BACKGROUND: The associations between Multiple Sclerosis (MS) and cardiovascular diseases, drawn from epidemiological studies, have attracted much attention in recent years.
METHODS: The present study employed a monocentric, observational, retrospective cohort design. The primary objective of the study was to describe the Framingham Risk Score (FRS) rate in a cross-sectional analysis of our cohort of relapsing-remitting MS patients who are regularly followed up and, if applicable, to identify any association with the patient\'s Patient Determined Disease Steps (PDDS). Cardiovascular risk was classified as follows: low if the FRS is less than 10%, moderate if it is 10% to 19%, and high if it is 20% or higher.
RESULTS: A total cohort of 229 patients was enrolled. The sample consists of 163 women (71.2%). FRS categories were distributed as follows: 97 (42.3%) patients had low FRS, 84 (36.7%) patients had moderate FRS, and 48 (21%) patients had high FRS. In the univariable ordinal regression analysis, one one-point increase in the PDDS scale was associated with a 24% risk of high FRS (vs. low) (proportional odds ratio [OR] =2.426, 95% confidence interval [CI] 1.660-3.545; p <.0001). The results were also confirmed by the EDSS score, with a point increase in the EDSS score associated with a 19% risk of high FRS (vs. low) (proportional OR =1.953, 95% CI 1.429-2.669-1.04; p <.0001).
CONCLUSIONS: The FRS demonstrated an association with the patient\'s \"perception of the disease\" as indicated by the PDDS. Further studies with larger cohorts are needed to adequately address cardiovascular risk in life-threatening conditions, such as MS.

UNASSIGNED: The PREVENT (Predicting Risk of cardiovascular disease EVENTs risk algorithm was developed to better reflect the impact of metabolic factors on cardiovascular risk.
UNASSIGNED: The purpose of this study was to compare the relative performance of PREVENT with standard comparator algorithms (Framingham risk score, pooled cohort equation, SCORE2 [Systematic COronary Risk Evaluation2]) for risk stratification emphasizing the implications of weighing chronic kidney disease.
UNASSIGNED: A simulated cohort was created of males and females aged 40 to 75 years with and without other traditional risk factors and either normal estimated glomerular filtration rates (eGFR 90 or 60 ml/min/1.73 m2) or abnormal eGFR (45 or 30 ml/min/1.73 m2). The concordance and reclassification rates were calculated for each category of risk with emphasis on subjects characterized as moderate risk by the standard comparator algorithms.
UNASSIGNED: PREVENT demonstrated increased risk with progressive decreases in eGFR. When the standard comparator algorithms identified moderate risk, PREVENT was concordant in 6% to 88% of simulations. In simulations with normal eGFR, PREVENT identified a lower risk in 18% to 88% and a higher risk in 0% to 12% of simulations. Conversely, with abnormal eGFR, PREVENT identified lower risk in 0% to 26% and higher risk in 4% to 94% of simulations.
UNASSIGNED: PREVENT substantially reclassifies risk and has the potential to alter prevention practice patterns. The tendency to assign a lower risk compared to standard algorithms when eGFR is normal may diminish implementation of preventive therapy. National health care systems need to monitor whether such changes improve overall public health.

Heart-brachium pulse wave velocity (hbPWV) is a promising measure of arterial stiffness including the proximal aorta. To characterize age-associated changes and the clinical utilities of hbPWV, we evaluated the impacts of age and cardiovascular disease (CVD) risks on hbPWV cross-sectionally (N = 7868) and longitudinally (N = 3710, followed by 9.1 ± 2.0 years). hbPWV were obtained using two validated equations for arterial path length (with and without considering age-related aortic elongations). Brachial-ankle pulse wave velocity (baPWV) was used as a comparative measure. Repeated-measures correlation (rmcorr) and regression analyses were used to characterize associations of PWVs with age and Framingham\'s general CVD risk score (FRS). In the cross-sectional study, hbPWVs derived by both equations showed stronger correlation with age (r = 0.746 ~ 0.796) and FRS (r = 0.714-0.749) than baPWV (r = 0.554 and r = 0.643). Furthermore, hbPWVs correlated with FRS even after controlling for age (r = 0.260 ~ 0.269, P < 0.0001). In the longitudinal study, hbPWVs demonstrated significantly higher rmcorr coefficient with age than baPWV (rrm=0.439-0.511 vs. 0.307, P < 0.0001). Across the adult lifespan, age-related increases in hbPWVs were almost consistent, starting from young adults, while baPWV displayed accelerated increases with age. A receiver operating characteristic curve analysis indicated that hbPWVs depicted more robust ability to stratify general CVD risk compared with baPWV (AUC = 0.896-0.913 vs. 0.833, P < 0.0001). The results of the follow-up study were consistent with the findings of the cross-sectional investigation. Our findings suggest that hbPWV undergoes a linear augmentation with age, commencing from an early adult life stage onward, rendering it a potential marker for discerning CVD risk.

UNASSIGNED: Cardiovascular disease (CVD) may not be detected in time with conventional clinical approaches. Abnormal gait patterns have been associated with pathological conditions and can be monitored continuously by gait video. We aim to test the association between non-contact, video-based gait information and general CVD status.
UNASSIGNED: Individuals undergoing confirmatory CVD evaluation were included in a prospective, cross-sectional study. Gait videos were recorded with a Kinect camera. Gait features were extracted from gait videos to correlate with the composite and individual components of CVD, including coronary artery disease, peripheral artery disease, heart failure, and cerebrovascular events. The incremental value of incorporating gait information with traditional CVD clinical variables was also evaluated. Three hundred fifty-two participants were included in the final analysis [mean (standard deviation) age, 59.4 (9.8) years; 25.3% were female]. Compared with the baseline clinical variable model [area under the receiver operating curve (AUC) 0.717, (0.690-0.743)], the gait feature model demonstrated statistically better performance [AUC 0.753, (0.726-0.780)] in predicting the composite CVD, with further incremental value when incorporated with the clinical variables [AUC 0.764, (0.741-0.786)]. Notably, gait features exhibited varied association with different CVD component conditions, especially for peripheral artery disease [AUC 0.752, (0.728-0.775)] and heart failure [0.733, (0.707-0.758)]. Additional analyses also revealed association of gait information with CVD risk factors and the established CVD risk score.
UNASSIGNED: We demonstrated the association and predictive value of non-contact, video-based gait information for general CVD status. Further studies for gait video-based daily living CVD monitoring are promising.

The prognostic value of growth differentiation factor-15 (GDF-15) in predicting long-term adverse outcomes in coronary heart disease (CHD) patients remains limited. Our study examines the association between GDF-15 and adverse outcomes over an extended period in CHD patients and firstly assesses the incremental prognostic effect of incorporating GDF-15 into the Framingham risk score (FRS)-based model. This single-center prospective cohort study included 3,321 patients with CHD categorized into 2,479 acute coronary syndrome (ACS) (74.6%) and 842 non-ACS (25.4%) groups. The median age was 61.0 years (range: 53.0-70.0), and 917 (27.6%) were females. Mortality and major adverse cardiovascular events (MACEs) included cardiovascular mortality, myocardial infarction (MI), stroke, and heart failure (HF) (inclusive of HF episodes requiring outpatient treatment and/or hospital admission). Cox regression models assessed the associations between GDF-15 and the incidence of all-cause mortality and MACEs. Patients were stratified into three groups based on GDF-15 levels: the first tertile group (< 1,370 ng/L), the second tertile group (1,370-2,556 ng/L), and the third tertile group (> 2,556 ng/L). The C-index, integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA) were used to assess incremental value. Over a median 9.4-year follow-up, 759 patients (22.9%) died, and 1,291 (38.9%) experienced MACEs. The multivariate Cox model indicated that GDF-15 was significantly associated with all-cause mortality (per ln unit increase, HR = 1.49, 95% CI: 1.36-1.64) and MACEs (per ln unit increase, HR = 1.29, 95% CI: 1.20-1.38). These associations persisted when GDF-15 was analyzed as an ordinal variable (p for trend < 0.05). Subgroup analysis of ACS and non-ACS for the components of MACEs separately showed a significant association between GDF-15 and both cardiovascular mortality and HF, but no association was observed between GDF-15 and MI /stroke in both ACS and non-ACS patients. The addition of GDF-15 to the FRS-based model enhanced the discrimination for both all-cause mortality (∆ C-index = 0.009, 95% CI: 0.005-0.014; IDI = 0.030, 95% CI: 0.015-0.047; continuous NRI = 0.631, 95% CI: 0.569-0.652) and MACEs (∆ C-index = 0.009, 95% CI: 0.006-0.012; IDI = 0.026, 95% CI: 0.009-0.042; continuous NRI = 0.593, 95% CI: 0.478-0.682). DCA suggested that incorporating GDF-15 into the FRS-based model demonstrated higher net benefits compared to FRS-based models alone (All-cause mortality: FRS-based model: area under the curve of DCA (AUDC) = 0.0903, FRS-based model + GDF-15: AUDC = 0.0908; MACEs: FRS-based model: AUDC = 0.1806, FRS-based model + GDF-15: AUDC = 0.1833). GDF-15 significantly associates with the long-term prognosis of all-cause mortality and MACEs in CHD patients and significantly improves the prognostic accuracy of the FRS-based model for both outcomes.

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BACKGROUND: Accurate risk stratification is vital for primary prevention of cardiovascular disease (CVD). However, traditional tools such as the Framingham Risk Score (FRS) may underperform within the diverse intermediate-risk group, which includes individuals requiring distinct management strategies.
OBJECTIVE: This study aimed to develop a lipidomic-enhanced risk score (LRS), specifically targeting risk prediction and reclassification within the intermediate group, benchmarked against the FRS.
METHODS: The LRS was developed via a machine learning workflow using ridge regression on the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab; n = 10,339). It was externally validated with the Busselton Health Study (n = 4,492), and its predictive utility for coronary artery calcium scoring (CACS)-based outcomes was independently validated in the BioHEART cohort (n = 994).
RESULTS: LRS significantly improved discrimination metrics for the intermediate-risk group in both AusDiab and Busselton Health Study cohorts (all P < 0.001), increasing the area under the curve for CVD events by 0.114 (95% CI: 0.1123-0.1157) and 0.077 (95% CI: 0.0755-0.0785), with a net reclassification improvement of 0.36 (95% CI: 0.21-0.51) and 0.33 (95% CI: 0.15-0.49), respectively. For CACS-based outcomes in BioHEART, LRS achieved a significant area under the curve improvement of 0.02 over the FRS (0.76 vs 0.74; P < 1.0 × 10-5). A simplified, clinically applicable version of LRS was also created that had comparable performance to the original LRS.
CONCLUSIONS: LRS, augmenting the FRS, presents potential to improve intermediate-risk stratification and to predict atherosclerotic markers using a simple blood test, suitable for clinical application. This could facilitate the triage of individuals for noninvasive imaging such as CACS, fostering precision medicine in CVD prevention and management.

BACKGROUND: Poor cardiovascular health (CVH) and physical frailty were reported to increase mortality risk, but their joint effects have not been fully elucidated.
OBJECTIVE: We aimed to explore the separate and joint effects of CVH and frailty on mortality based on two perspectives of Life\'s Essential 8 (LE8) and Framingham Risk Score (FRS).
METHODS: 21 062 participants in the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018 were involved in this study. CVH was evaluated by the LE8 and FRS, and categorized into low, moderate and high CVH groups. Cox proportional hazard models were applied to estimate the separate and joint associations of CVH and frailty index (FI) with all-cause, cardiovascular disease (CVD) and cancer mortality.
RESULTS: Over a median follow-up period of 87 months (95% CI: 86.0-88.0), 2036 deaths occurred. The separate linear dose-response relationships between CVH, frailty and mortality were observed (nonlinear P > .05). The combination of low CVH/frailty was negatively associated with all-cause mortality [hazard ratio (HR) and 95%CI: low LE8*FI, 5.30 (3.74, 7.52); high FRS*FI, 4.34 (3.20, 5.88)], CVD mortality [low LE8*FI, 6.57 (3.54, 12.22); high FRS*FI, 7.29 (3.92, 13.55)] and cancer mortality [low LE8*FI, 1.99 (1.14, 3.25); high FRS*FI, 2.32 (1.30, 4.15)], with high CVH/fit group as reference. Further stratified analyses showed that the combined burden of mortality from frailty and low CVH was greater among the young and females.
CONCLUSIONS: Low CVH and frailty were independently and jointly correlated with greater risk of all-cause, CVD and cancer deaths, especially among the young and females.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is associated with increases in morbidity and mortality worldwide. The mechanisms of how SARS-CoV-2 may cause cardiovascular (CV) complications are under investigation. The aim of the study was to assess the impact of the COVID-19 pandemic on CV risk.
METHODS: These are single-centre Bialystok PLUS (Poland) population-based and case‒control studies. The survey was conducted between 2018 and 2022 on a sample of residents (n = 1507) of a large city in central Europe and patients 6-9 months post-COVID-19 infection (n = 126). The Systematic Coronary Risk Estimation 2 (SCORE2), the Systematic Coronary Risk Estimation 2-Older Persons (SCORE2-OP), the Cardiovascular Disease Framingham Heart Study and the LIFEtime-perspective model for individualizing CardioVascular Disease prevention strategies in apparently healthy people (LIFE-CVD) were used. Subsequently, the study populations were divided into CV risk classes according to the 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice.
RESULTS: The study population consisted of 4 groups: a general population examined before (I, n = 691) and during the COVID-19 pandemic (II, n = 816); a group of 126 patients post-COVID-19 infection (III); and a control group matched subjects chosen from the pre-COVID-19 pandemic (IV). Group II was characterized by lower blood pressure, low-density lipoprotein cholesterol (LDL-c) and high-density lipoprotein cholesterol (HDL-c) values than group I. Group III differed from the control group in terms of lower LDL-c level. There was no effect on CV risk in the general population, but in the population post-COVID-19 infection, CV risk was lower using FS-lipids, FS-BMI and LIFE-CVD 10-year risk scores compared to the prepandemic population. In all subgroups analysed, no statistically significant difference was found in the frequency of CV risk classes.
CONCLUSIONS: The COVID-19 pandemic did not increase the CV risk calculated for primary prevention. Instead, it prompted people to pay attention to their health status, as evidenced by better control of some CV risk factors. As the COVID-19 pandemic has drawn people\'s attention to health, it is worth exploiting this opportunity to improve public health knowledge through the design of wide-ranging information campaigns.

UNASSIGNED: Cardiovascular diseases (CVDs) are the leading causes of mortality worldwide. Predicting the 10-year risk of cardiovascular events (CVEs) may save lives through timely intervention. Framingham risk scoring (FRS) can effectively predict this risk.
UNASSIGNED: This study aimed to estimate the 10-year risk of CVE using FRS and to estimate the prevalence of CVD risk factors and their associations with FRS among adults in the West Tripura District of India.
UNASSIGNED: This community-based cross-sectional study was conducted from 1 November 2019 to 30 November 2021 in the West Tripura District of India, using FRS 2008 and a pretested interview schedule among 290 individuals aged ≥ 30 years chosen by multistage sampling.
UNASSIGNED: The majority, that is 61.7%, of the study subjects had low risk, 18.6% had intermediate risk and 19.7% had high risk of CVE within 10 years. The prevalence of hypertension was 55.6%; diabetes mellitus, 55.9%; smoking, 96.2%; dyslipidaemia, 34.3%; alcohol consumption, 96.2%; physical inactivity, 54%; and obesity, 64.6%. The bivariate analysis detected a significant association of FRS with age, sex, residence, literacy, marital status, obesity, smoking, alcoholism, blood pressure (BP), high-density lipoprotein cholesterol (HDL-C) and glycaemic status of the study subjects. The logistic regression analysis has identified age >50 years, male sex, hypertension, smoking and diabetes mellitus as significant determinants of high FRS.
UNASSIGNED: Adults living in the West Tripura District of India have a high prevalence of CVD risk factors. About one-fifth of this population has a high risk of CVE in 10 years. Controlling hypertension, smoking and diabetes mellitus may help reduce this risk.