Predictor Of Cardiovascular Disease Mortality Research Articles

An office-based cardiovascular prediction model developed and validated in cohort studies of a middle-income country

ObjectivePrediction models for cardiovascular disease (CVD) mortality come from high-income countries, comprising laboratory measurements, not suitable for resource-limited countries. This study aims to develop and validate a non-laboratory model to predict CVD mortality in a middle-income setting. Study design and settingWe used data of population aged 40-80 years from three cohort studies: Tehran Lipid and Glucose Study (n = 5160), Isfahan Cohort Study (n = 4350), and Golestan Cohort Study (n = 45,500). Using Cox proportional hazard models, we developed prediction models for men and women, separately. Cross-validation and bootstrapping procedures were applied. The models’ discrimination and calibration were assessed by concordance statistic (C-index) and calibration plot, respectively. We calculated the models' sensitivity, specificity and net benefit fraction in a threshold probability of 5%. ResultsThe 10-year CVD mortality risks were 5.1% (95%CI: 4.8-5.5) in men and 3.1% (95%CI: 2.9%-3.3%) in women. The optimism-corrected performance of the model was c = 0.774 in men and c = 0.798 in women. The models showed good calibration in both sexes, with a predicted-to-observed ratio of 1.07 in men and 1.09 in women. The sensitivity was 0.76 in men and 0.66 in women. The net benefit fraction was higher in men compared to women (0.46 vs. 0.35). ConclusionA low-cost model can discriminate well between low- and high-risk individuals, and can be used for screening in low-middle income countries.

Impact of genetic risk score on the association between male childlessness and cardiovascular disease and mortality

Childless men are reported to have a higher risk of cardiovascular disease (CVD) and mortality. Information on inherited genetic risk for CVD has improved the predictive models. Presuming that childlessness is a proxy of infertility we aimed to investigate if childless men inherit more often genetic traits for CVD and if combining genetic and parenthood information improves predictive models for CVD morbidity and mortality. Data was sourced from a large prospective population-based cohort where genetic risk score (GRS) was calculated using two sets of either 27 (GRS 27) or 50 (GRS 50) single nucleotide polymorphisms (SNPs) previously found to be associated with CVD. Part of the participants (n = 2572 men) were randomly assigned to a sub-cohort with focus on CVD which served as an exploratory cohort. The obtained statistically significant results were tested in the remaining (confirmatory) part of the cohort (n = 9548 men). GRS distribution did not differ between childless men and fathers (p-values for interaction between 0.29 and 0.76). However, when using fathers with low GRS as reference high GRS was a strong predictor for CVD mortality, the HR (95% CI) increasing from 1.92 (1.10–3.36) for GRS 50 and 1.54 (0.87–2.75) for GRS 27 in fathers to 3.12 (1.39–7.04) for GRS50 and 3.73 (1.75–7.99) for GRS27 in childless men. The confirmatory analysis showed similar trend. Algorithms including paternal information and GRS were more predictive for CVD mortality at 5 and 10 years follow-ups when compared to algorithms including GRS only (AUC 0.88 (95% CI 0.84–0.92) and 0.86 (95% CI 0.84–0.90), and, AUC 0.81 (95% CI 0.75–0.87) and 0.78 (95% CI 0.73–0.82), respectively). Combining information on parental status and GRS for CVD may improve the predictive power of risk algorithms in middle-aged men. Childless men and those with severe infertility problem may be an important target group for prevention of CVD.

Obstructive sleep apnea predicts 10-year cardiovascular disease-related mortality in the Sleep Heart Health Study: a machine learning approach.

Obstructive sleep apnea (OSA) is considered to be an important risk factor for the development of cardiovascular disease (CVD). This study aimed to develop and evaluate a machine learning approach with a set of features for assessing the 10-year CVD mortality risk of the OSA population. This study included 2,464 patients with OSA who met study inclusion criteria and were selected from the Sleep Heart Health Study. We evaluated the importance of potential features by mutual information. The top 9 features were selected to develop a random forest model. We evaluated the model performance on a test set (n = 493) using the area under the receiver operating curve with 95% confidence interval and confusion matrix. A random forest model awarded the highest area under the receiver operating curve of 0.84 (95% confidence interval: 0.78-0.89). The specificity and sensitivity were 73.94% and 81.82%, respectively. Sixty-three years old was a threshold for increased risk of 10-year CVD mortality. Persons with severe OSA had higher risk than those with mild OSA. This study demonstrated that a random forest model can provide a quick assessment of the risk of 10-year CVD mortality. Our model may be more informative for patients with OSA in determining their future CVD mortality risk. Li A, Roveda JM, Powers LS, Quan SF. Obstructive sleep apnea predicts 10-year cardiovascular disease-related mortality in the Sleep Heart Health Study: a machine learning approach. J Clin Sleep Med. 2022;18(2):497-504.

A Decreased Level of Soluble Klotho Can Predict Cardiovascular Death in No or Mild Abdominal Aortic Calcification Hemodialysis Patients.

Background: Soluble Klotho plays an important role in cardiovascular disease and death in chronic kidney disease (CKD). We assessed the relationship between serum soluble Klotho (sKL) level and outcome in MHD patients.Methods: Soluble Klotho was detected by ELISA. Cox regression analysis and Kaplan-Meier analysis showed the relationship between sKL and cardiovascular disease (CVD) mortality in maintenance hemodialysis (MHD) patients.Results: There were 45 cases (35.2%) of all-cause death and 36 cases (28.1%) of CVD mortality. Multivariate linear regression analysis showed that Log[iPTH] (γ = −0.224, P = 0.015) was an independent predictor of sKL level. Cox regression showed that lower sKL was associated with higher CVD mortality rate [OR = 0.401, 95% CI (0.183–0.867), P = 0.022]. Kaplan-Meier analysis showed that the CVD mortality rate increased significantly in patients with low sKL (P = 0.006). Compared with high sKL patients, low sKL patients with no or mild vascular calcification [aortic calcification score (AACs) ≤ 4] had no significant difference in all-cause mortality rate. The CVD mortality rate was significantly lower in high sKL patients (P = 0.004) than in those with low sKL. In the severe calcification group (AACs ≥ 5), all-cause and CVD mortality rates were similar between different sKL groups (P = 0.706 and 0.488, respectively). The area under the receiver-operating characteristic curve (AUC) of soluble Klotho for predicting the CVD in MHD patients with AACs ≤ 4 was 0.796 (0.647–0.946, P = 0.017), sensitivity was 0.921, and specificity was 0.50 for a cutoff value of 307.69 pg/ml.Conclusions: Lower sKL was associated with higher CVD mortality rate. Lower sKL concentration in MHD patients with no or mild calcification can predict CVD mortality.

Arterial stiffness is associated with cardiovascular and cancer mortality in cancer patients: Insight from NHANESIII

BackgroundCancer survivors are at greater risk for cardiovascular disease (CVD) than second malignancy, resulting in a decreased quality of life and increased cost of care. Additional knowledge of CVD prevention by identifying possible risk factors has clinical relevance. Our main objective was to determine the relevance of a clinical index of arterial stiffness, pulse pressure, in predicting CVD mortality in cancer patients, with a second objective to examine its relationship with cancer mortality. MethodsWe retrospectively analyzed 781 cancer patients from Third National Health and Nutrition Examination Survey and Linked Mortality File, including demographic, anthropometric, blood pressure, and cause of death. Kaplan-Meier survival curve and Cox hazard regression analyses were performed to assess the relationship between pulse pressure and cardiovascular, cancer, and all-cause mortality. ResultsDuring a mean follow-up time of 8.1 years, 603 deaths, 257 cancer and 151 CVD, occurred. In unadjusted models, the risk of CVD, cancer, and all-cause mortality were 3.8-fold, 5.3-fold, and 1.6-fold higher, respectively, for pulse pressure ≥70 ​mmHg compared to <50 ​mmHg. Adjusted analyses revealed a higher CVD mortality in cancer patients <65 years with a pulse pressure 60–70 ​mmHg (adjusted hazard ratio, 5.26; 95%CI, 1.12–24.78) when compared to pulse pressure of <50 ​mmHg. Pulse pressure was not associated with risk of all-cause, CVD, or cancer in those ≥65 years. ConclusionPulse pressure, an index of arterial stiffness, is predictive of CVD mortality in cancer patients. Our findings support non-invasive office-setting measurements of arterial stiffness to identify high risk patients.

Predicting Australian Adults at High Risk of Cardiovascular Disease Mortality Using Standard Risk Factors and Machine Learning.

Effective cardiovascular disease (CVD) prevention relies on timely identification and intervention for individuals at risk. Conventional formula-based techniques have been demonstrated to over- or under-predict the risk of CVD in the Australian population. This study assessed the ability of machine learning models to predict CVD mortality risk in the Australian population and compare performance with the well-established Framingham model. Data is drawn from three Australian cohort studies: the North West Adelaide Health Study (NWAHS), the Australian Diabetes, Obesity, and Lifestyle study, and the Melbourne Collaborative Cohort Study (MCCS). Four machine learning models for predicting 15-year CVD mortality risk were developed and compared to the 2008 Framingham model. Machine learning models performed significantly better compared to the Framingham model when applied to the three Australian cohorts. Machine learning based models improved prediction by 2.7% to 5.2% across three Australian cohorts. In an aggregated cohort, machine learning models improved prediction by up to 5.1% (area-under-curve (AUC) 0.852, 95% CI 0.837–0.867). Net reclassification improvement (NRI) was up to 26% with machine learning models. Machine learning based models also showed improved performance when stratified by sex and diabetes status. Results suggest a potential for improving CVD risk prediction in the Australian population using machine learning models.

Objective Sleep Efficiency Predicts Cardiovascular Disease in a Community Population: The Sleep Heart Health Study.

BackgroundThere was little evidence about the role of objective sleep efficiency (SE) in the incidence of major cardiovascular disease (CVD) events. The purpose of this study was to investigate the correlation between objective SE and CVD based on polysomnography.Methods and ResultsA total of 3810 participants from the SHHS (Sleep Heart Health Study) were selected in the current study. CVD was assessed during an almost 11‐year follow‐up period. The primary composite cardiovascular outcome was major adverse cardiovascular events, defined as CVD mortality, congestive heart failure, myocardial infarction, and stroke. The secondary composite cardiovascular outcome was major adverse cardiovascular event plus revascularization. Objective measured SE, including SE and wake after sleep onset, was based on in‐home polysomnography records. Cox regression analysis was used to explore the association between SE and CVD. After multivariate Cox regression analysis, poor SE (<80%) was significantly associated with primary (hazard ratio [HR], 1.338; 95% CI, 1.025–1.745; P=0.032) and secondary composite cardiovascular outcomes (HR, 1.250; 95% CI, 1.027–1.521; P=0.026); it was also found to be a predictor of CVD mortality (HR, 1.887; 95% CI, 1.224–2.909; P=0.004). Moreover, wake after sleep onset of fourth quartile (>78.0 minutes) was closely correlated with primary (HR, 1.436; 95% CI, 1.066–1.934; P=0.017), secondary composite cardiovascular outcomes (HR, 1.374; 95% CI, 1.103–1.712; P=0.005), and CVD mortality (HR, 2.240; 95% CI, 1.377–3.642; P=0.001).ConclusionsPoor SE and long wake after sleep onset, objectively measured by polysomnography, were associated with the increased risk of incident CVD.

HDL, apo a1 and long-term cardio-metabolic prognosis in statin-treated patients with suspected stable angina pectoris: a prospective cohort study

Abstract Background Reduced serum levels of high density lipoprotein cholesterol (HDL-C) is a hallmark of the metabolic syndrome. Epidemiologic studies have reported an inverse correlation between HDL- C and cardiovascular disease (CVD) risk. However, recent works suggest that the association is strongest in healthy individuals. Changes in particle number and functional properties of HDL may more closely reflect CVD prognosis in patients with pre-existent disease. The majority of such patients receive statin treatment, which affects both HDL-C levels, and particle composition. Hence, serum apoA1 and the HDL-C:apoA1 ratio have been proposed as more sensitive indicators of cardio-metabolic prognosis. Purpose We studied the associations of serum HDL-C, apoA1 and the HDL-C: apoA1 ratio to long term risk of CVD mortality and incident type 2 diabetes (T2D) patients with suspected stable angina pectoris (SAP). Methods A total of 41064 patients underwent elective coronary angiography in 2000–2004 and were followed-up for CVD mortality throughout 2016. In a subgroup of 2519 participants without verified or possible diabetes at baseline, the associations to incident type 2 diabetes (T2D) were evaluated throughout 2014. Information on clinical endpoints was obtained through national health registries. Risk estimates are reported per 1 SD increment of (log transformed) biomarkers and were calculated by cox or logistic regression. We explored risk classification by calculating the continuous net reclassification improvement (NRI). Results At inclusion, median (25th-75th percentiles) age was 62 (55–70) years, 28% were women 76% had obstructive coronary artery disease and 80% received statins. During median (25th-75th percentiles) 13.9 (12.0–15.3) years of follow-up, 14.1% of the participants died from CVD. After multivariate adjustment (age, gender, body mass index, HbA1c, triglycerides, statin treatment, fasting status) HDL and apoA1, but not the HDL: apoA1 ratio, significantly predicted CVD mortality. The hazard ratio (HR) and 95% confidence interval (CI) was: 0.86 (0.78–0.94), 0.88 (0.80–0.98) and 0.96 (0.86–1.03) for HDL-C, apoA1 and the HDL-C:apoA1 ratio, respectively. HDL-C was the only of the evaluated biomarkers providing a significant NRI (95% CI) of 0.14 (0.04–0.19). In the subset evaluated for incdent T2D, HDL-C provided multivariate adjusted odds ratios (OR; 95% CI) and NRI (95% CI) of 0.69 (0.58–0.82) and 0.34 (0.21–0.47) for new onset TSD. The corresponding OR (95% CI) and NRI (95% CI) for apoA1 were: 0.85 (0.73–0.99) and 0.20 (0.06–0.33), respectively. The HDL:apo A1 ratio provided an OR (95% CI) of 0.66 (0.55–0.80) and NRI (95% CI) of 0.24 (0.11–0.37) for T2D. No significant effect modifications according to statin treatment were found (P≥0.22). Conclusion Among patients with suspected SAP, of which the majority received statins, HDL-C was non-inferior to apoA1 and the HDL:apoA1 ratio in predicting long term risk of CVD mortality and T2D. Funding Acknowledgement Type of funding source: Public hospital(s). Main funding source(s): Department of Heart Disease, Haukeland University Hospital; Department of Clinical Science, University of Bergen

The effects of loneliness and social isolation on all-cause, injury, cancer, and CVD mortality in a cohort of middle-aged Finnish men. A prospective study

Objectives Loneliness and social isolation both increase mortality and are likely to affect health via several pathways. However, information on the potential pathways remains scarce. We investigated the associations between loneliness, social isolation, and mortality, and possible mechanisms underlying these connections. Methods The analyzed data comprised a prospective population-based cohort of Finnish men (42–61 years at baseline, n = 2588) who were followed up for an average of 23.2 years. Mortality data were obtained from the national population register in 2012. Cox proportional hazards analysis with adjustments for possible confounding factors was used to examine the associations between loneliness and social isolation at baseline and all-cause, injury, cancer, and cardiovascular disease (CVD) mortality. Mediation analysis was conducted to investigate the mechanisms underlying the associations of loneliness and social isolation with mortality. Results Loneliness predicted all-cause mortality, even after adjustments for all covariates. Loneliness predicted cancer mortality, except after adjustments for lifestyle variables or Human Population Laboratory (HPL) depression scores, and also predicted CVD mortality, except after adjustments for HPL depression scores. Social isolation predicted all-cause mortality and injury mortality. The effect of social isolation on all-cause mortality was mediated by loneliness and HPL depression scores. Conclusions Our findings suggest that both loneliness and social isolation increase the risk of all-cause mortality, while they have differing effects on different causes of death. Loneliness and depressive symptoms may mediate the effect of social isolation on increased mortality.

Prediction of Cardiovascular Disease Mortality in a Middle Eastern Country: Performance of the Globorisk and Score Functions in Four Population-Based Cohort Studies of Iran.

Background: Considering the importance of cardiovascular disease (CVD) risk prediction for healthcare systems and the limited information available in the Middle East, we evaluated the SCORE and Globorisk models to predict CVD death in a country of this region. Methods: We included 24 427 participants (11 187 men) aged 40-80 years from four population-based cohorts in Iran. Updating approaches were used to recalibrate the baseline survival and the overall effect of the predictors of the models. We assessed the models’ discrimination using C-index and then compared the observed with the predicted risk of death using calibration plots. The sensitivity and specificity of the models were estimated at the risk thresholds of 3%, 5%, 7%, and 10%. An agreement between models was assessed using the intra-class correlation coefficient (ICC). We applied decision analysis to provide perception into the consequences of using the models in general practice; for this reason, the clinical usefulness of the models was assessed using the net benefit (NB) and decision curve analysis. The NB is a sensitivity penalized by a weighted false positive (FP) rate in population level. Results: After 154 522 person-years of follow-up, 437 cardiovascular deaths (280 men) occurred. The 10-year observed risks were 4.2% (95% CI: 3.7%-4.8%) in men and 2.1% (1.8-2%.5%) in women. The c-index for SCORE function was 0.784 (0.756-0.812) in men and 0.780 (0.744-0.815) in women. Corresponding values for Globorisk were 0.793 (0.766- 0.820) and 0.793 (0.757-0.829). The deviation of the calibration slopes from one reflected a need for recalibration; after which, the predicted-to-observed ratio for both models was 1.02 in men and 0.95 in women. Models showed good agreement (ICC 0.93 in men, and 0.89 in women). Decision curve showed that using both models results in the same clinical usefulness at the risk threshold of 5%, in both men and women; however, at the risk threshold of 10%, Globorisk had better clinical usefulness in women (Difference: 8%, 95% CI: 4%-13%). Conclusion: Original Globorisk and SCORE models overestimate the CVD risk in Iranian populations resulting in a high number of people who need intervention. Recalibration could adopt these models to precisely predict CVD mortality. Globorisk showed better performance clinically, only among high-risk women.

Is Cumulative Time of Oxygen Desaturation a Better Predictor of Cardiovascular Mortality than Apnoea Hypopnoea Index?

In this paper, we explored the link between sleep apnoea and cardiovascular disease (CVD) using a time-series statistical measure of sleep apnoea-related oxygen desaturation. We compared the performance of a hypoxic measure derived from the polysomnogram with the Apnoea Hypopnoea Index (AHI) in predicting CVD mortality in patients of the Sleep Heart Health Study.We estimated the relative cumulative time of SpO2 below 90% (Tr90) using pulse oximetry signals from polysomnogram recordings as the hypoxic measure of desaturation patterns. Then, the survival curves for hypoxia quintiles were evaluated for the prediction of CVD mortality and were compared with the results using AHI for prediction. We also calculated the Cox hazard ratios for Tr90 and AHI. Our results show that the Tr90 was a better predictor of CVD mortality outcomes than AHI.

Low levels of antibodies for the oral bacterium Tannerella forsythia predict cardiovascular disease mortality in men with myocardial infarction: A prospective cohort study

Antibody levels to periodontal pathogens in prediction of cardiovascular disease (CVD) mortality were explored using data from a health survey in Oslo in 2000 (Oslo II-study) with 12 1/2 years follow-up. IgG antibodies to four common periodontal pathogens; Tannerella forsythia (TF), Porphyromonas gingivalis (PG), and Treponema denticola (TD) all termed collectively the “red complex”, and Aggregatibacter actinomycetemcomitans(AA) were analysed. The study sample consisted of 1172 men drawn from a cohort of 6,530 men who participated in the Oslo II-study, where they provided information on medical and dental history. Of the study sample, 548 men had reported prior myocardial infarction (MI) at baseline whereas the remaining 624 men were randomly drawn from the ostensibly healthy participants for comparative analyses. Dental anamnestic information included tooth extractions and oral infections. An inverse relation was found for trend by the quartile risk level of TF predicting CVD mortality, p-value for trend = 0.017. Comparison of the first to fourth quartile of TF antibodies resulted in hazard ratio (HR) = 1.82, 95% confidence interval 1.12–2.94, p = 0.015, adjusted for age, education, diabetes, daily smoking, and systolic blood pressure. Specificity comparing decile 1 to deciles 2–10 of TF predicting mortality was 92.3%. We found an increased HR by low levels of antibodies to the bacterium T. forsythia predicting CVD mortality in a 12 ½ years follow-up in persons who had experienced an MI but not among non-MI men. This novel finding constitutes a plausible causal link between oral infections and CVD mortality.

Contribution of income and job strain to the association between education and cardiovascular disease in 1.6 million Danish employees.

AimsWe examined the extent to which associations between education and cardiovascular disease (CVD) morbidity and mortality are attributable to income and work stress.Methods and resultsWe included all employed Danish residents aged 30–59 years in 2000. Cardiovascular disease morbidity analyses included 1 638 270 individuals, free of cardiometabolic disease (CVD or diabetes). Mortality analyses included 41 944 individuals with cardiometabolic disease. We assessed education and income annually from population registers and work stress, defined as job strain, with a job-exposure matrix. Outcomes were ascertained until 2014 from health registers and risk was estimated using Cox regression. During 10 957 399 (men) and 10 776 516 person-years (women), we identified 51 585 and 24 075 incident CVD cases, respectively. For men with low education, risk of CVD was 1.62 [95% confidence interval (CI) 1.58–1.66] before and 1.46 (95% CI 1.42–1.50) after adjustment for income and job strain (25% reduction). In women, estimates were 1.66 (95% CI 1.61–1.72) and 1.53 (95% CI 1.47–1.58) (21% reduction). Of individuals with cardiometabolic disease, 1736 men (362 234 person-years) and 341 women (179 402 person-years) died from CVD. Education predicted CVD mortality in both sexes. Estimates were reduced with 54% (men) and 33% (women) after adjustment for income and job strain.ConclusionLow education predicted incident CVD in initially healthy individuals and CVD mortality in individuals with prevalent cardiometabolic disease. In men with cardiometabolic disease, income and job strain explained half of the higher CVD mortality in the low education group. In healthy men and in women regardless of cardiometabolic disease, these factors explained 21–33% of the higher CVD morbidity and mortality.

Cardiovascular Risk in COPD: Deciphering the Contribution of Tobacco Smoking

The observation that COPD is an independent risk factor for cardiovascular disease (CVDs) comes from comparisons between smokers with COPD and smokers without COPD. The mechanisms that explain increased risk of CVD in patients with COPD are still unclear. The goal of this study was to assess systemic arterial stiffness (a predictor of CVD mortality) and to evaluate its determinants in a group of patients with mild to moderate COPD secondary to organic dust exposure, tobacco smoking, or both. Systemic arterial stiffness was assessed by using aortic pulse wave velocity (aPWV). Measurements were made in 142 patients with COPD and 155 healthy controlsubjects matched for age, sex, BMI, and tobacco smoking, exposed to tobacco smoking (n= 56/70 for COPD/control subjects, respectively), organic dusts (n= 44/48), or both (n= 42/37). aPWV was higher in COPD than in healthy controls in subjects exposed to tobacco smoking and to both organic dusts and tobacco smoking. By contrast, among never smokers exposed to organic dusts, patients with COPD and matched control subjects had similar aPWV. Multivariate analysis of the 142 patients with COPD (exposed to tobacco smoking and/or to organic dusts) showed that tobacco smoking was associated with high aPWV. Moreover, soluble suppression of tumorigenicity 2, a marker of major cardiovascular events, was correlated with aPWV in these patients. Analysis of an unselected group of patients with COPD with different causessuggests that: (1) COPD by itself is not sufficient to explain increased aPWV; and (2) tobacco smoking is a risk factor for elevated aPWV in COPD.

Does Information on Blood Heavy Metals Improve Cardiovascular Mortality Prediction?

BackgroundTo evaluate whether blood markers of lead, cadmium, and mercury can improve prediction for cardiovascular disease (CVD) mortality when added individually, jointly, or as an integrative index/Environmental Risk Score (ERS), in a model with established risk factors.Methods and ResultsOur study sample comprised 16 028 adults aged ≥40 years who were enrolled in the National Health and Nutrition Examination Survey 1999–2012 and followed up through December 31, 2015. The study sample was randomly split into training for the ERS construction (n=8043) and testing for the evaluation of prediction performance (n=7985). ERS was computed using elastic‐net penalized Cox's model based on the selected metal predictors predicting CVD mortality. During median follow‐up of 7.2 years, 517 died from CVD. In the training set, linear terms of cadmium and mercury, squared terms of lead and mercury, and all 3 pairwise interactions were selected by elastic‐net for ERS construction. In the testing set, the C‐statistic increased from 0.845 when only established CVD risk factors were in the model to 0.854 when the ERS was additionally added to the model. Addition of all linear, squared, and pairwise interaction terms of blood metals to the Cox's models improved C‐statistic from 0.845 to 0.857. The improvement remained significant when it was assessed by net reclassification improvement and integrated discrimination improvement.ConclusionsOur findings suggest that blood markers of toxic metals can improve CVD risk prediction over the established risk factors and highlight their potential utility for CVD risk assessment, prevention, and precision health.

1446A greater healthy behaviors score is associated with a lower risk of all-cause and cause specific mortality: insight from two prospective multi-ethnic surveys

Abstract Background Mortality from non-communicable diseases (NCDs) is influenced bymodifiable risk factors. Simple tools which do not require laboratory tests, (blood pressure (BP) [B], exercise [E], weight [W], alimentation [A] (fruit and vegetable consumption), and tobacco [T] (BEWAT) may estimate the risk of all-cause and cause specific mortality. Purpose Therefore, we evaluated the link between BEWAT and mortality in a randomly selected sample of the US population. Method Adults aged ≥20 years, enrolled in the Third National Health and Nutrition Examination Survey (NHANES-III, 1988–1994) and continuous NHANES (2005–2010), and followed up to December 31st 2011, were included in the present analysis. Multiple Cox regressionswere applied to evaluate the associations between the total BEWAT score and each of its components with all-cause and cause specific mortality. Results Overall, 22,968 participants (47.1% men) were included in the present analysis (mean age: 47.4 years). Individuals in the highest BEWAT tertile (T3) had a 25% lower risk of mortality compared with T1 [hazard ratio (HR): 0.75, 95% confidence interval (CI): 0.71–0.79], further corrections slightly diluted the magnitude of link to 22% (HR: 0.78, 95% CI: 0.75–0.81) (Figure). In a fully adjusted model, individuals in T3 also had a 26% lower risk of cardiovascular disease (CVD) mortality compared with those in T1 (HR: 0.74, 95% CI: 0.64–0.83), similar trends were observed across the BEWAT tertiles for cancer mortality risk (participants in T3 had a 31 and 26% lower risk for cancer death in Models 1 and 2, respectively). For sensitivity analyses after excluding smoking from the total BEWAT score, in the fully adjusted model the association between the BEWAT score and cancer death was attenuated but remained significant (HR: 0.80, 95% CI: 0.72–0.89 for T3 vs T1). Furthermore, total BEWAT score (without the BP component) could still predict CVD mortality (T3= HR: 0.71, 95% CI: 0.61–0.82). All-cause death and BEWAT tertiles. Conclusion A higher BEWAT status is beneficial regarding all-cause and cause specific mortality. Our results highlight the value of modifiable risk factors as a simple and affordable variable for evaluating the risk of mortality.

Arterial stiffness and 5-year mortality in patients with peripheral arterial disease.

Among patients with peripheral arterial disease (PAD) the risk of mortality remains extremely high. We investigated whether arterial stiffness evaluated by aortic Pulse Wave Velocity (aPWV) and Augmentation index normalized for a standard heart rate of 75 bpm (Aix@75), predict cardiovascular disease (CVD) and total mortality in PAD and No-PAD patients. In 231 PAD patients (ankle-brachial index-ABI ≤ 0.9) and 167 No-PAD (ABI ≥ 0.91 < 1.3) the aPWV and Aix @75HR were evaluated using arterial tonometry and ABI values were obtained using an 8-MHz Doppler probe. The CVD and total mortality rates in relation to aPWV and Aix@75HR were analyzed using Cox regression model. During a mean follow-up of 5.4 ± 2 years 39 (16.9%) deaths occurred in PAD patients and 8 (4.8%) in No-PAD. In the population study, the age was a predictor of CVD mortality (HR = 0.143, 95% CI, 0.06-0.23; p = 0.0004) while the aPWV, was a predictor of total mortality (HR = 1.18, 95% CI, 1.07-1.30; p = 0.0008). In the PAD group, the aPWV remained associated with an increased risk for total mortality (HR = 1.14, 95% CI, 1.03-1.27; p = 0.010). An increase of aPWV may be an indicator of total mortality in PAD patients.

Cardiorespiratory Fitness, Different Measures of Adiposity, and Cardiovascular Disease Mortality Risk in Women.

Background: Associations among cardiorespiratory fitness (CRF), different adiposity exposures, and cardiovascular disease (CVD) mortality in women are not well defined. Materials and Methods: A total of 19,838 women completed a baseline examination between 1971 and 2013. Measures included body mass index (BMI), waist circumference (WC), waist-to-height (W:HT) ratio, skinfold-derived percent body fat (% Fat), and CRF estimated from a maximal treadmill test. CRF categories were low (quintile 1), moderate (quintiles 2-3), and high (quintiles 4-5); standard cut points were used for adiposity exposures. Hazard ratios (HRs) were estimated using Cox regression. Results: During a mean follow-up period of 19.2 ± 10.3 years, 391 cardiovascular deaths occurred. HRs (95% confidence interval) for CVD in moderate and low CRF groups, using high CRF as the referent, were 1.87 (1.46-2.38) and 2.54 (1.93-3.35), respectively (p trend <0.001). HRs of obese women within each adiposity exposure were higher when compared with normal-weight women (p ≤ 0.03). Joint associations of CRF × adiposity showed a positive trend in CVD mortality across decreasing categories of CRF within each category of W:HT and % Fat, as well as within the normal and overweight BMI categories and the normal WC category (p ≤ 0.03 for each). Conclusion: Higher levels of CRF are associated with lower CVD mortality risk in women, and predict lower risk of CVD mortality in normal-weight women and in obese women. Using different measures of adiposity to predict CVD mortality risk in women may be misleading unless CRF is taken into account. These results support the American Heart Association (AHA) recommendation for including CRF as a clinical vital sign.

Development and validation of a ceramide- and phospholipid-based cardiovascular risk estimation score for coronary artery disease patients.

Distinct ceramide lipids have been shown to predict the risk for cardiovascular disease (CVD) events, especially cardiovascular death. As phospholipids have also been linked with CVD risk, we investigated whether the combination of ceramides with phosphatidylcholines (PCs) would be synergistic in the prediction of CVD events in patients with atherosclerotic coronary heart disease in three independent cohort studies. Ceramides and PCs were analysed using liquid chromatography-mass spectrometry (LC-MS) in three studies: WECAC (The Western Norway Coronary Angiography Cohort) (N = 3789), LIPID (Long-Term Intervention with Pravastatin in Ischaemic Disease) trial (N = 5991), and KAROLA (Langzeiterfolge der KARdiOLogischen Anschlussheilbehandlung) (N = 1023). A simple risk score, based on the ceramides and PCs showing the best prognostic features, was developed in the WECAC study and validated in the two other cohorts. This score was highly significant in predicting CVD mortality [multiadjusted hazard ratios (HRs; 95% confidence interval) per standard deviation were 1.44 (1.28-1.63) in WECAC, 1.47 (1.34-1.61) in the LIPID trial, and 1.69 (1.31-2.17) in KAROLA]. In addition, a combination of the risk score with high-sensitivity troponin T increased the HRs to 1.63 (1.44-1.85) and 2.04 (1.57-2.64) in WECAC and KAROLA cohorts, respectively. The C-statistics in WECAC for the risk score combined with sex and age was 0.76 for CVD death. The ceramide-phospholipid risk score showed comparable and synergistic predictive performance with previously published CVD risk models for secondary prevention. A simple ceramide- and phospholipid-based risk score can efficiently predict residual CVD event risk in patients with coronary artery disease.

Serum nitric oxide metabolites and hard clinical endpoints: a population-based prospective study

Objective. Limited data are available regarding prognostic value of nitric oxide metabolites (NOx) for clinical hard end points. In this study, we defined optimum cut-off values of serum NOx for predicting all-cause and cardiovascular disease (CVD) mortality events and prospectively investigated their hazards in the presence of traditional risk factors. Design. Serum NOx concentrations were measured at baseline (2006–2008) and 3520 adult men and women were followed during 7.7 years for all-cause and cardiovascular disease (CVD) mortality. To determine the optimal cut-off points of serum NOx, the receiver operator characteristic (ROC) curve analysis was used. Multivariate Cox proportional hazard models were used to estimate the hazard ratios (HRs) with 95% confidence intervals (95% CIs) of all-cause and CVD mortality below and above the defined optimal cut-off points of serum NOx. Results. Mean age of participants was 44.5 ± 16.0 years at baseline and 40.2% were male. Median (inter-quartile range) of serum NOx levels was 25.0 µmol/L (19.0–37.0), at baseline. The optimal cut-off points of serum NOx levels for predicting CVD and all-cause mortality were 30.5 and 32.5 µmol/L, respectively. In the presence of age, sex, body mass index, smoking, type 2 diabetes, hypertension, and history of CVD, a significant increased risk of CVD mortality (HR = 1.98, 95% CI = 1.10–3.58) and all-cause mortality (HR = 1.52, 95% CI = 1.05–2.21) was observed for serum NOx values higher than their cut-offs. Conclusion. Serum NOx level may be predictor of CVD mortality and death, in general populations.