Search

Abstract Background Low-density lipoprotein cholesterol (LDL-C) is associated with atherosclerotic cardiovascular disease (ASCVD). Friedewald, Sampson, and Martin-Hopkins equations are used to calculate LDL-C. This study compares the impact of switching between these equations in a large geographically defined population. Materials and methods Data for individuals who had a lipid panel ordered clinically between 2010 and 2019 were included. Comparisons were made across groups using the two-sample t-test or chi-square test as appropriate. Discordances between LDL measures based on clinically actionable thresholds were summarized using contingency tables. Results The cohort included 198,166 patients (mean age 54 years, 54% female). The equations perform similarly at the lower range of triglycerides but began to diverge at a triglyceride level of 125 mg/dL. However, at triglycerides of 175 mg/dL and higher, the Martin-Hopkins equation estimated higher LDL-C values than the Samson equation. This discordance was further exasperated at triglyceride values of 400 to 800 mg/dL. When comparing the Sampson and Friedewald equations, at triglycerides are below 175 mg/dL, 9% of patients were discordant at the 70 mg/dL cutpoint, whereas 42.4% were discordant when triglycerides are between 175 and 400 mg/dL. Discordance was observed at the clinically actionable LDL-C cutpoint of 190 mg/dL with the Friedewald equation estimating lower LDL-C than the other equations. In a high-risk subgroup (ASCVD risk score > 20%), 16.3% of patients were discordant at the clinical cutpoint of LDL-C

Abstract Background Most patients with heart failure (HF) have multimorbidity which may cause difficulties with self-management. Understanding the resources patients draw upon to effectively manage their health is fundamental to designing new practice models to improve outcomes in HF. We describe the rationale, conceptual framework, and implementation of a multi-center survey of HF patients, characterize differences between responders and non-responders, and summarize patient characteristics and responses to the survey constructs among responders. Methods This was a multi-center cross-sectional survey study with linked electronic health record (EHR) data. Our survey was guided by the Chronic Care Model to understand the distribution of patient-centric factors, including health literacy, social support, self-management, and functional and mental status in patients with HF. Most questions were from existing validated questionnaires. The survey was administered to HF patients aged ≥ 30 years from 4 health systems in PCORnet® (the National Patient-Centered Clinical Research Network): Essentia Health, Intermountain Health, Mayo Clinic, and The Ohio State University. Each health system mapped their EHR data to a standardized PCORnet Common Data Model, which was used to extract demographic and clinical data on survey responders and non-responders. Results Across the 4 sites, 10,662 patients with HF were invited to participate, and 3330 completed the survey (response rate: 31%). Responders were older (74 vs. 71 years; standardized difference (95% CI): 0.18 (0.13, 0.22)), less racially diverse (3% vs. 12% non-White; standardized difference (95% CI): -0.32 (-0.36, -0.28)), and had higher prevalence of many chronic conditions than non-responders, and thus may not be representative of all HF patients. The internal reliability of the validated questionnaires in our survey was good (range of Cronbach’s alpha: 0.50–0.96). Responders reported their health was generally good or fair, they frequently had cardiovascular comorbidities, > 50% had difficulty climbing stairs, and > 10% reported difficulties with bathing, preparing meals, and using transportation. Nearly 80% of patients had family or friends sit with them during a doctor visit, and 54% managed their health by themselves. Patients reported generally low perceived support for self-management related to exercise and diet. Conclusions More than half of patients with HF managed their health by themselves. Increased understanding of self-management resources may guide the development of interventions to improve HF outcomes.

Abstract Background Heart failure (HF) is a complex clinical syndrome with persistently high mortality. High-throughput proteomic technologies offer new opportunities to improve HF risk stratification, but their contribution remains to be clearly defined. We aimed to systematically review prognostic studies using high-throughput proteomics to identify protein signatures associated with HF mortality. Methods We searched four databases and two clinical trial registries for articles published from 2012 to 2023. HF proteomics studies measuring high numbers of proteins using aptamer or antibody-based affinity platforms on human plasma or serum with outcomes of all-cause or cardiovascular death were included. Two reviewers independently screened articles, extracted data, and assessed the risk of bias. A third reviewer resolved conflicts. We assessed the risk of bias using the Risk Of Bias In Non-randomized Studies—of Exposure tool. Results Out of 5131 unique articles identified, nine articles were included in the review. The nine studies were observational; three used the aptamer platform, and six used the antibody platform. We found considerable heterogeneity across studies in measurement panels, HF definitions, ejection fraction categorization, follow-up duration, and outcome definitions, and a lack of risk estimates for most protein associations. Hence, we proceeded with a systematic review rather than a meta-analysis. In two comparable aptamer studies in patients with HF with reduced ejection fraction, 21 proteins were identified in common for the association with all-cause death. Among these, one protein, WAP four-disulfide core domain protein 2 was also reported in an antibody study on HFrEF and for the association with CV death. We proposed standardized reporting criteria to facilitate the interpretation of future studies. Conclusions In this systematic review of nine studies evaluating the association of proteomics with mortality in HF, we identified a limited number of proteins common across several studies. Heterogeneity across studies compromised drawing broad inferences, underscoring the importance of standardized approaches to reporting.

BackgroundHeart failure (HF) risk is greater in rural versus urban regions in the United States (US), potentially due to differences in healthcare coverage and access. Whether this excess risk applies to countries with universal healthcare is unclear and the underlying biological mechanisms are unknown. In the prospective United Kingdom (UK) Biobank, we investigated urban–rural regional differences in HF risk and the mechanistic role of biological aging.MethodsMultivariable Cox regression was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of incident HF in relation to residential urban–rural region and a Biological Health Score (BHS) that reflects biological aging from environmental, social, or dietary stressors. We estimated the proportion of the total effect of urban–rural region on HF mediated through BHS.ResultsAmong 417,441 European participants, 10,332 incident HF cases were diagnosed during the follow-up. Compared to participants in large urban regions of Scotland, those in England/Wales had significantly increased HF risk (smaller urban: HR = 1.83, 95%CI: 1.64–2.03; suburban: HR = 1.77, 95%CI: 1.56–2.01; very rural: HR = 1.61, 95%CI: 1.39–1.85). Additionally, we found a dose–response relationship between increased biological aging and HF risk (HRper 1 SD increase = 1.14 (95%CI: 1.12–1.17). Increased biological aging mediated a notable 6.6% (p

Background Frailty is common in heart failure (HF) and is associated with death but not routinely captured clinically. Frailty is linked with inflammation and malnutrition, which can be assessed by a novel plasma multimarker score: the metabolic vulnerability index (MVX). We sought to evaluate the associations between frailty and MVX and their prognostic impact. Methods and Results In an HF community cohort (2003–2012), we measured frailty as a proportion of deficits present out of 32 physical limitations and comorbidities, MVX by nuclear magnetic resonance spectroscopy, and collected extensive longitudinal clinical data. Patients were categorized by frailty score (≤0.14, >0.14 and ≤0.27, >0.27) and MVX score (≤50, >50 and ≤60, >60 and ≤70, >70). Cox models estimated associations of frailty and MVX with death, adjusted for Meta‐Analysis Global Group in Chronic Heart Failure (MAGGIC) score and NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide). Uno's C‐statistic measured the incremental value of MVX beyond frailty and clinical factors. Weibull's accelerated failure time regression assessed whether MVX mediated the association between frailty and death. We studied 985 patients (median age, 77; 48% women). Frailty and MVX were weakly correlated (Spearman's ρ=0.21). The highest frailty group experienced an increased rate of death, independent of MVX, MAGGIC score, and NT‐proBNP (hazard ratio, 3.3 [95% CI, 2.5–4.2]). Frailty improved Uno's c‐statistic beyond MAGGIC score and NT‐proBNP (0.69–0.73). MVX only mediated 3.3% and 4.5% of the association between high and medium frailty groups and death, respectively. Conclusions In this HF cohort, frailty and MVX are weakly correlated. Both independently contribute to stratifying the risk of death, suggesting that they capture distinct domains of vulnerability in HF.

Background Clinical risk scores are used to identify those at high risk of atherosclerotic cardiovascular disease (ASCVD). Despite preventative efforts, residual risk remains for many individuals. Very low‐density lipoprotein cholesterol (VLDL‐C) and lipid discordance could be contributors to the residual risk of ASCVD. Methods and Results Cardiovascular disease–free residents, aged ≥40 years, living in Olmsted County, Minnesota, were identified through the Rochester Epidemiology Project. Low‐density lipoprotein cholesterol (LDL‐C) and VLDL‐C were estimated from clinically ordered lipid panels using the Sampson equation. Participants were categorized into concordant and discordant lipid pairings based on clinical cut points. Rates of incident ASCVD, including percutaneous coronary intervention, coronary artery bypass grafting, stroke, or myocardial infarction, were calculated during follow‐up. The association of LDL‐C and VLDL‐C with ASCVD was assessed using Cox proportional hazards regression. Interaction between LDL‐C and VLDL‐C was assessed. The study population (n=39 098) was primarily White race (94%) and female sex (57%), with a mean age of 54 years. VLDL‐C (per 10‐mg/dL increase) was significantly associated with an increased risk of incident ASCVD (hazard ratio, 1.07 [95% CI, 1.05–1.09]; P

BackgroundThe relationship between ketone bodies (KB) and mortality in patients with heart failure (HF) syndrome has not been well established.ObjectivesThe aim of this study is to assess the distribution of KB in HF, identify clinical correlates, and examine the associations between plasma KB and all-cause mortality in a population-based HF cohort.MethodsThe plasma KB levels were measured by nuclear magnetic resonance spectroscopy. Multivariable linear regression was used to examine associations between clinical correlates and KB levels. Proportional hazard regression was employed to examine associations between KB (represented as both continuous and categorical variables) and mortality, with adjustment for several clinical covariates.ResultsAmong the 1,382 HF patients with KB measurements, the median (IQR) age was 78 (68, 84) and 52% were men. The median (IQR) KB was found to be 180 (134, 308) μM. Higher KB levels were associated with advanced HF (NYHA class III–IV) and higher NT-proBNP levels (both P

Objective: To compare the 1-year health care utilization and mortality in persons living with heart failure (HF) before and during the coronavirus disease 2019 (COVID-19) pandemic. Patients and Methods: Residents of a 9-county area in southeastern Minnesota aged 18 years or older with a HF diagnosis on January 1, 2019; January 1, 2020; and January 1, 2021, were identified and followed up for 1-year for vital status, emergency department (ED) visits, and hospitalizations. Results: We identified 5631 patients with HF (mean age, 76 years; 53% men) on January 1, 2019, 5996 patients (mean age, 76 years; 52% men) on January 1, 2020, and 6162 patients (mean age, 75 years; 54% men) on January 1, 2021. After adjustment for comorbidities and risk factors, patients with HF in 2020 and patients with HF in 2021 experienced similar risks of mortality compared with those in 2019. After adjustment, patients with HF in 2020 and 2021 were less likely to experience all-cause hospitalizations (2020: rate ratio [RR], 0.88; 95% CI, 0.81-0.95; 2021: RR, 0.90; 95% CI, 0.83-0.97) compared with patients in 2019. Patients with HF in 2020 were also less likely to experience ED visits (RR, 0.85; 95% CI, 0.80-0.92). Conclusion: In this large population-based study in southeastern Minnesota, we observed an approximately 10% decrease in hospitalizations among patients with HF in 2020 and 2021 and a 15% decrease in ED visits in 2020 compared with those in 2019. Despite the change in health care utilization, we found no difference in the 1-year mortality between patients with HF in 2020 and those in 2021 compared with those in 2019. It is unknown whether any longer-term consequences will be observed.

Abstract Background Efforts to limit the spread of COVID-19 have included public space closures, mask usage, and quarantining. Studies regarding the impact of these measures on the psychosocial and behavioral health outcomes of the workforce have focused frequently on healthcare employees. To expand the literature base, we deployed a one-year longitudinal survey among mostly non-healthcare employees assessing changes in select psychosocial outcomes, health behaviors, and COVID-19-related transmission prevention behaviors and perceptions. Methods We deployed the CAPTURE baseline survey across eight companies from November 20, 2020-February 8, 2021. The baseline survey included questions on psychosocial outcomes, health behaviors, and COVID-19 transmission prevention behaviors, with several questions containing a retrospective component to cover the time period prior to the pandemic. Additional questions on vaccination status and social support were subsequently added, and the updated survey deployed to the same baseline participants at three, six, and 12 months after baseline survey deployment. We analyzed data descriptively and performed Friedman’s and subsequent Wilcoxon-signed rank tests, as appropriate, to compare data within and between time points. Results A total of 3607, 1788, 1545, and 1687 employees completed the baseline, 3-month, 6-month, and 12-month CAPTURE surveys, respectively, with 816 employees completing all four time points. Employees reported higher stress, anxiety, fatigue, and feelings of being unsafe across all time points compared to pre-pandemic. Time spent sleeping increased initially but returned to pre-pandemic levels at follow-up. Lower rates of physical activity and higher rates of non-work screen time and alcohol consumption relative to pre-pandemic were also reported. Over 90% of employees perceived wearing a mask, physical distancing, and receiving the COVID-19 vaccine as ‘moderately’ or ‘very important’ in preventing the spread of COVID-19 across all time points. Conclusions Relative to pre-pandemic, poorer psychosocial outcomes and worsened health behaviors were observed across all time points, with values worse at the baseline and 12-month time points when COVID-19 surges were highest. While COVID-19 prevention behaviors were consistently deemed to be important by employees, the psychosocial outcome and health behavior data suggest the potential for harmful long-term effects of the pandemic on the well-being of non-healthcare employees.

Background Heart failure (HF) is a complex disease that contributes to a high number of hospitalizations, deaths, and economic health care costs each year. However, among patients with HF, there is a lack of awareness of their HF diagnosis that has not been fully examined. Methods and Results Residents from 3 counties of southeast Minnesota with a first‐ever International Classification of Diseases, Ninth Revision (ICD‐9) code 428 or Tenth Revision (ICD‐10) code I50 between January 1, 2013 and March 31, 2016 (N=2461) were prospectively surveyed to measure HF self‐awareness. A total of 1114 patients returned the survey (response rate, 45%), and 787 had validated HF upon medical record review. Among these 787 patients with HF (mean age, 76 years; 53% men), 37% (n=293) were aware of their HF diagnosis. After adjustment, being a woman (odds ratio [OR], 1.56 [95% CI, 1.10–2.22]), having HF with reduced ejection fraction (OR, 1.58 [95% CI, 1.13–2.22]), attending the HF clinic (OR, 4.07 [95% CI, 2.25–7.36]), and having coronary artery disease (OR, 1.65 [95% CI, 1.16–2.37]) were all associated with increased awareness of an HF diagnosis. Conversely, having diabetes was associated with decreased awareness of an HF diagnosis (adjusted OR, 0.69 [95% CI, 0.50–0.95]). Conclusions Awareness of an HF diagnosis is low in a community population of patients with HF. Strategies to improve patient awareness of their diagnosis should be implemented to improve self‐care behaviors and outcomes in patients with HF.

Background Among patients with heart failure (HF), social risk factors (SRFs) are associated with poor outcomes. However, less is known about how co‐occurrence of SRFs affect all‐cause health care utilization for patients with HF. The objective was to address this gap using a novel approach to classify co‐occurrence of SRFs. Methods and Results This was a cohort study of residents living in an 11‐county region of southeast Minnesota, aged ≥18 years with a first‐ever diagnosis for HF between January 2013 and June 2017. SRFs, including education, health literacy, social isolation, and race and ethnicity, were obtained via surveys. Area‐deprivation index and rural‐urban commuting area codes were determined from patient addresses. Associations between SRFs and outcomes (emergency department visits and hospitalizations) were assessed using Andersen‐Gill models. Latent class analysis was used to identify subgroups of SRFs; associations with outcomes were examined. A total of 3142 patients with HF (mean age, 73.4 years; 45% women) had SRF data available. The SRFs with the strongest association with hospitalizations were education, social isolation, and area‐deprivation index. We identified 4 groups using latent class analysis, with group 3, characterized by more SRFs, at increased risk of emergency department visits (hazard ratio [HR], 1.33 [95% CI, 1.23–1.45]) and hospitalizations (HR, 1.42 [95% CI, 1.28–1.58]). Conclusions Low educational attainment, high social isolation, and high area‐deprivation index had the strongest associations. We identified meaningful subgroups with respect to SRFs, and these subgroups were associated with outcomes. These findings suggest that it is possible to apply latent class analysis to better understand the co‐occurrence of SRFs among patients with HF.

Background Larger within‐patient variability of lipid levels has been associated with increased risk of cardiovascular disease (CVD); however, measures of lipid variability require ≥3 measurements and are not currently used clinically. We investigated the feasibility of calculating lipid variability within a large electronic health record–based population cohort and assessed associations with incident CVD. Methods and Results We identified all individuals ≥40 years of age who resided in Olmsted County, MN, on January 1, 2006 (index date), without prior CVD, defined as myocardial infarction, coronary artery bypass graft surgery, percutaneous coronary intervention, or CVD death. Patients with ≥3 measurements of total cholesterol, low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, or triglycerides during the 5 years before the index date were retained. Lipid variability was calculated using variability independent of the mean. Patients were followed through December 31, 2020 for incident CVD. We identified 19 652 individuals (mean age 61 years; 55% female), who were CVD‐free and had variability independent of the mean calculated for at least 1 lipid type. After adjustment, those with highest total cholesterol variability had a 20% increased risk of CVD (Q5 versus Q1 hazard ratio, 1.20 [95% CI, 1.06–1.37]). Results were similar for low‐density lipoprotein cholesterol and high‐density lipoprotein cholesterol. Conclusions In a large electronic health record–based population cohort, high variability in total cholesterol, high‐density lipoprotein cholesterol, and low‐density lipoprotein cholesterol was associated with an increased risk of CVD, independent of traditional risk factors, suggesting it may be a possible risk marker and target for intervention. Lipid variability can be calculated in the electronic health record environment, but more research is needed to determine its clinical utility.

Objective: To study associations between the Minnesota coronavirus disease 2019 (COVID-19) mitigation strategies on incidence rates of acute myocardial infarction (MI) or revascularization among residents of Southeast Minnesota. Methods: Using the Rochester Epidemiology Project, all adult residents of a nine-county region of Southeast Minnesota who had an incident MI or revascularization between January 1, 2015, and December 31, 2020, were identified. Events were defined as primary in-patient diagnosis of MI or undergoing revascularization. We estimated age- and sex-standardized incidence rates and incidence rate ratios (IRRs) stratified by key factors, comparing 2020 to 2015–2019. We also calculated IRRs by periods corresponding to Minnesota’s COVID-19 mitigation timeline: “Pre-lockdown” (January 1–March 11, 2020), “First lockdown” (March 12–May 31, 2020), “Between lockdowns” (June 1–November 20, 2020), and “Second lockdown” (November 21–December 31, 2020). Results: The incidence rate in 2020 was 32% lower than in 2015–2019 (24 vs 36 events/100,000 person-months; IRR, 0.68; 95% CI, 0.62-0.74). Incidence rates were lower in 2020 versus 2015–2019 during the first lockdown (IRR, 0.54; 95% CI, 0.44-0.66), in between lockdowns (IRR, 0.70; 95% CI, 0.61-0.79), and during the second lockdown (IRR, 0.54; 95% CI, 0.41-0.72). April had the lowest IRR (IRR 0.48; 95% CI, 0.34-0.68), followed by August (IRR, 0.55; 95% CI, 0.40-0.76) and December (IRR, 0.56; 95% CI, 0.41-0.77). Similar declines were observed across sex and all age groups, and in both urban and rural residents. Conclusion: Mitigation measures for COVID-19 were associated with a reduction in hospitalizations for acute MI and revascularization in Southeast Minnesota. The reduction was most pronounced during the lockdown periods but persisted between lockdowns.

Objective: To investigate the impact of coronavirus disease 2019 (COVID-19) on psychosocial and behavioral responses of the non–health care workforce and to evaluate transmission prevention behavior implementation in the workplace. Participants and Methods: We deployed the baseline questionnaire of a prospective online survey from November 20, 2020, through February 8, 2021 to US-based employees. The survey included questions on psychosocial and behavioral responses in addition to transmission prevention behaviors (e.g., mask wearing). Select questions asked employees to report perceptions and behaviors before and during the COVID-19 pandemic. Data were analyzed descriptively and stratified by work from home (WFH) percentage. Results: In total, 3607 employees from 8 companies completed the survey. Most participants (70.0%) averaged 90% or more of their time WFH during the pandemic. Employees reported increases in stress (54.0%), anxiety (57.4%), fatigue (51.6%), feeling unsafe (50.4%), lack of companionship (60.5%), and feeling isolated from others (69.3%) from before to during the pandemic. Productivity was perceived to decrease for 42.9% of employees and non–work-related screen time and alcohol consumption to increase for 50.7% and 25.1% of employees, respectively, from before to during the pandemic. Adverse changes were worse among those with lower WFH percentages. Most employees reported wearing a mask (98.2%), washing hands regularly (95.7%), and physically distancing (93.6%) in the workplace. Conclusion: These results suggest worsened psychosocial and behavioral outcomes from before to during the COVID-19 pandemic and higher transmission prevention behavior implementation among non–health care employees. These observations provide novel insight into how the COVID-19 pandemic has impacted non–health care employees.

Abstract Background The rate of decline in cardiovascular disease (CVD) mortality has lessened nationally. How these findings apply to specific states or causes of CVD deaths is not known. Examining these trends at the state level is important to plan local interventions. Methods We analyzed CVD mortality trends in Minnesota (MN) using the U.S. Centers for Disease Control and Prevention (CDC) Wide-ranging ONline Data for Epidemiologic Research (WONDER). Trends were analyzed by age, sex, type of CVD and location of death. Results CVD mortality rates in MN declined in 2000–2009 and then leveled off in 2010–2018, paralleling national rates. Age- and sex-adjusted CVD mortality decreased by 3.7% per year in 2000–2009 (average annual percent changes [AAPC]: -3.7; 95% CI: − 4.8, − 2.6) with no change observed in 2010–2018. Those aged 65–84 years had the most rapid early decline in CVD mortality (AAPC: -5.9, 95% CI: − 6.2, − 5.7) and had less improvement in 2010–2018 (AAPC: -1.8, 95% CI: − 2.2, − 1.5), and the younger age group (25–64 years) now experiences the most adverse trends (AAPC: 1.2, 95% CI: 0.7–1.8). Coronary heart disease (CHD) and cerebrovascular disease had the largest relative decreases in mortality in 2000–2009 (CHD AAPC: -5.2; 95% CI: − 6.5,-3.9; cerebrovascular disease AAPC: -4.4, 95% CI: − 5.2, − 3.6) with no change 2010–2018. Heart failure (HF)/cardiomyopathy followed similar trends with a 2.5% decrease (AAPC 95% CI: − 3.5, − 1.5) per year in 2000–2009 and no change in 2010–2018. Deaths from other CVD also decreased in the early time period (AAPC: -1.6, 95% CI: − 2.7, − 0.5) but increased in 2010–2018 (AAPC: 1.9, 95% CI: 0.5, 3.3). In- and out-of-hospital death rates improved in 2000–2009 with a slowing in improvement for in-hospital death and no further improvement for out-of-hospital death in 2010–2018. Conclusion Concerning CVD mortality trends occurred in MN. In the most recent decade (2010–2018) mortality from all CVD subtypes plateaued or even increased. CVD mortality among the younger age groups increased as well. These data are congruent with adverse national trends supporting their generalizability. These adverse trends underscore the urgent need for CVD prevention and treatment, as well as continued surveillance to assess progress at the state and national level.

Objective: To evaluate the trends in incident premature myocardial infarction (MI) and prevalence of cardiac risk factors in a population-based cohort. Methods: We studied a population-based cohort of incident premature MIs among residents (MI in men aged 18-55 years and women aged 18-65 years) in Olmsted County, Minnesota, during a 26-year period from January 1, 1987 through December 31, 2012. Recurrent MI and death after incident premature MI were enumerated through September 30, 2018. Results: Of 3276 MI cases, 850 were premature events (37.9% [322/850] women). Age-adjusted premature MI incidence rates (2012 vs 1987) declined by 39% in men (rate ratio, 0.61; 95% CI, 0.46 to 0.81]) and 61% in women (rate ratio, 0.39; 95% CI, 0.27 to 0.57). Among men with premature MI, the prevalence of hypertension, diabetes, and hyperlipidemia increased over time, whereas in women, only the prevalence of hyperlipidemia increased. During a mean follow-up of 13.3 years, there was no temporal decline in recurrent MI in men and women. Women showed 66% decreased risk for mortality (hazard ratio, 0.34; 95% CI, 0.17 to 0.68) over time, whereas men showed no change. Conclusion: The incidence of premature MI declined over a 26-year period for both men and women. The risk factor profile of persons presenting with MI worsened over time, especially in men. Death following incident MI declined only in women. These results underscore the importance of primary prevention in young adults and of sex-specific approaches.

Background Electronic medical records are increasingly used to identify disease cohorts; however, computable phenotypes using electronic medical record data are often unable to distinguish between prevalent and incident cases. Methods and Results We identified all Olmsted County, Minnesota residents aged ≥18 with a first‐ever International Classification of Diseases, Ninth Revision (ICD‐9) diagnostic code for atrial fibrillation or atrial flutter from 2000 to 2014 (N=6177), and a random sample with an International Classification of Diseases, Tenth Revision (ICD‐10) code from 2016 to 2018 (N=200). Trained nurse abstractors reviewed all medical records to validate the events and ascertain the date of onset (incidence date). Various algorithms based on number and types of codes (inpatient/outpatient), medications, and procedures were evaluated. Positive predictive value (PPV) and sensitivity of the algorithms were calculated. The lowest PPV was observed for 1 code (64.4%), and the highest PPV was observed for 2 codes (any type) >7 days apart but within 1 year (71.6%). Requiring either 1 inpatient or 2 outpatient codes separated by >7 days but within 1 year had the best balance between PPV (69.9%) and sensitivity (95.5%). PPVs were slightly higher using ICD‐10 codes. Requiring an anticoagulant or antiarrhythmic prescription or electrical cardioversion in addition to diagnostic code(s) modestly improved the PPVs at the expense of large reductions in sensitivity. Conclusions We developed simple, exportable, computable phenotypes for atrial fibrillation using structured electronic medical record data. However, use of diagnostic codes to identify incident atrial fibrillation is prone to some misclassification. Further study is warranted to determine whether more complex phenotypes, including unstructured data sources or using machine learning techniques, may improve the accuracy of identifying incident atrial fibrillation.

Cardiovascular disease surveillance involves quantifying the evolving population‐level burden of cardiovascular outcomes and risk factors as a data‐driven initial step followed by the implementation of interventional strategies designed to alleviate this burden in the target population. Despite widespread acknowledgement of its potential value, a national surveillance system dedicated specifically to cardiovascular disease does not currently exist in the United States. Routinely collected health care data such as from electronic health records (EHRs) are a possible means of achieving national surveillance. Accordingly, this article elaborates on some key strengths and limitations of using EHR data for establishing a national cardiovascular disease surveillance system. Key strengths discussed include the: (1) ubiquity of EHRs and consequent ability to create a more “national” surveillance system, (2) existence of a common data infrastructure underlying the health care enterprise with respect to data domains and the nomenclature by which these data are expressed, (3) longitudinal length and detail that define EHR data when individuals repeatedly patronize a health care organization, and (4) breadth of outcomes capable of being surveilled with EHRs. Key limitations discussed include the: (1) incomplete ascertainment of health information related to health care–seeking behavior and the disconnect of health care data generated at separate health care organizations, (2) suspect data quality resulting from the default information‐gathering processes within the clinical enterprise, (3) questionable ability to surveil patients through EHRs in the absence of documented interactions, and (4) the challenge in interpreting temporal trends in health metrics, which can be obscured by changing clinical and administrative processes.

Background Prior reports indicate that living in a rural area may be associated with worse health outcomes. However, data on rurality and heart failure (HF) outcomes are scarce. Methods and Results Residents from 6 southeastern Minnesota counties with a first‐ever code for HF (International Classification of Diseases, Ninth Revision [ICD‐9], code 428, and International Classification of Diseases, Tenth Revision [ICD‐10] code I50) between January 1, 2013 and December 31, 2016, were identified. Resident address was classified according to the rural‐urban commuting area codes. Rurality was defined as living in a nonmetropolitan area. Cox regression was used to analyze the association between living in a rural versus urban area and death; Andersen‐Gill models were used for hospitalization and emergency department visits. Among 6003 patients with HF (mean age 74 years, 48% women), 43% lived in a rural area. Rural patients were older and had a lower educational attainment and less comorbidity compared with patients living in urban areas (P

Abstract Introduction: Air pollution is linked to mortality and morbidity. Since humans spend nearly all their time indoors, improving indoor air quality (IAQ) is a compelling approach to mitigate air pollutant exposure. To assess interventions, relying on clinical outcomes may require prolonged follow-up, which hinders feasibility. Thus, identifying biomarkers that respond to changes in IAQ may be useful to assess the effectiveness of interventions. Methods: We conducted a narrative review by searching several databases to identify studies published over the last decade that measured the response of blood, urine, and/or salivary biomarkers to variations (natural and intervention-induced) of changes in indoor air pollutant exposure. Results: Numerous studies reported on associations between IAQ exposures and biomarkers with heterogeneity across study designs and methods. This review summarizes the responses of 113 biomarkers described in 30 articles. The biomarkers which most frequently responded to variations in indoor air pollutant exposures were high sensitivity C-reactive protein (hsCRP), von Willebrand Factor (vWF), 8-hydroxy-2′-deoxyguanosine (8-OHdG), and 1-hydroxypyrene (1-OHP). Conclusions: This review will guide the selection of biomarkers for translational studies evaluating the impact of indoor air pollutants on human health.

Abstract The purpose of this analysis was to develop and validate computable phenotypes for heart failure (HF) with preserved ejection fraction (HFpEF) using claims‐type measures using the Rochester Epidemiology Project. This retrospective study utilized an existing cohort of Olmsted County, Minnesota residents aged ≥ 20 years diagnosed with HF between 2007 and 2015. The gold standard definition of HFpEF included meeting the validated Framingham criteria for HF and having an LVEF ≥ 50%. Computable phenotypes of claims‐type data elements (including ICD‐9/ICD‐10 diagnostic codes and lab test codes) both individually and in combinations were assessed via sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with respect to the gold standard. In the Framingham‐validated cohort, 2,035 patients had HF; 1,172 (58%) had HFpEF. One in‐patient or two out‐patient diagnosis codes of ICD‐9 428.3X or ICD‐10 I50.3X had 46% sensitivity, 88% specificity, 84% PPV, and 54% NPV. The addition of a BNP/NT‐proBNP test code reduced sensitivity to 35% while increasing specificity to 91% (PPV = 84%, NPV = 51%). Broadening the diagnostic codes to ICD‐9 428.0, 428.3X, and 428.9/ICD‐10 I50.3X and I50.9 increased sensitivity at the expense of decreasing specificity (diagnostic code‐only model: 87% sensitivity, 8% specificity, 56% PPV, 30% NPV; diagnostic code and BNP lab code model: 61% sensitivity, 43% specificity, 60% PPV, 45% NPV). In an analysis conducted to mimic real‐world use of the computable phenotypes, any one in‐patient or out‐patient code of ICD‐9 428/ICD‐10 150 among the broader population (N = 3,755) resulted in lower PPV values compared with the Framingham cohort. However, one in‐patient or two out‐patient instances of ICD‐9 428.0, 428.9, or 428.3X/ICD‐10 150.3X or 150.9 brought the PPV values from the two cohorts closer together. While some misclassification remains, the computable phenotypes defined here may be used in claims databases to identify HFpEF patients and to gain a greater understanding of the characteristics of patients with HFpEF.

Background Temporal declines in cardiac stress tests results, coronary revascularization, and cardiovascular mortality have suggested a decline in the population burden of coronary disease until the 2000s. However, recent data indicate these favorable trends could be ending. We aimed to assess the evolution of the population burden of coronary disease in the community by examining trends in angiography and revascularization. Methods and Results We analyzed age‐ and sex‐adjusted trends from all coronary angiographic diagnostic procedures and revascularizations performed in Olmsted County, MN from 2000 to 2018. A total of 12 981 invasive angiograms were performed among 9049 individuals (64% men; 55% aged ≥65 years). Adjusted angiography rates decreased by 30% (95% CI, 25%–34%) between 2000 and 2009 and leveled off thereafter. Including computed tomography, angiography uncovered an increase in angiography use in recent years (risk ratio=1.15 [95% CI, 1.07–1.23] for 2018 versus 2014) and a decline in the prevalence of anatomic CAD from 2000 to 2018. CAD severity declined substantially from 2000 to 2009, followed by a plateau. Among 6570 revascularizations (72% men; 57% aged ≥65 years), 77% were percutaneous coronary interventions and 23% coronary artery bypass graft surgeries. The adjusted revascularization rates declined by 34% (95% CI, 27%–39%) from 2000 to 2009, followed by a plateau (risk ratio=1.10 [95% CI, 1.00–1.22]). Conclusions Between 2000 and 2018 in the community, coronary angiography use declined initially, leveled off, and then increased. Trends in CAD severity and revascularization use decreased then plateaued. The most recent trends are concerning as they suggest the burden of coronary disease is no longer declining. This warrants reinvigorated primary prevention and population surveillance.

BackgroundPerceived social isolation has been shown to have a negative impact on health outcomes, particularly among older adults. However, these relationships have not been fully examined among patients with heart failure. Methods and ResultsResidents from 11 southeast Minnesota counties with a first‐ever International Classification of Diseases, Ninth Revision (ICD‐9) code 428 for heart failure between January 1, 2013, and March 31, 2015 (N=3867), were prospectively surveyed to measure perceived social isolation. A total of 2003 patients returned the survey (response rate, 52%); 1681 patients completed all questions and were retained for analysis. Among these patients (53% men; mean age, 73 years), ≈19% (n=312) had moderate perceived social isolation and 6% (n=108) had high perceived social isolation. After adjustment, patients reporting moderate perceived social isolation did not have an increased risk of death, hospitalizations, or emergency department visits compared with patients reporting low perceived social isolation; however, patients reporting high perceived social isolation had >3.5 times increased risk of death (hazard ratio, 3.74; 95% confidence interval [CI], 1.82–7.70), 68% increased risk of hospitalization (hazard ratio, 1.68; 95% CI, 1.18–2.39), and 57% increased risk of emergency department visits (hazard ratio, 1.57; 95% CI, 1.09–2.27). Compared with patients who self‐reported low perceived social isolation, patients reporting moderate perceived social isolation had a 16% increased risk of outpatient visits (rate ratio, 1.16; 95% CI, 1.03–1.31), whereas those reporting high perceived social isolation had a 26% increased risk (rate ratio, 1.26; 95% CI, 1.04–1.53). ConclusionsIn patients with heart failure, greater perceived social isolation is associated with an increased risk of death and healthcare use. Assessing perceived social isolation during the clinical encounter with a brief screening tool may help identify patients with heart failure at greater risk of poor outcomes.

BackgroundCurrent American Heart Association/American College of Cardiology guidelines recommend the GRACE (Global Registry of Acute Coronary Events) and TIMI (Thrombolysis in Myocardial Infarction) scores to assess myocardial infarction (MI) prognosis. Changes in the epidemiological characteristics of MI and the availability of new biomarkers warrant an assessment of the performance of these scores in contemporary practice. We assessed the following: (1) the performance of GRACE and TIMI to predict 1‐year mortality in a cohort of patients stratified by ST‐segment elevation MI (STEMI) and non‐STEMI (NSTEMI) and (2) the incremental discriminatory power of soluble suppression of tumorigenicity‐2, a myocardial fibrosis biomarker. Methods and ResultsOlmsted County, Minnesota, residents with incident MI (N=1401) were recruited prospectively from November 1, 2002 to December 31, 2012 (mean age, 67 years; 61% men; 79% with NSTEMI). Baseline data were used to calculate risk scores; soluble suppression of tumorigenicity‐2 was measured in stored plasma samples obtained at index MI. C‐statistics adapted to survival data were used to assess the discriminatory power of the risk scores and the improvement gained by adding other markers. During the first year of follow‐up, 190 patients (14%) died. The discriminatory performance to predict death was reasonable for GRACE and poor for TIMI, and was generally worse in those with NSTEMI versus those with STEMI. In people with NSTEMI, sequential addition of comorbidities and soluble suppression of tumorigenicity‐2 substantially improved the c‐statistic over GRACE (from 0.78 to 0.80 to 0.84) and TIMI (from 0.61 to 0.73 to 0.81), respectively (all P≤0.05). ConclusionsGuideline‐recommended scores for risk assessment after MI underperform in contemporary community patients, particularly those with NSTEMI, which now represents most infarcts. Incorporating comorbidities and soluble suppression of tumorigenicity‐2 substantially improves risk prediction, thereby delineating opportunities to improve clinical care.

BackgroundWhile atrial fibrillation is a recognized risk factor for stroke, contemporary data on trends in stroke incidence after the diagnosis of atrial fibrillation are scarce. Methods and ResultsOlmsted County, MN residents with incident atrial fibrillation or atrial flutter (collectively referred to as AF) from 2000 to 2010 were identified. Cox regression determined associations of year of AF diagnosis with ischemic stroke and transient ischemic attack (TIA) occurring through 2013. Among 3247 AF patients, 321 (10%) had an ischemic stroke/TIA over a mean of 4.6 years (incidence rate [95% CI] per 100 person‐years: 2.14 [1.91–2.38]). Two hundred thirty‐nine (7%) of 3265 AF patients experienced an ischemic stroke (incidence rate: 1.54 [1.35–1.75]). The risk of both outcomes remained unchanged over time after adjusting for demographics and comorbidities (hazard ratio [95% CI] per year of AF diagnosis: 1.00 [0.96–1.04] for ischemic stroke/TIA; 1.01 [0.96–1.06] for ischemic stroke only). In analyses restricted to patients with prescription information, the rates of anticoagulation use did not change over time, reaching 50.8% at 1 year after AF diagnosis. Further adjustment for anticoagulation use did not alter the temporal trends in stroke incidence (hazard ratio [95% CI] per year of AF diagnosis: 1.06 [0.97–1.15] for ischemic stroke/TIA; 1.08 [0.98–1.20] for ischemic stroke only). ConclusionsStrokes/TIAs are frequent after AF, occurring in 10% of patients after 5 years of follow‐up. The occurrence of stroke/TIA did not decline over the last decade, which may be influenced by a leveling off of anticoagulation use. This concerning trend has major public health implications.