Predictor Of Cardiovascular Disease Mortality Research Articles

Deep learning to predict cardiovascular mortality from aortic disease in heavy smokers

AbstractAortic angiopathy is a common manifestation of cardiovascular disease (CVD) and may serve as a surrogate marker of CVD burden. While the maximum aortic diameter is the primary prognostic measure, the potential of other features to improve risk prediction remains uncertain. This study developed a deep learning framework to automatically quantify thoracic aortic disease features and assessed their prognostic value in predicting CVD mortality among heavy smokers. Using non-contrast chest CTs from the National Lung Screening Trial (NLST), aortic features quantified included maximum diameter, volume, and calcification burden. Among 24,770 participants, 440 CVD deaths occurred over a mean 6.3-year follow-up. Aortic calcifications and volume were independently associated with CVD mortality, even after adjusting for traditional risk factors and coronary artery calcifications. These findings suggest that deep learning-derived aortic features could improve CVD risk prediction in high-risk populations, enabling more personalized prevention strategies.

#1961 Cardiovascular-kidney-metabolic syndrome components and cardio-vascular disease mortality based on half-a-million Asian adults

Abstract Background and Aims The American Heart Association (AHA) has recently issued guidelines addressing the “Cardiovascular-Kidney-Metabolic (CKM) Syndrome” to mitigate cardiovascular diseases. In parallel, European healthcare entities have established the CaReMe (CArdioRenal and MEtabolic) Partnership, emphasizing interdisciplinary health concepts. This study aims to evaluate CKM prevalence and its associated components in a substantial Asian cohort, along with the risk of cardiovascular mortality. Method The investigation focused on a cohort of 565 940 participants aged 20 years and above enrolled in a health screening program in Taiwan spanning from 1994 to 2017. The study assessed cardiovascular disease (CVD) and cause-specific mortality related to CKM stages and its components—hypertension, diabetes, chronic kidney disease, metabolic syndrome, and hyperlipidemia. Multivariable Cox proportional hazards models were employed to calculate hazard ratios (HRs). Results In this cohort with more than half-a-million Asian adults, approximately 74.3% exhibit CKM syndrome, distributed as 28.1% in Stage 1, 38.9% in Stage 2, 4.9% in Stage 3, and 2.4% in Stage 4. Among individuals aged 50 and above, almost 90% had CKM. The CKM components—hypertension (20.5%), chronic kidney disease (CKD) (11.1%), hyperlipidemia (28.4%), metabolic syndrome (13.1%), and diabetes (5.5%)—display diverse prevalence rates. We identified 13,449 participants who had CVD mortality, and the median follow-up was 15 years. CKM predicts CVD mortality with a dose-response relationship: Hazard Ratios (HRs) for Stage 2 is 2.34 (95% confidence interval (CI): 2.06, 2.65); HR for Stage 3 is 2.69 (95% CI: 2.36, 3.07), and HR for Stage 4 is 4.70 (95% CI: 4.11, 5.39). Within CKM, 43.3% have two or more components, 20.4% have three or more, and 7.3% have four or more. In those aged 65 and above, 66.6% have two or more components, 37.9% have three or more, and 17.8% have four or more. Participants with two or more components exhibit a higher CVD mortality risk than those with a single CKM component. Conclusion The prevalence rates of CKM and its components vary, contributing to distinct risks of cardiovascular disease mortality. A clustering phenomenon exists among different components, where an increased number of clustered factors corresponds to a higher risk of cardiovascular disease mortality.

Hypoxic indices for obstructive sleep apnoea severity and cardiovascular disease risk prediction: A comparison and application in a community population.

The apnoea-hypopnoea index (AHI) and oxygen desaturation index (ODI) encounter challenges in capturing the intricate relationship between obstructive sleep apnoea (OSA) and cardiovascular disease (CVD) risks. Although novel hypoxic indices have been proposed to tackle these limitations, there remains a gap in comprehensive validation and comparisons across a unified dataset. Samples were derived from the Sleep Heart Health Study (SHHS), involving 4485 participants aged over 40 years after data quality screening. The study compared several key indices, including AHI, ODI, the reconstructed hypoxic burden (rHB), the percentage of sleep time with the duration of respiratory events causing desaturation (pRED_3p) and the sleep breathing impairment index (SBII), in relation to CVD mortality and morbidity risks. Adjusted Cox proportional models were employed to calculate hazard ratios (HRs) for each index, and comparisons were performed. SBII and pRED_3p exhibited significant correlations with both CVD mortality and morbidity, with SBII showing the highest adjusted HR (95% confidence interval) for mortality (2.04 [1.25, 3.34]) and pRED_3p for morbidity (1.43 [1.09-1.88]). In contrast, rHB was only significant in predicting CVD mortality (1.63 [1.05-2.53]), while AHI and ODI did not show significant correlations with CVD outcomes. The adjusted models based on SBII and pRED_3p exhibited optimal performance in the CVD mortality and morbidity datasets, respectively. This study identified the optimal indices for OSA-related CVD risks prediction, SBII for mortality and pRED_3p for morbidity. The open-source online platform provides the computation of the indices.

ASSOCIATION OF BLOOD PRESSURE WITH MORTALITY IN OLDEST OLD PEOPLE WITH FRAILTY IN CHINA: RESULTS FROM CHINESE LONGITUDINAL HEALTHY LONGEVITY SURVEY (CLHLS)

Objective: To determine the target blood pressure in old people (80+ years) with frailty. Design and method: In this community based, longitudinal prospective study, we enrolled 3,134 oldest old people with frailty. The exposure-response associations between blood pressure and all-cause mortality, cardiovascular disease (CVD) mortality, and non-CVD mortality were assessed by the penalized cubic splines fitted in Cox models. Results: During 5 years follow-up, 2,532 deaths were documented. An approximate L-shaped association between systolic blood pressure (SBP) and 5-year all-cause mortality was identified. Compared with 140 mmHg (inflection point), the risk of all-cause mortality significantly increased for SBP below 127 mmHg, which varied from HR of 1.050 (95% CI: 1.003-1.100) to 1.576 (95% CI: 1.128-2.203). After 140 mmHg, mortality risk gradually fell with increasing SBP, although not reaching statistical significance. Diastolic blood pressure (DBP) suggested a significant U-shaped association with 5-year all-cause mortality with 90 mmHg conferred the lowest risk. Before that, the risk of all-cause mortality rose with decreasing DBP, which varied from HR of 1.041 (95% CI: 1.001-1.082) to 1.304 (95% CI: 1.005-1.692). After 90 mmHg, although the observed differences were not statistically significant, mortality risk tended to rise with increasing DBP. Among the 2,037 participants with a confirmed cause of death, 346 died from CVDs and 1,691 died from non-CVDs. In comparison with 120 mmHg, SBP above 134 mm Hg exhibited a significantly elevated CVD mortality risk; when SBP below 121 mmHg, significantly increased non-CVD mortality risk could be found in comparison with SBP at 140 mmHg. As for DBP, it could not predict CVD mortality risk; there was an approximate U-shaped association between DBP and non-CVD mortality that DBP below 69 mmHg was associated with a higher risk with 85 mmHg as the reference. Stratified and sensitivity analyses showed robustness of main findings. Conclusions: In the oldest old people with frailty, in addition to all-cause mortality, blood pressure management should balance CVDs risk and non-CVD risk. Maintaining blood pressure at 120-140/80-100 mmHg can reduce all-cause mortality risk and meanwhile may prevent the adverse events due to excessively higher or lower blood pressure.

Neck circumference as an additional predictor of cardiovascular disease mortality: A multi-center prospective population-based study in northeastern China

Background and aimsThis study aimed to assess the potential of neck circumference (NC) and neck-to-height ratio (NHR) as predictors of future cardiovascular disease (CVD) mortality in a general population from Northeastern China. MethodsA multi-center prospective study was conducted in Northeastern China, involving 18, 796 participants. The associations between NC or NHR and the incidence of overall CVD mortality, stroke mortality, and coronary heart disease (CHD) mortality were examined using multivariate Cox regression models. Hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) were calculated. Reclassification analyses were conducted to determine the incremental predictive value of NC or NHR. ResultsNC was significantly associated with the risk of CVD mortality, independent of other anthropometric measurements for obesity. Individuals in the highest quartile of NC had a 1.83-fold (95% CI 1.29 to 2.61) and a 2.40-fold (95% CI 1.45 to 4.00) higher risk of overall CVD mortality and CHD mortality, respectively. Larger NC was significantly related to a heightened risk of ischemic stroke mortality, although no such association was observed with hemorrhagic stroke mortality. Furthermore, the risk of overall CVD mortality, stroke mortality, and CHD mortality increased by approximately 1.21 to 1.25 times per 1-SD change in NC. Similar findings were observed for NHR. The percentages of correct classification of overall CVD mortality improved by 12.1% and 16.3% after the addition of NC or NHR into established models, respectively. ConclusionsNC and NHR might be promising predictors of CVD mortality, with higher values indicating greater risk.

O008 Refining the Hypoxic Burden Algorithm by Investigating different Methods for Calculating the SpO2 Baseline

Abstract Introduction Intermittent hypoxia is a key mechanism linking Obstructive Sleep Apnoea (OSA) to cardiovascular disease (CVD). Oximetry analysis could enhance understanding of which OSA phenotypes are associated with CVD risk. The hypoxic burden (HB) is a measure calculated from the oximetry signal that shows promise for predicting CVD mortality, but its calculation is complex. With a view to simplifying its calculation, we investigated three different baseline calculation methods and its impact on predicting CVD mortality for the HB algorithm. Methods Data from Sleep Heart Health Study (SHHS) with CVD mortality outcome and complete covariate information was used. We implemented the HB method of Azarbarzin et al 2018 ERJ. The three baseline methods included an event-based baseline (same as Azarbarzin et al 2018 ERJ), a record-based baseline, and a fixed baseline. The performance of each parameter in predicting CVD mortality was assessed using an adjusted Cox proportional hazard ratio (HR) analysis. Results The best performing method was the record-based baseline method which returned a fully adjusted model hazard ratio of 1.83 (95% CI: 1.03-3.27, p<0.05). The results for the event-based and record-based baseline methods were 1.60 (95% CI: 0.86-3.00, p=0.14) and 1.73 (95% CI: 0.93-3.22, p=0.08) respectively. Discussion HB with the record-based baseline was easier to calculate than the original event-based baseline method by Azarbarzin at al. and resulted in improved CVD mortality prediction performance. We believe that this method provides a step towards providing a novel parameter with easy calculation providing early risk stratification in cardiovascular patients.

PB1202 Fibrinogen Concentration and Plasma Clot Properties as Predictors of Cardiovascular Disease Mortality in Black South Africans

PB1202 Fibrinogen Concentration and Plasma Clot Properties as Predictors of Cardiovascular Disease Mortality in Black South Africans

Associations of Recreational and Nonrecreational Physical Activity and Body Weight Change on Cardiovascular Disease Mortality During the Obesogenic Transition in the United States: National Health and Nutrition Examination Survey Follow-up Study.

To investigate cardiovascular disease mortality associated with longitudinal changes in body weight, and recreational and nonrecreational physical activity during the obesogenic transition in the United States since the 1970s. Data were analyzed from 4921 individuals aged 25-74years who participated in the National Health and Nutrition Examination Survey between 1971 and 1979 and follow-up studies to 1992. Mortality was confirmed by searching the National Death Index or proxy interview; clinical data were collected in person. Changes in self-reported recreational and nonrecreational physical activity categories over time were coded as stable, increase, or decrease. Competing risks regression was used to determine hazard ratios adjusted for covariates. A logit model in a generalization method was used to explore mediation effects of change in body weight. Compared with the "moderate-vigorous stable" group (reference), individuals who remained inactive ("inactive stable") or reduced their participation in physical activity ("active to inactive") experienced the highest mortality, with a 50% to 176% and 22% to 222% relative increased hazard ratios for nonrecreational and recreational physical activity, respectively, across all models adjusted for covariates. This corresponded to significant loss of life (up to 3y; all P < .05). Individuals who became active ("inactive to active") were not at increased risk. We found weak (but nonstatistically significant) evidence of mediation effects of body weight change on mortality. Longitudinal changes in moderate-vigorous recreational and nonrecreational physical activity were important predictors of cardiovascular disease mortality during the obesogenic transition period in the United States and were mostly unexplained by changes in body weight.

Predicting Cardiovascular Disease Mortality: Leveraging Machine Learning for Comprehensive Assessment of Health and Nutrition Variables.

Cardiovascular disease (CVD) is one of the primary causes of death around the world. This study aimed to identify risk factors associated with CVD mortality using data from the National Health and Nutrition Examination Survey (NHANES). We created three models focusing on dietary data, non-diet-related health data, and a combination of both. Machine learning (ML) models, particularly the random forest algorithm, demonstrated robust consistency across health, nutrition, and mixed categories in predicting death from CVD. Shapley additive explanation (SHAP) values showed age, systolic blood pressure, and several other health factors as crucial variables, while fiber, calcium, and vitamin E, among others, were significant nutritional variables. Our research emphasizes the importance of comprehensive health evaluation and dietary intake in predicting CVD mortality. The inclusion of nutrition variables improved the performance of our models, underscoring the utility of dietary intake in ML-based data analysis. Further investigation using large datasets with recurring dietary recalls is necessary to enhance the effectiveness and interpretability of such models.

Fatty Liver Index and mortality after myocardial infarction: A prospective analysis in the Alpha Omega Cohort.

Accumulating evidence shows that NAFLD might play a role in the etiology and progression of CVD, but little is known on the association of NAFLD and CVD mortality in patients with a history of a myocardial infarction (MI). Therefore, we studied the relationship of Fatty Liver Index (FLI), as indicator for non-alcoholic fatty liver disease (NAFLD), with 12-year risk of cardiovascular disease (CVD) and all-cause mortality in post-MI patients. We included 4165 Dutch patients from the Alpha Omega Cohort aged 60-80 years who had an MI ≤10 years prior to study enrolment. NAFLD was defined as FLI ≥60. Patients were followed for cause-specific mortality from enrolment (2002-2006) through December 2018. Hazard ratios for CVD and all-cause mortality were obtained by multivariable Cox regression using FLI <30 (indicating absence of NAFLD) as the reference. Baseline FLI as a continuous measure was studied with mortality using restricted cubic splines analyses. The median (IQR) FLI was 68 (48-84). Sixty percent of the patients had FLI ≥60, who were more likely to be male and more often had diabetes, high blood pressure, and high serum cholesterol levels. During 12 years of follow-up, 2042 deaths occurred of which 846 from CVD. Patients with NAFLD were at increased risk of CVD mortality (HR: 1.55 [1.19, 2.03]) and all-cause mortality (HR: 1.21 [1.03; 1.41]) compared to patients without NAFLD. Results remained consistent after excluding patients with obesity and diabetes. To conclude, the adverse association of FLI with CVD mortality was stronger in female than in male patients with conventional cut-off points. FLI ≥60, indicating NAFLD, was a predictor for CVD and all-cause mortality in post-MI patients, independent of other cardiometabolic risk factors. However, cut-off points might differ between male and female patients for predicting CVD mortality.

Total and Regional Fat/Muscle Mass Ratio and Risks of Incident Cardiovascular Disease and Mortality.

Background To evaluate the sex-specific associations of total and regional fat/muscle mass ratio (FMR) with cardiovascular disease (CVD) incidence and mortality, and to explore the underlying mechanisms driven by cardiometabolites and inflammatory cells. We compared the predictive value of FMRs to body mass index. Methods and Results This population-based, prospective cohort study included 468 885 UK Biobank participants free of CVD at baseline. Fat mass and muscle mass were estimated using a bioelectrical impedance assessment device. FMR was calculated as fat mass divided by muscle mass in corresponding body parts (total body, trunk, arm, and leg). Multivariable Cox proportional hazards models and mediation analyses were used. During 12.5 years of follow-up, we documented 49 936 CVD cases and 4158 CVD deaths. Higher total FMR was associated with an increased risk of incident CVD (hazard ratios [HRs] were 1.63 and 1.83 for men and women, respectively), ischemic heart disease (men: HR, 1.61; women: HR, 1.81), myocardial infarction (men: HR, 1.72; women: HR, 1.49), and congestive heart failure (men: HR, 2.25; women: HR, 2.57). The positive associations of FMRs with mortality from total CVD or its subtypes were significant mainly in trunk and arm for male patients (P for trend <0.05). We also identified 8 cardiometabolites and 5 inflammatory cells that partially mediated FMR-CVD associations. FMRs were modestly better at discriminating cardiovascular mortality risk. Conclusions Higher total and regional FMRs were associated with an increased risk of CVD and mortality, partly mediated through cardiometabolites and inflammatory cells. Early monitoring of FMR should be considered to alleviate CVD risk. FMRs were superior to body mass index in predicting CVD mortality.

Assessment of Left Ventricular Myocardial Fibrosis in Adult Patients With Ebstein Anomaly: A Retrospective Cohort Study Based on Cardiac Magnetic Resonance and Histopathological Samples.

The association between Ebstein anomaly and myocardial fibrosis, particularly in the left ventricle, has been controversial. We aimed to assess the prevalence of replacement fibrosis with a focus on the left ventricle (LV) using cardiac magnetic resonance (CMR), make a histopathological association between LV fibrosis and CMR findings, and explore whether LV fibrosis is an independent risk factor for cardiovascular disease mortality using a derived risk score. We performed a 12-year (2009-2021) retrospective cohort of adult patients with Ebstein anomaly who underwent CMR. The CMR evaluation included a comprehensive assessment of myocardial fibrosis by late gadolinium enhancement (LGE). Four postmortem samples were obtained from our cohort and stained using Masson trichrome to characterize LV fibrosis. We used Cox-regression analysis to identify and derive a prediction score that associated LV fibrosis with cardiovascular disease mortality. We included 57 adults with Ebstein anomaly (52% men; median age, 29.52 [interquartile range, 21.24-39.17] years), of whom 12 died during follow-up. LGE prevalence by CMR was observed in 52.6% in any chamber; LV-LGE in 29.8%. Histopathological findings revealed a mid-wall pattern with predominantly interstitial fibrosis and minimal replacement fibrosis. LV-LGE was associated with increased risk of cardiovascular disease mortality (hazard ratio, 6.02 [95% CI, 1.22-19.91]) attributable to lateral and mid-wall LV segment involvement. Our mortality score achieved an overall good prediction capacity (R2, 0.435; C statistic, 0.93; Dxy, 0.86). There is a high prevalence of LV fibrosis replacement in adults with Ebstein anomaly, characterized by specific CMR and histological patterns. Furthermore, LV-LGE fibrosis is an independent predictor of cardiovascular disease mortality, which could be integrated into risk assessment in clinical management.

Abstract P659: Cluster Analysis of County-Level Cardiovascular Disease Mortality in the United States

Introduction: In the United States, cardiovascular disease (CVD) mortality has been declining since 1980s. However, the decline in CVD mortality is not uniform across regions and may show different trajectories that are driven by place-based social determinants of health (SDOH) such as physical and built environment, social-cultural environment, and health care system. We conducted a cluster analysis of county-level CVD mortality and SDOH indicators from 2009 to 2018. Hypothesis: We test the hypothesis that CVD mortality in US counties show different trajectories that can be grouped by clusters, and within each cluster, there are different SDOH variables that predict CVD mortality. Methods: We linked the Centers for Disease Control and Prevention's CVD mortality data with the Agency for Healthcare Research and Quality's public database on SDOH using county identifiers. CVD mortality rate was calculated as the number of deaths per 100,000 people in each county. There were 179 SDOH variables included in the model, classified into five different domains: the biological, behavioral, built and physical environment, health care system, and sociocultural environment domain. We employed a linear mixed-effects model fitted with a doubly penalized likelihood to induce sparsity for parameter estimation and effect selection. Results: We identified three clusters among a total of 3,136 counties. Overall, 1,182 counties were identified as cluster 1 that showed a consistent decline of CVD mortality over the past decade. The most important driving factor of CVD mortality in cluster 1 was population distribution - the percentage of population aged 15-17 (coefficient=7.032). Secondly, 1,116 counties were identified as cluster 2 that showed a decline between 2009 and 2012, and then a steady increase in CVD mortality after 2012. Within cluster 2, the number of mild drought months was the most predictive factor of CVD mortality (coefficient= -1.065), and the percentage of adults reporting no leisure-time physical activity was the second important predictor (coefficient= 0.646). Finally, 838 counties were identified as cluster 3 that showed a flattening trend in CVD mortality. Within cluster 3, the total number of obstetrics and gynecology, generalist, and primary care hospital residents plays the most important role (coefficient = -25.537). Each cluster has unique pattern and distinctive associations between certain SDOH variables and CVD mortality. Conclusions: In conclusion, we identified three intrinsic clusters that showed distinguishing trajectories of CVD mortality during the past decade. The SDOH indicators most predictive of CVD mortality were different within each cluster. This study suggests that place based SDOH drive substantial differences in CVD outcomes across regions.

Changes in Socioeconomic Status as Predictors of Cardiovascular Disease Incidence and Mortality: A 10-Year Follow-Up of a Polish-Population-Based HAPIEE Cohort.

Although the inverse association between socioeconomic status (SES) and cardiovascular disease (CVD) is well established, research on the effect of changes in the SES throughout life on CVD risk in populations with different social backgrounds remains scarce. This study aimed to assess the relationship between childhood SES, adulthood SES, and changes in SES over time, and CVD incidence and mortality in a Polish urban population. In addition, the predictive performance of the SES index was compared with education alone. A cohort study with a 10-year follow-up was conducted, in which a random sample of 10,728 residents in Kraków aged 45-69 years were examined. The SES was assessed at baseline using data on education, parents' education, housing standard at the age of 10 years, professional activity, household amenities, and difficulties in paying bills and buying food. SES categories (low, middle, and high) were extracted using cluster analyses. Information on new CVD cases was obtained from questionnaires in subsequent phases of the study and confirmed by reviewing clinical records. Data on deaths and causes were obtained from the residents' registry, Central Statistical Office, and the participants' families. The effect of the SES index on the risk of CVD was assessed using Cox proportional hazard models. In male and female participants, the CVD incidence and mortality were observed to be 27,703 and 32,956 person-years (384 and 175 new CVD cases) and 36,219 and 40,048 person-years (159 and 92 CVD deaths), respectively. Childhood SES was not associated with CVD incidence and mortality. A protective effect of high adulthood SES against CVD mortality was observed in men and women (HR = 0.59, 95% CI = 0.31-0.97; HR = 0.33, 95% CI = 0.14-0.75, respectively). In women, downward social mobility was related to 2.24 and 3.75 times higher CVD incidence and mortality, respectively. In men, a protective effect against mortality was observed in upward mobility (HR = 0.50, 95% CI = 0.29-0.84). Model discrimination was similar for the SES index and education alone for the association with CVD incidence. In women, the SES index was a slightly better predictor of CVD mortality than education alone (C-index = 0.759, SE = 0.0282 vs. C-index = 0.783, SE = 0.0272; p = 0.041). In conclusion, high adulthood SES, but not childhood SES, may be considered to be a protective factor against CVD in urban populations in high-CVD-risk regions. No effects of critical periods in early life were observed on CVD risk. In later life, social mobility was found to affect CVD mortality in both men and women. In men, a protective effect of upward mobility was confirmed, whereas in women, an increased CVD risk was related to downward mobility. It can be concluded that CVD prevention may be beneficial if socioeconomic potentials are strengthened in later life.

Cardiovascular mortality risk prediction using objectively measured physical activity phenotypes in NHANES 2003–2006

Increased physical activity (PA) has been associated with a decreased risk of cardiovascular disease (CVD) and mortality. However, most previous studies use self-reported PA instead of objectively measured PA assessed by wearable accelerometers. To the best of our knowledge, there have not been studies that quantified the univariate and multivariate ability of objectively measured PA summaries to predict the risk of CVD mortality. We investigate the ability of objectively measured PA summary variables to predict CVD mortality: as individual predictors, as part of the best multivariate model incorporating traditional predictors, and as additions to the best multivariate model using only traditional CVD predictors. Data were collected in the National Health and Nutrition Examination Survey 2003–2006 waves for US participants aged 50–85. The predictive ability was measured using Concordance, sometimes referred to as the C-statistic. Specifically, we calculated 10-fold cross-validated concordance (CVC) in survey-weighted Cox proportional hazard models. The best univariate predictor of CVD mortality was total activity count (outperformed age). In multivariate models, two of the eight predictors identified using the improvement in CVC threshold of 0.001 were PA measures (CVC = 0.844). The best model without physical activity (7 predictors) had CVC of 0.830. The addition of PA measures to the best traditional model was significantly better at predicting CVD mortality (P < 0.001). Accelerometer-derived PA measures have excellent cardiovascular mortality prediction performance. Wearable accelerometers have a potential for assessment of individuals' CVD mortality risks.

Even chained acylcarnitines predict long-term cardiovascular prognosis in patients with chest pain and non-obstructive coronary artery disease

BackgroundAcylcarnitines are essential for mitochondrial fatty acid oxidation. Earlier studies suggest that impaired energy metabolism may be implicated in the pathogenesis of microvascular angina. We explored metabolites from the carnitine pathway as predictors of cardiovascular disease (CVD) - and all-cause mortality among patients with non-obstructive coronary artery disease (NOCAD). MethodsA total of 1046 patients with suspected stable coronary syndrome underwent coronary angiography during 2000–2004, with findings of NOCAD. Serum levels of 8 selected carnitine metabolites were analyzed through liquid chromatography tandem mass spectrometry. Associations with CVD- and all-cause mortality were assessed by multivariable Cox regression models. ResultsMedian age at inclusion was 57 years. 51.5% were men. During median (25th- 75th percentiles), 14.1 (13.2–15.4) years of follow-up, 5.7% of the participants died from CVD and the incidence of all-cause mortality was 17.3%. Serum acetyl, octanoyl- and palmitoylcarnitine predicted CVD mortality with multivariable HR and 95% CI (per SD increment log transformed) of 1.36 (1.01–1.83), 1.49 (1.15–1.93) and 2.07 (1.49–2.85), p ≤ 0.04, respectively. Higher serum acetyl- and palmitoylcarnitines were also associated with increased risk of all-cause mortality (HR (95% CI): 1.27 (1.01–1.50), and 1.51 (1.26–1.81), p ≤ 0.007. Baseline levels of the precursors trimethyllysine and ƴ-butyrobetaine, carnitine or the odd chained propionylcarnitine and (iso)valerylcarnitine were not associated with adverse outcomes. ConclusionElevated serum even-chained acylcarnitines predicted adverse long-term prognosis in NOCAD. The strongest risk estimates were observed for palmitoylcarnitine, which predicted both CVD- and all-cause mortality after extensive multivariable adjustments. Underlying pathomechanisms should be further elucidated.

Late non-fasting plasma glucose predicts cardiovascular mortality independent of hemoglobin A1c

It is unknown whether non-fasting plasma glucose (PG) is associated with cardiovascular disease (CVD) mortality. This study aimed to investigate this association in US adults. This study included adults from the National Health and Nutrition Examination Surveys from 1988 to 2014. Mortality outcomes were ascertained by linkage to the National Death Index records. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of PG for CVD mortality. Among 34,907 participants, 1956, 5564, and 27,387 had PG from participants in early non-fasting, late non-fasting, and fasting states, respectively (defined as a period since last calorie intake of 0–2.9, 3.0–7.9, or ≥ 8.0 h, respectively). This cohort was followed up for 455,177 person-years (mean follow-up, 13.0 years), with 2,387 CVD deaths being recorded. After adjustment for all confounders including hemoglobin A1c (HbA1c), only late non-fasting PG (continuous, natural log-transformed) was positively associated with CVD mortality risks (hazard ratio, 1.73; 95% confidence interval 1.12–2.67). Higher late non-fasting PG (dichotomous, at a cut-off of 105, 110, or 115 mg/dL) was associated with higher CVD mortality risks. In addition, at the cut-off of 115 mg/dL, higher late non-fasting PG was associated with higher CVD mortality risks in those with either a normal (< 5.7%) or prediabetic HbA1c level (from 5.7 to 6.4%). In conclusion, late non-fasting PG predicts CVD mortality independent of HbA1c. Late non-fasting PG with a cut-off of 115 mg/dL may be used to identify those at high CVD risk.

MO681: Association of Framingham Risk Score with Mortality in Kidney Failure Patients from China and Sweden

Abstract BACKGROUND AND AIMS The Framingham risk score (FRS) was developed to estimate an individual`s risk of coronary heart disease over the next 10 years in the general population by using traditional cardiovascular disease (CVD) risk factors age, sex, systolic blood pressure, treatment of hypertension, total cholesterol, high-density lipoprotein cholesterol and smoking status. However, the utility of FRS in predicting CVD mortality in kidney failure patients is not clear. We examined the association between FRS and all-cause and CVD mortality in two cohorts of kidney failure patients from China and Sweden, respectively. METHOD In 1276 Chinese incident peritoneal dialysis [median age 50 years, 56% males, BMI 21 (19–23); incident peritoneal dialysis] and 559 Swedish incident or prevalent dialysis patients [median age 58 years, 62% males, BMI 24 (22–28)], FRS and baseline biochemical and metabolic biomarkers were analysed in relation to mortality during follow-up period of up to 5 years. All-cause and CVD mortality risk of were analysed with competing-risk regression models with transplantation as competing risk adjusting for BMI, serum albumin, hemoglobulin and calendar year. RESULTS Chinese patients were significantly younger (P &amp;lt; 0.01) and had lower BMI (P &amp;lt; 0.01) and FRS (P &amp;lt; 0.01) than Swedish patients but their sex distribution was similar. ‘In the Chinese patients,’ during median 3.6 years of follow-up, all-cause mortality rate was 16%, and 91 (46%) of the 199 deaths were caused by CVD. Both middle and high tertiles of FRS were associated with higher all-cause (Fig. 1A) and CVD mortality (Fig 1B) risk after adjusting for confounders. ‘In the Swedish patients,’ after median 2.1 years of follow-up, all-cause mortality rate was 36%, and 89 (44%) of the 204 deaths were caused by CVD. Both middle and high tertiles were associated with higher all-cause (Fig. 2A) and CVD mortality (Fig. 2B) risk after adjusting for confounders. CONCLUSION Higher FRS (both middle and high tertiles of FRS) was independently associated with significantly higher all-cause and CVD mortality risk in Chinese as well as in Swedish patients with kidney failure. These results underline the importance of traditional CVD risk factors in kidney failure patients and suggest that FRS may be a useful risk-assessment tool for predicting clinical outcomes in these patients.

Association of the serum transaminase with mortality among the US elderly population.

Considering the inconsistent findings of research into the associations between serum levels of liver enzymes (alanine aminotransferase [ALT], aspartate aminotransferase [AST], and gamma-glutamyltransferase [GGT]) and mortality among elderly people, we aimed to investigate the associations of ALT, AST, GGT, and De-Ritis ratio (DRR, defined as AST/ALT) and all-cause or cause-specific mortality among the US elderly people using National Health and Nutrition Examination Surveys data. We included 6415 elderly participants (≥65years). Exclusion criteria included positive test for hepatitis B virus, hepatitis C virus, and human immunodeficiency virus infection at baseline. Multivariable-adjusted Cox regression models calculating hazard ratios (HR) and 95% confidence intervals were developed for each of the liver enzyme measures. All-cause cumulative mortality was 33.8%, of which 23.8% were cardiovascular disease (CVD) deaths, 15.6% were cancer deaths, and 60.6% were other cause deaths. Adjusted Cox models found increased all-cause mortality risk for low ALT (HR: 1.70), low AST (HR: 1.13), high GGT (HR: 1.25), and high DRR (HR: 1.68). Low ALT and high DRR predicted CVD mortality. Low ALT (HR: 1.91), low AST (HR: 1.16), high GGT (HR: 1.40), and high DRR (HR: 1.76) predicted other cause mortality. Low ALT and high DRR were associated with increased CVD and cancer mortality. All serum liver enzyme measures were associated with all-cause mortality and other cause mortality in the US elderly population. Further studies may validate these findings in other elderly populations.

The Relationship Between Racial Prejudice and Cardiovascular Disease Mortality Risk at the State and County Level.

Robust evidence shows that perceived discrimination among stigmatized groups is associated with negative health outcomes. However, little work has examined whether holding prejudiced attitudes toward others is associated with health risks for prejudiced individuals. The study is a test of the hypothesis that holding prejudicial attitudes has negative health implications for both the holders and targets of prejudicial attitudes. The project connected data (2003-2015) at the state and county levels on average explicit and implicit prejudice held by White, Black, and Native American respondents from Project Implicit with data on cardiovascular disease (CVD) mortality for White, Black, and Native American individuals from the CDC Wonder database. Separate analyses regressed implicit and explicit prejudice on CVD mortality risk for White, Black, and Native American individuals, respectively. At the state level, among White individuals, explicit prejudice toward Blacks (β = .431, p =.037) and implicit prejudice toward Native Americans (β = .283, p = .045) were positively associated with greater CVD mortality for Whites. At the county level, White individuals' implicit prejudice toward Blacks (β =.081, p = .015) and Black individuals' implicit prejudice toward Whites (β = -.066, p = .018) were associated with greater CVD mortality for Whites. Also, at the county-level, among Black individuals, higher implicit (β = -.133, p < .001) and explicit (β = -.176, p < .001) prejudice toward Whites predicted CVD mortality for Blacks. Moreover, explicit prejudice held by White individuals was positively associated with Blacks' county-level CVD deaths (β = .074, p = .036). This evidence suggests that across racial groups, holding racial prejudice is associated with CVD mortality risk for both the prejudiced and the stigmatized groups. Future research should verify the reliability of this potential public health effect with additional work explicating moderators and mediators to inform surveillance and interventions.