Cholesterol Lowering in Older Adults: Should We Wait for Further Evidence?

PURPOSE OF REVIEW: Current guidelines for primary and secondary prevention of cardiovascular events in adults up to age 75 years are well-established. However, recommendations for lipid-lowering therapies (LLT), particularly for primary prevention, are inconclusive after age 75. In this review, we focus on adults ≥ 75 years to assess low-density lipoprotein-cholesterol (LDL-C) as a marker for predicting atherosclerotic cardiovascular disease (ASCVD) risk, review risk assessment tools, highlight guidelines for LLT, and discuss benefits, risks, and deprescribing strategies. RECENT FINDINGS: The relationship between LDL-C and all-cause mortality and cardiovascular outcomes in older adults is complex and confounded. Current ASCVD risk estimators heavily depend on age and lack geriatric-specific variables. Emerging tools may reclassify individuals based on biologic rather than chronologic age, with coronary artery calcium scores gaining popularity. After initiating LLT for primary or secondary prevention, target LDL-C levels for older adults are lacking, and non-statin therapy thresholds remain unknown, relying on evidence from younger populations. Shared decision-making is crucial, considering therapy's time to benefit, life expectancy, adverse events, and geriatric syndromes. Deprescribing is recommended in end-of-life care but remains unclear in fit or frail older adults. After an ASCVD event, LLT is appropriate for most older adults, and deprescribing can be considered for those approaching the last months of life. Ongoing trials will guide statin prescription and deprescribing among older adults free of ASCVD. In the interim, for adults ≥ 75 years without a limited life expectancy who are free of ASCVD, an LLT approach that includes both lifestyle and medications, specifically statins, may be considered after shared decision-making.

Ambient Air Pollution Exposure and Adverse Outcomes Among Medicare Beneficiaries With Heart Failure.

BACKGROUND: Exposure to fine particulate matter (<2.5 um, particulate matter with an aerodynamic diameter <2.5 microns [PM2.5]) has been implicated in atherogenesis. Limited data in animal studies suggest that PM2.5 exposure leads to myocardial fibrosis and increased incidence of heart failure (HF). Whether PM2.5 is associated with adverse outcomes in patients with preexisting HF has not been widely studied. METHODS AND RESULTS: In this retrospective cohort study, Medicare patients hospitalized with first HF between 2013 and 2020 were identified from the Medicare Provider Analysis and Review Part A 100% files. Patients were linked with integrated estimates of ambient PM2.5 obtained at 1×1 km using the zip code of participants' residence. The study outcomes were all-cause death, HF, and all-cause readmissions burden. A total of 2 599 525 patients were included in this study, with 6 321 731 person-years of follow-up. Mean PM2.5 was 7.3±1.7 µg/m3. Each interquartile range of PM2.5 was associated with 0.9% increased hazard of all-cause death, 4.5% increased hazard of first HF readmission, 3.1% increased risk of HF hospitalization burden, and 5.2% increase in all-cause readmission burden, after adjusting for 11 sociodemographic and medical factors. Subgroup analyses showed that the effects were more pronounced at levels <7 µg/m3 and in patients aged <75 years, Asians, and those residing in rural areas. CONCLUSIONS: Ambient air pollution is associated with higher risk of adverse events in Medicare beneficiaries with established HF. These associations persist below the National Air Quality Standards (12 µg/m3), supporting that no threshold effect exists for health effects of air pollution exposure.

Does Timing of Coronary Artery Bypass Grafting after ST-Elevation Myocardial Infarction Impact Early- and Long-Term Outcomes?

BACKGROUND: The optimal timing of surgical revascularization after ST-elevation myocardial infarction (STEMI) is controversial, with some suggesting higher mortality rates in patients undergoing early surgery. The aim of the study is to determine the effect of the timing of surgical revascularization on 30-day mortality and long-term outcomes in these patients. METHODS: Retrospective single-center analysis of patients with STEMI undergoing coronary artery bypass grafting (CABG) between January 2008 and December 2019 at our institution. The cohort was split into three groups based on time from symptom onset until surgical revascularization (Group 1: <12 hours, Group 2: 12-72 hours, Group 3: >72 hours). Statistical analyses were performed with and without patients in cardiogenic shock. Primary outcomes were 30-day mortality and 10-year survival. RESULTS: During the study period, 437 consecutive patients underwent surgical revascularization in the setting of STEMI. The mean age was 67.0 years, 96 (22.0%) patients were female, and 281 (64.3%) patients underwent off-pump CABG. The overall 30-day mortality including patients with cardiogenic shock was 12.8%. The 30-day mortality was 16.1, 13.9, and 9.3% in Groups 1, 2, and 3 (p = 0.31), whereas 10-year survival was 48.5, 57.3, and 54.9% (log-rank: p = 0.40). After exclusion of patients in cardiogenic shock, there was no difference between the three groups in 30-day and 10-year mortality. Timing of surgery had no influence on early- and long-term survival. CONCLUSION: In patients with STEMI, early surgical revascularization achieved similar early- and long-term survival rates compared with a delayed surgical revascularization strategy. Hence, when indicated, an early CABG strategy has no disadvantages in comparison to a delayed strategy.

Air Pollution and Adverse Cardiovascular Events After Coronary Artery Bypass Grafting: A 10-Year Nationwide Study.

Background: Increased particulate matter <2.5 µm (PM2.5) air pollution is associated with adverse cardiovascular outcomes. However, its impact on patients with prior coronary artery bypass grafting (CABG) is unknown. Objectives: The purpose of this study was to evaluate the association between major adverse cardiovascular events (MACE) (defined as myocardial infarction, stroke, or cardiovascular death) and air pollution after CABG. Methods: We linked 26,403 U.S. veterans who underwent CABG (2010-2019) nationally with average annual ambient PM2.5 estimates using residential address. Over a 5-year median follow-up period, we identified MACE and fit a multivariable Cox proportional hazard model to determine the risk of MACE as per PM2.5 exposure. We also estimated the absolute potential reduction in PM2.5 attributable MACE simulating a hypothetical PM2.5 lowered to the revised World Health Organization standard of 5 µg/m3. Results: The observed median PM2.5 exposure was 7.9 µg/m3 (IQR: 7.0-8.9 µg/m3; 95% of patients were exposed to PM2.5 above 5 µg/m3). Increased PM2.5 exposure was associated with a higher 10-year MACE rate (first tertile 38% vs third tertile 45%; P < 0.001). Adjusting for demographic, racial, and clinical characteristics, a 10 µg/m3 increase in PM2.5 resulted in 27% relative risk for MACE (HR: 1.27, 95% CI: 1.10-1.46; P < 0.001). Currently, 10% of total MACE is attributable to PM2.5 exposure. Reducing maximum PM2.5 to 5 µg/m3 could result in a 7% absolute reduction in 10-year MACE rates. Conclusions: In this large nationwide CABG cohort, ambient PM2.5 air pollution was strongly associated with adverse 10-year cardiovascular outcomes. Reducing levels to World Health Organization-recommended standards would result in a substantial risk reduction at the population level.

Historical neighborhood redlining and bystander CPR disparities in out-of-hospital cardiac arrest.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is associated with low survival rates. Bystander cardiopulmonary resuscitation (CPR) is essential for improving outcomes, but its utilization remains limited, particularly among racial and ethnic minorities. Historical redlining, a practice that classified neighborhoods for mortgage risk in 1930s, may have lasting implications for social and health outcomes. This study sought to investigate the influence of redlining on the provision of bystander CPR during witnessed OHCA. METHODS: We conducted an analysis using data from the comprehensive Cardiac Arrest Registry to Enhance Survival (CARES), encompassing 736,066 non-traumatic OHCA cases across the United States. The Home Owners' Loan Corporation (HOLC) map shapefiles were utilized to categorize census tracts of arrests into four grades (A signifying "best", B "still desirable", C "declining", and D "hazardous"). Multivariable hierarchical logistic regression models were employed to predict the likelihood of CPR provision, adjusting for various factors including age, sex, race/ethnicity, arrest location, calendar year, and state of occurrence. Additionally, we accounted for the percentage of Black residents and residents below poverty levels at the census tract level. RESULTS: Among the 43,186 witnessed cases of OHCA in graded HOLC census tracts, 37.2% received bystander CPR. The rates of bystander CPR exhibited a gradual decline across HOLC grades, ranging from 41.8% in HOLC grade A to 35.8% in HOLC grade D. In fully adjusted model, we observed significantly lower odds of receiving bystander CPR in HOLC grades C (OR 0.89, 95% CI 0.81-0.98, p = 0.016) and D (OR 0.86, 95% CI 0.78-0.95, p = 0.002) compared to HOLC grade A. CONCLUSION: Redlining, a historical segregation practice, is associated with reduced contemporary rates of bystander CPR during OHCA. Targeted CPR training in redlined neighborhoods may be imperative to enhance survival outcomes.

Geographic proximity to cardiovascular clinical trial sites: A National analysis in the United States.

INTRODUCTION: Suboptimal geographical access to cardiovascular clinical trial sites (CV-CTS) may be a cause of inadequate demographic representation in contemporary trials. Thus, we investigate access to CV-CTS in the US. METHODS: We obtained the location of CV-CTS from Clinicaltrials.gov. We calculated the distance in kilometers from each ZIP code to the nearest CV-CTS, stratifying our results based on urban/rural setting, sex and race. RESULTS: We identified a total of 10,506 studies in 4,630 US ZIP codes (10.5 %), of those only 237 (5 %) were rural. The overall median CV-CTS distance was 5.8 km (IQR: 2.7, 15.8). For urban residents, this distance was 4.5 km (IQR: 2.3, 9.2), while for rural residents, it was 24.2 km (IQR: 13.8, 42.2). RESULTS: We revealed important disparities involving geographical proximity to cardiovascular clinical trial sites. Increasing the representation of these populations in clinical trials is paramount to improving the applicability of their findings to real-world settings.

Quantifying lead-attributable cardiovascular disease burden in the United States.

Lead exposure has been linked to a myriad of cardiovascular diseases. Utilizing data from the 2019 Global Burden of Disease Study, we quantified age-standardized lead exposure-related mortality and disability-adjusted life years (DALYs) in the United States between 1990 and 2019. Our analysis revealed a substantial reduction in age-standardized cardiovascular disease (CVD) mortality attributable to lead exposure by 60 % (from 7.4 to 2.9 per 100,000), along with a concurrent decrease in age-standardized CVD DALYs by 66 % (from 143.2 to 48.7 per 100,000).

County-Level Socio-Environmental Factors Associated With Stroke Mortality in the United States: A Cross-Sectional Study.

We used machine learning methods to explore sociodemographic and environmental determinants of health (SEDH) associated with county-level stroke mortality in the USA. We conducted a cross-sectional analysis of individuals aged ≥15 years who died from all stroke subtypes between 2016 and 2020. We analyzed 54 county-level SEDH possibly associated with age-adjusted stroke mortality rates/100,000 people. Classification and Regression Tree (CART) was used to identify specific county-level clusters associated with stroke mortality. Variable importance was assessed using Random Forest analysis. A total of 501,391 decedents from 2397 counties were included. CART identified 10 clusters, with 77.5% relative increase in stroke mortality rates across the spectrum (28.5 vs 50.7 per 100,000 persons). CART identified 8 SEDH to guide the classification of the county clusters. Including, annual Median Household Income ($), live births with Low Birthweight (%), current adult Smokers (%), adults reporting Severe Housing Problems (%), adequate Access to Exercise (%), adults reporting Physical Inactivity (%), adults with diagnosed Diabetes (%), and adults reporting Excessive Drinking (%). In conclusion, SEDH exposures have a complex relationship with stroke. Machine learning approaches can help deconstruct this relationship and demonstrate associations that allow improved understanding of the socio-environmental drivers of stroke and development of targeted interventions.

Associations of diabesity with all-cause and cardiovascular disease mortality: Findings from the Mexico City Prospective Study.

AIM: To investigate the joint associations of diabetes and obesity with all-cause and cardiovascular disease (CVD) mortality in the Mexico City Prospective Study. MATERIALS AND METHODS: In total, 154 128 participants (67.2% women) were included in this prospective analysis. Diabetes was self-reported, while body mass index was used to calculate obesity. Using diabetes and obesity classifications, six groups were created: (a) normal (no diabetes and normal weight); (b) normal weight and diabetes; (c) overweight but not diabetes (overweight); (d) overweight and diabetes (prediabesity); (e) obesity but not diabetes (obesity); and (f) obesity and diabetes (diabesity). Associations between these categories and outcomes were investigated using Cox proportional hazard models adjusted for confounder factors. RESULTS: During 18.3 years of follow-up, 27 197 (17.6%) participants died (28.5% because of CV causes). In the maximally adjusted model, participants those with the highest risk {hazard ratio (HR): 2.37 [95% confidence interval (CI): 2.24-2.51]}, followed by those with diabesity [HR: 2.04 (95% CI: 1.94-2.15)]. Similar trends of associations were observed for CVD mortality. The highest CV mortality risk was observed in individuals with diabesity [HR: 1.80 (95% CI: 1.63-1.99)], followed by normal weight and diabetic individuals [HR: 1.78 (95% CI: 1.60-1.98)]. CONCLUSION: This large prospective study identified that diabetes was the main driver of all-cause and CVD mortality in all the categories studied, with diabesity being the riskiest. Given the high prevalence of both conditions in Mexico, our results reinforce the importance of initiating prevention strategies from an early age.

Air pollution exposure and cardiometabolic risk.

The Global Burden of Disease assessment estimates that 20% of global type 2 diabetes cases are related to chronic exposure to particulate matter (PM) with a diameter of 2·5 µm or less (PM2·5). With 99% of the global population residing in areas where air pollution levels are above current WHO air quality guidelines, and increasing concern in regard to the common drivers of air pollution and climate change, there is a compelling need to understand the connection between air pollution and cardiometabolic disease, and pathways to address this preventable risk factor. This Review provides an up to date summary of the epidemiological evidence and mechanistic underpinnings linking air pollution with cardiometabolic risk. We also outline approaches to improve awareness, and discuss personal-level, community, governmental, and policy interventions to help mitigate the growing global public health risk of air pollution exposure.

County-level socio-environmental factors and obesity prevalence in the United States.

AIMS: To investigate high-risk sociodemographic and environmental determinants of health (SEDH) potentially associated with adult obesity in counties in the United States using machine-learning techniques. MATERIALS AND METHODS: We performed a cross-sectional analysis of county-level adult obesity prevalence (body mass index ≥30 kg/m2) in the United States using data from the Diabetes Surveillance System 2017. We harvested 49 county-level SEDH factors that were used in a classification and regression trees (CART) model to identify county-level clusters. The CART model was validated using a 'hold-out' set of counties and variable importance was evaluated using Random Forest. RESULTS: Overall, we analysed 2752 counties in the United States, identifying a national median (interquartile range) obesity prevalence of 34.1% (30.2%, 37.7%). The CART method identified 11 clusters with a 60.8% relative increase in prevalence across the spectrum. Additionally, seven key SEDH variables were identified by CART to guide the categorization of clusters, including Physically Inactive (%), Diabetes (%), Severe Housing Problems (%), Food Insecurity (%), Uninsured (%), Population over 65 years (%) and Non-Hispanic Black (%). CONCLUSION: There is significant county-level geographical variation in obesity prevalence in the United States, which can in part be explained by complex SEDH factors. The use of machine-learning techniques to analyse these factors can provide valuable insights into the importance of these upstream determinants of obesity and, therefore, aid in the development of geo-specific strategic interventions and optimize resource allocation to help battle the obesity pandemic.

Impact of Residential Social Deprivation on Prediction of Heart Failure in Patients With Type 2 Diabetes: External Validation and Recalibration of the WATCH-DM Score Using Real World Data.

BACKGROUND: Patients with type 2 diabetes are at risk of heart failure hospitalization. As social determinants of health are rarely included in risk models, we validated and recalibrated the WATCH-DM score in a diverse patient-group using their social deprivation index (SDI). METHODS: We identified US Veterans with type 2 diabetes without heart failure that received outpatient care during 2010 at Veterans Affairs medical centers nationwide, linked them to their SDI using residential ZIP codes and grouped them as SDI <20%, 21% to 40%, 41% to 60%, 61% to 80%, and >80% (higher values represent increased deprivation). Accounting for all-cause mortality, we obtained the incidence for heart failure hospitalization at 5 years follow-up; overall and in each SDI group. We evaluated the WATCH-DM score using the C statistic, the Greenwood Nam D'Agostino test χ2 test and calibration plots and further recalibrated the WATCH-DM score for each SDI group using a statistical correction factor. RESULTS: In 1 065 691 studied patients (mean age 67 years, 25% Black and 6% Hispanic patients), the 5-year incidence of heart failure hospitalization was 5.39%. In SDI group 1 (least deprived) and 5 (most deprived), the 5-year heart failure hospitalization was 3.18% and 11%, respectively. The score C statistic was 0.62; WATCH-DM systematically overestimated heart failure risk in SDI groups 1 to 2 (expected/observed ratios, 1.38 and 1.36, respectively) and underestimated the heart failure risk in groups 4 to 5 (expected/observed ratios, 0.95 and 0.80, respectively). Graphical evaluation demonstrated that the recalibration of WATCH-DM using an SDI group-based correction factor improved predictive capabilities as supported by reduction in the χ2 test results (801-27 in SDI groups I; 623-23 in SDI group V). CONCLUSIONS: Including social determinants of health to recalibrate the WATCH-DM score improved risk prediction highlighting the importance of including social determinants in future clinical risk prediction models.

Association of five diet scores with severe NAFLD incidence: A prospective study from UK Biobank.

AIM: This study aimed to contrast the associations of five common diet scores with severe non-alcoholic fatty liver disease (NAFLD) incidence. MATERIALS AND METHODS: In total, 162 999 UK Biobank participants were included in this prospective population-based study. Five international diet scores were included: the 14-Item Mediterranean Diet Adherence Screener (MEDAS-14), the Recommended Food Score (RFS), the Healthy Diet Indicator (HDI), the Mediterranean Diet Score and the Mediterranean-DASH Intervention for Neurodegenerative Delay score. As each score has different measurements and scales, all scores were standardized and categorized into quartiles. Cox proportional hazard models adjusted for confounder factors investigated associations between the standardized quartiles and severe NAFLD incidence. RESULTS: Over a median follow-up of 10.2 years, 1370 participants were diagnosed with severe NAFLD. When the analyses were fully adjusted, participants in quartile 4 using the MEDAS-14 and RFS scores, as well as those in quartiles 2 and 3 using the HDI score, had a significantly lower risk of severe incident NAFLD compared with those in quartile 1. The lowest risk was observed in quartile 4 for the MEDAS-14 score [hazard ratio (HR): 0.76 (95% confidence interval (CI): 0.62-0.94)] and the RFS score [HR: 0.82 (95% CI: 0.69-0.96)] and as well as in quartile 2 in the HDI score [HR: 0.80 (95% CI: 0.70-0.91)]. CONCLUSION: MEDAS-14, RFS and HDI scores were the strongest diet score predictors of severe NAFLD. A healthy diet might protect against NAFLD development irrespective of the specific approach used to assess diet. However, following these score recommendations could represent optimal dietary approaches to mitigate NAFLD risk.

Sex-specific heart failure burden across the United States: Global burden of disease 1990-2019.

BACKGROUND: Heart failure (HF) has unique aspects that vary by biological sex. Thus, understanding sex-specific trends of HF in the US population is crucial to develop targeted interventions. We aimed to analyze the burden of HF in female and male patients across the US, from 1990 to 2019. METHODS: Using the Global Burden of Disease (GBD) study data from 2019, we performed an analysis of the burden of HF from 1990-2019, across US states and regions. The GBD defined HF through studies that used symptom-based criteria and expressed the burden of HF as the age-adjusted prevalence and years lived with disability (YLDs) rates per 100,000 individuals. RESULTS: The age-adjusted prevalence of HF for the US in 2019 was 926.2 (95% UI [799.6, 1,079.0]) for females and 1,291.2 (95% UI [1,104.1, 1,496.8]) for males. Notably, our findings also highlight cyclic fluctuations in HF prevalence over time, with peaks occurring in the mid-1990s and around 2010, while reaching their lowest points in around 2000 and 2018. Among individuals >70 years of age, the absolute number of individuals with HF was higher in females, and this age group doubled the absolute count between 1990 and 2019. Comparing 1990-1994 to 2015-2019, 10 states had increased female HF prevalence, while only 4 states increased male prevalence. Overall, Western states had the greatest relative decline in HF burden, in both sexes. CONCLUSION: The burden of HF in the US is high, although the magnitude of this burden varies according to age, sex, state, and region. There is a significant increase in the absolute number of individuals with HF, especially among women >70 years, expected to continue due to the aging population.

Geographically Weighted Modeling to Explore Social and Environmental Factors Affecting County-Level Cardiovascular Mortality in People With Diabetes in the United States: A Cross-Sectional Analysis.

Disparities exist in the cardiovascular mortality rates among people with type 2 diabetes (T2D). Research has established that these disparities are often related to the environmental and social determinations of health. This study explores the spatial variation between air pollution, social determinants of health and T2D related age-adjusted cardiovascular mortality (aa-CVM) in the United States. We obtained county-level T2D related to aa-CVM (per 100,000 residents) from Centers for Disease Control and Prevention WONDER (Wide-ranging Online Data for Epidemiologic Research) (2010 to 2019). We fit a geographically weighted linear regression with aa-CVM as the outcome and the following covariates (ambient air pollution [particulate matter of 2.5 µm size], median annual household income, racial/ethnic minorities, higher education, rurality, food insecurity, and primary health care access) were included. Overall, the median aa-CVM rate was 92.9 and highest in the South (102.2). In the West, aa-CVM was significantly associated with particulate matter of 2.5 µm size, annual median household income, racial minority status and primary health care access. Food insecurity was the most significant exposure in the Midwest and Northeast, while in the South, annual median household income and food insecurity were significant. In conclusion, this study demonstrated a substantial regional variation of exposure to determinants of T2D related aa-CVM in the United States. These findings should be considered in policy frameworks and interventions as part of community-level approaches to addressing T2D related aa-CVM, and within broader state and national discussions of the importance of population health.