health data-based risk score, to the Framingham Risk Score (FRS) and atherosclerotic cardiovascular disease (ASCVD) score. Risk estimates were calculated for a cohort of 8783 patients, and the patients were followed up from November 29, 2012, through June 1, 2015, for a cardiovascular disease (CVD) event. During follow-up, 246 men and 247 women had a CVD event. Cohen's kappa statistic for the comparison of the QRISKII and FRS was 0.22 for men and 0.23 for women, with the QRISKII classifying more patients in the higher-risk groups. The QRISKII and ASCVD were more similar with kappa statistics of 0.49 for men and 0.51 for women. The QRISKII shows increased discrimination with area under the curve (AUC) statistics of 0.65 and 0.71, respectively, compared to the FRS (0.59 and 0.66) and ASCVD (0.63 and 0.69). These results demonstrate that incorporating additional data from the electronic health record (EHR) may improve CVD risk stratification.
Project description:<h4>Objective</h4>In type 2 diabetes mellitus (T2DM), it remains unclear whether coronary artery calcium (CAC) provides additional information about cardiovascular disease (CVD) mortality beyond the Framingham Risk Score (FRS) factors.<h4>Research design and methods</h4>A total of 1,123 T2DM participants, ages 34-86 years, in the Diabetes Heart Study followed up for an average of 7.4 years were separated using baseline computed tomography scans of CAC (0-9, 10-99, 100-299, 300-999, and ?1,000). Logistic regression was performed to examine the association between CAC and CVD mortality adjusting for FRS. Areas under the curve (AUC) with and without CAC were compared. Net reclassification improvement (NRI) compared FRS (model 1) versus FRS+CAC (model 2) using 7.4-year CVD mortality risk categories 0% to <7%, 7% to <20%, and ?20%.<h4>Results</h4>Overall, 8% of participants died of cardiovascular causes during follow-up. In multivariate analysis, the odds ratios (95% CI) for CVD mortality using CAC 0-9 as the reference group were, CAC 10-99: 2.93 (0.74-19.55); CAC 100-299: 3.17 (0.70-22.22); CAC 300-999: 4.41(1.15-29.00); and CAC ?1,000: 11.23 (3.24-71.00). AUC (95% CI) without CAC was 0.70 (0.67-0.73), AUC with CAC was 0.75 (0.72-0.78), and NRI was 0.13 (0.07-0.19).<h4>Conclusions</h4>In T2DM, CAC predicts CVD mortality and meaningfully reclassifies participants, suggesting clinical utility as a risk stratification tool in a population already at increased CVD risk.
Project description:We assess the improvement in discrimination afforded by the addition of the computed tomography risk markers thoracic aorta calcium (TAC), aortic valve calcification (AVC), mitral annular calcification (MAC), pericardial adipose tissue volume (PAT), and liver attenuation (LA) to the Framingham risk score (FRS)?+?coronary artery calcium (CAC) for incident coronary heart disease (CHD) and incident cerebrovascular disease (CVD) in a multiethnic cohort.A total of 5745 participants were enrolled, with 2710 at intermediate Framingham risk, 210 CVD events, and 155 CHD events). Over 9 years of follow up, 251 had adjudicated CHD, 346 had CVD events, and 321 died. The data were analysed using Cox proportional hazard, receiver operator curve (ROC), and net reclassification improvement (NRI) analyses. In the whole cohort and also when the analysis was restricted to only the intermediate-risk participants, CAC, TAC, AVC, and MAC were all significantly associated with incident CVD, incident CHD, and mortality, and CAC had the strongest association. When added to the FRS, CAC had the highest area under the curve (AUC) for the prediction of incident CVD and incident CHD; LA had the least. The addition of TAC, AVC, MAC, PAT, and LA to FRS?+?CAC all resulted in a significant reduction in AUC for incident CHD (0.712 vs. 0.646, 0.655, 0.652, 0.648, and 0.569; all p?<?0.01, respectively) in participants with intermediate FRS. The addition of CAC to FRS resulted in an NRI of 0.547 for incident CHD in the intermediate-risk group. The NRI when TAC, AVC, MAC, PAT, and LA were added to FRS?+?CAC were 0.024, 0.026, 0.019, 0.012, and 0.012, respectively, for incident CHD in the intermediate-risk group. Similar results were obtained for incident CVD in the intermediate-risk group and also when the whole cohort was used instead of the intermediate FRS group.The addition of CAC to the FRS provides superior discrimination especially in intermediate-risk individuals compared with the addition of TAC, AVC, MAC, PAT, or LA for incident CVD and incident CHD. Compared with FRS?+?CAC, the addition of TAC, AVC, MAC, PAT, or LA individually to FRS?+?CAC worsens the discrimination for incident CVD and incident CHD. These risk markers are unlikely to be useful for improving cardiovascular risk prediction.
Project description:BACKGROUND:The high prevalence of metabolic syndrome (MetS) and cardiovascular diseases (CVD) is observed among Kazakhs in Xinjiang. Because MetS may significantly predict the occurrence of CVD, the inclusion of CVD-related indicators in metabolic network may improve the predictive ability for a CVD-risk model for Kazakhs in Xinjiang. METHODS:The study included 2,644 subjects who were followed for 5 years or longer. CVD cases were identified via medical records of the local hospitals from April 2016 to August 2017. Factor analysis was performed in 706 subjects (267 men and 439 women) with MetS to extract CVD-related potential factors from 18 biomarkers tested in a routine health check-up, served as a synthetic predictor (SP). We evaluated the predictive ability of the CVD-risk model using age and SP, logistic regression discrimination for internal validation (n = 384; men = 164, women = 220) and external validation (n = 219; men = 89, women = 130), calculated the probability of CVD for each participant, and receiver operating characteristic curves. RESULTS:According to the diagnostic criteria of JIS, the prevalence of MetS in Kazakh was 30.9%. Seven potential factors with a similar pattern were obtained from men and women and comprised the CVD predictors. When predicting CVD in the internal validation, the area under the curve (AUC) were 0.857 (95%CI 0.807-0.898) for men and 0.852 (95%CI 0.809-0.889) for women, respectively. In the external validation, the AUC to predict CVD were 0.914 (95%CI 0.832-0.963) for men and 0.848 (95%CI 0.774-0.905) for women. It is suggested that SP might serve as a useful tool in identifying CVD with in Kazakhs, especially for Kazakhs men. CONCLUSIONS:Among 7 potential factors were extracted from 18 biomarkrs in Kazakhs with MetS, and SP may be used for CVD risk assessment.
Project description:This study aimed to determine whether nonalcoholic fatty liver disease (NAFLD) is an independent risk factor for CVD and to identify the most useful NAFLD diagnostic tool for predicting CVD. Data from a total of 23,376 Korean adults without established CVD were analyzed. Cardiovascular risk was calculated using the Framingham Risk Score (FRS) 2008. The presence of NAFLD was defined as moderate-to-severe fatty liver disease diagnosed by ultrasonography. Scores for fatty liver were calculated using four NAFLD scoring systems (Fatty Liver Index, FLI; Hepatic Steatosis Index, HSI; Simple NAFLD Score, SNS; Comprehensive NAFLD Score, CNS), and were compared and analyzed according to cardiovascular risk group. Using the FRS, 67.4% of participants were considered to be at low risk of CVD, 21.5% at intermediate risk, and 11.1% at high risk. As the risk of CVD increased, both the prevalence of NAFLD and the score from each NAFLD scoring system increased significantly (<i>p</i> < 0.001). In the unadjusted analysis, the CNS had the strongest association with high CVD risk; in the adjusted analysis, the FLI score was most strongly associated with high CVD risk. Fatty liver is an important independent risk factor for CVD. Therefore, the available NAFLD scoring systems could be utilized to predict CVD.