Manemann, Sheila M.

Background: Prevention strategies for Alzheimer’s disease and Alzheimer’s disease related dementias (AD/ADRDs) are urgently needed for reducing incidence. Intra-patient variability in lipid levels is a potentially modifiable risk factor for incident AD/ADRD. Although regular lipid measurements are a part of common clinical practice and longitudinal data routinely available in electronic health records (EHR), research examining this association between AD/ADRD and lipid variability across multiple lipid types remains scarce. Methods: All residents living in Olmsted County, MN on 1/1/2006 age ≥60 years without an AD/ADRD diagnosis were identified using Centers for Medicare & Medicaid Services diagnostic codes. Persons with ≥3 lipid measurements (total cholesterol or triglycerides) in the 5 years prior to index date were retained. Lipid variability was quantified using variability independent of the mean (VIM). Models were adjusted for traditional risk factors. Associations between lipid variability quintiles and incident AD/ADRD were assessed using Cox proportional hazards regression. Multiple imputation was used for missing covariates. Participants were followed through 2018 for incident AD/ADRD. Results: The final analysis included data on 11,551 participants with total cholesterol and 11,502 participants with triglycerides. Participants had a mean age of 71 (range 60-99) years, and were primarily white (96%). Females (54%) were also slightly more frequent than males. Median follow up was 12.9 years (range: 0-13). Participants in the highest quintile of variability for total cholesterol and triglycerides had a 20% increased risk of incident AD/ADRD. Similar results were found in the subset with complete covariate data. Conclusion: In a large EHR derived cohort, persons in the highest quintile of lipid variation had an increased risk of incident AD/ADRD. Further studies to identify the mechanisms behind this risk factor and replication of these results across a more diverse population are needed.

Background: Larger within-patient variability of lipid levels has been associated with an increased risk of cardiovascular disease (CVD). However, measures of lipid variability are not currently used clinically. We investigated the feasibility of calculating lipid variability within a large electronic health record (EHR)-based population cohort and assessed associations with incident CVD. Methods: We identified all individuals ≥40 years of age who resided in Olmsted County, MN on 1/1/2006 (index date) without prior CVD. CVD was defined as myocardial infarction, coronary artery bypass graft surgery, percutaneous coronary intervention or stroke. Patients with ≥3 measurements of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and/or triglycerides during the 5 years before the index date were retained in the analyses. Lipid variability was calculated using variability independent of the mean (VIM). Patients were followed through 9/30/2017 for incident CVD (including CVD death). Cox regression was used to investigate the association between quintiles of lipid VIMs and incident CVD. Results: We identified 18,642 individuals (mean age 60; 55% female) who were free of CVD at baseline and VIM calculated for at least one lipid measurement. After adjustment, those in the highest VIM quintiles of total cholesterol had a 25% increased risk of CVD (Q5 vs. Q1 HR: 1.25, 95% CI: 1.08-1.45; Table). We observed similar results for LDL-C (Q5 vs. Q1 HR: 1.20, 95% CI: 1.04-1.39) and HDL-C (Q5 vs. Q1 HR: 1.25, 95% CI: 1.09-1.43). There was no association between triglyceride variability quintiles and CVD risk. Conclusion: In a large EHR-based population cohort, high variability in total cholesterol, HDL-C and LDL-C was associated with an increased risk of CVD, independently of traditional risk factors, suggesting it may be a target for intervention. Lipid variability can be calculated in the EHR environment but more research is needed to determine its clinical utility.

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 <0.001). After a mean (SD) follow‐up of 2.8 (1.7) years, 2440 deaths, 20 506 emergency department visits, and 11 311 hospitalizations occurred. After adjustment, rurality was independently associated with an increased risk of death (hazard ratio [HR], 1.18; 95% CI, 1.09–1.29) and a reduced risk of emergency department visits (HR, 0.89; 95% CI, 0.82–0.97) and hospitalizations (HR, 0.78; 95% CI, 0.73–0.84). Conclusions Among patients with HF, living in a rural area is associated with an increased risk of death and fewer emergency department visits and hospitalizations. Further study to identify and address the mechanisms through which rural residence influences mortality and healthcare utilization in HF is needed in order to reduce disparities in rural health.

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.

Background: The effective self-management of heart failure (HF) is highly dependent on cognitive function. Dementia frequently coexists with HF, but its exact prevalence and impact on health care utilization and death is not well understood. Methods: Residents from 7 southeast Minnesota counties with a first-ever code for HF (ICD-9 428 and ICD-10 I50) between 1/1/2012 and 12/31/2017 were identified. Dementia before and after the HF diagnosis was ascertained with codes recommended by the US Department of Health and Human Services. Patients were followed through 12/31/2018 for death and hospitalizations. Cox and Andersen-Gill models were used to examine associations between dementia (prior and post HF) and death and hospitalizations, respectively. Dementia after HF was analyzed as a time-dependent variable. Results: Among 6,312 patients with HF (mean age 75 years, 49% female), 636 (10%) had a prior diagnosis of dementia. After a mean (SD) follow-up of 3.1 (1.8) years, 601 (9.5%) patients were diagnosed with dementia post HF. The median time from HF to dementia was 1.3 years, with 43% of dementia cases occurring within 1 year and 64% within 2 years post HF. During follow-up, 2,678 deaths and 15,095 hospitalizations occurred. After adjustment, patients with dementia before HF had nearly a 2-times increased risk of death and 10% increased risk of hospitalization compared to those that did not have dementia (Table). Dementia after HF was associated with a 78% increased risk of death and 63% increased risk of hospitalization compared to those that did not have dementia. Conclusions: Approximately 10% of patients had dementia prior to HF and 10% develop dementia shortly after HF diagnosis. Patients with HF and dementia have an increased risk of death and hospitalization compared to dementia-free counterparts. These data underscore the importance of recognizing the presence and impact of dementia on outcomes in HF to optimize care delivery.

Background: Current cardiovascular disease (CVD) risk scores are derived from research cohorts and are particularly inaccurate in women, older adults, and those with missing data. To overcome these limitations, we aimed to develop a cohort to capitalize on the depth and breadth of clinical data within electronic health record (EHR) systems in order to develop next-generation sex-specific risk prediction scores for incident CVD. Methods: All individuals 30 years of age or older residing in Olmsted County, Minnesota on 1/1/2006 were identified. We developed and validated algorithms to define a variety of risk factors, thus building a comprehensive risk profile for each patient. Outcomes including myocardial infarction (MI), percutaneous intervention (PCI), coronary artery bypass graft (CABG), and CVD death were ascertained through 9/30/2017. Results: We identified 73,069 individuals without CVD (Table). We retrieved a total of 14,962,762 lab results; 14,534,466 diagnoses; 17,062,601 services/procedures; 1,236,998 outpatient prescriptions; 1,079,065 heart rate measurements; and 1,320,115 blood pressure measurements. The median number of blood pressure and heart rate measurements ascertained per individuals were 11 and 9, respectively. The five most prevalent conditions were: hypertension, hyperlipidemia, arthritis, depression, and cardiac arrhythmias. During follow-up 1,455 MIs, 1,581 PCI, 652 CABG, and 2,161 CVD-related deaths occurred. Conclusions: We developed a cohort with comprehensive risk profiles and follow-up for each patient. Using sophisticated machine learning approaches, this electronic cohort will be utilized to develop next-generation sex-specific CVD risk prediction scores. These approaches will allow us to address several challenges with use of EHR data including the ability to 1) deal with missing values, 2) assess and utilize a large number of variables without over-fitting, 3) allow non-linear relationships, and 4) use time-to-event data.

Background: Patient reported measures are fundamental to patient centered research and are often collected by questionnaires. Low participation can compromise the validity of the results; transparent reporting and comparing characteristics of participants to nonparticipants is important to assess the generalizability of survey results. We analyzed participation in a survey of social determinants of health among a population-based sample of patients with heart failure (HF). Methods: A total of 7920 residents from 11 Minnesota counties were identified with a first-ever code for HF (ICD-9 428 and ICD-10 I50) between 1/1/2013 and 12/31/2016. Participants completed a battery of 12 questionnaires by mail or telephone. Characteristics and outcomes data were extracted from medical records and compared between participants and nonparticipants. Response rate (RR) was calculated using guidelines of the American Association for Public Opinion Research (AAPOR). The association between nonparticipation and outcomes was examined by Cox proportional hazards regression for death and Andersen-Gill modeling for hospitalizations. Results: Among 7920 patients, 3438 responded to the survey (AAPOR RR#2= 43%). Numerous clinical and demographic differences between participants and non-participants were noted (Table), particularly for education, marital status, and neuropsychiatric conditions. After a mean (±SD) of 1.5±1 years after survey administration, 1,577 deaths and 5,873 hospitalizations had occurred. Nonparticipation was associated with a two-fold increased risk of death (HR: 2.30; 95% CI: 2.06-2.57; p<0.001) and a 10% increased risk of hospitalizations (HR: 1.10; 95% CI: 1.01-1.21; p=0.03) after adjusting for age, sex, marital status, coronary disease, arrhythmia, hyperlipidemia, cancer, chronic kidney disease, depression and anxiety. Conclusions: In a large survey of patients with HF, participation was associated with large differences in clinical and demographic characteristics and outcomes. Examining the impact of participation is critical to draw inference from studies of patient reported measures.

Background: The decline in cardiovascular disease (CVD) mortality in the United States noted since the mid 1970s has recently leveled off. This has generated concern and a need for further analyses to understand geographic variation, cause-specific deaths, location of death, and age-specific trends. Methods: Death certificate data obtained from the Minnesota Department of Health were used for analysis. The American Heart Association (AHA) classification was applied to the underlying cause of death to generate the following CVD categories: coronary heart disease (CHD), non-CHD diseases of the heart, and non-cardiac circulatory diseases. Temporal trends in death rates were explored by negative binomial regression, which enables estimates of age- and sex-adjusted average annual percentage changes (AAPCs). Differences in AAPCs between 2000-2009 and 2010-2017 were tested overall and across demographic, CVD, and location of death categories. Results: CVD mortality rates, which were declining in 2000-2009, have leveled off in 2010-2017 (Table). These trends were observed across all subgroups. After adjusting for sex, the age group that drove the decline in rates from 2000-2009 was the 65-84 year old group, which experienced no change in rates from 2010-2017. Across CVD categories, after adjusting for age and sex, the decline in rates from 2000-2009 was largely attributable to steep reductions in CHD and non-cardiac circulatory diseases, with lesser reduction in non-CHD diseases of the heart. In 2010-2017, CHD and non-cardiac circulatory diseases rates showed no change, whereas the rate of non-CHD diseases of the heart increased. The rates for in- and out-of-hospital deaths improved in 2000-2009 with no further improvement observed in 2010-2017. Conclusions: CVD mortality rates are no longer declining in Minnesota, paralleling national trends. These trends are particularly concerning for non-CHD diseases of the heart.

Background: Previous studies have indicated that living in a rural or non-urban area may be associated with poor health outcomes. However, data on rurality and death in heart failure (HF) are scarce. Methods: Residents from 11 southeast MN counties with a first-ever code for HF (including codes ICD-9 428 and ICD-10 I50) between 1/1/2013 and 12/31/2016 were identified. Resident address was geo-coded and classified according to the Rural-Urban Commuting Area (RUCA) codes, which classifies US census tracts to measure population density, urbanization and daily commuting. Rurality was defined as living in a non-metropolitan area. Cox proportional hazards regression was used to determine the association between living in a rural vs. urban area and death. Results: Among 6,996 patients (mean age 73 years, 52% male), 54% of patients lived in a rural area. These patients were older and had a lower level of educational attainment and comorbidity burden (p<0.001). After a mean (SD) follow-up of 2.9 (1.3) years, 1,856 deaths occurred. Living in a rural area was univariately associated with a higher risk of death (HR 1.20, 95% CI: 1.09-1.31; Table). After adjustment for age, sex, education status and comorbidity burden, rurality remained associated with an increased risk of death (HR 1.15; 95% CI: 1.04-1.27). Conclusions: Among patients with HF, living in a rural area is associated with an increased risk of death. Further study to identify and address the mechanisms through which rural residence influences mortality in patients with HF is needed.

Objective Grip strength is a well-characterised measure of weakness and of poor muscle performance, but there is a lack of consensus on its prognostic implications in terms of cardiac adverse events in patients with cardiac disorders. Methods Articles were searched in PubMed, Cochrane Library, BioMed Central and EMBASE. The main inclusion criteria were patients with cardiac disorders (ischaemic heart disease, heart failure (HF), cardiomyopathies, valvulopathies, arrhythmias); evaluation of grip strength by handheld dynamometer; and relation between grip strength and outcomes. The endpoints of the study were cardiac death, all-cause mortality, hospital admission for HF, cerebrovascular accident (CVA) and myocardial infarction (MI). Data of interest were retrieved from the articles and after contact with authors, and then pooled in an individual patient meta-analysis. Univariate and multivariate logistic regression was performed to define predictors of outcomes. Results Overall, 23 480 patients were included from 7 studies. The mean age was 62.3±6.9 years and 70% were male. The mean follow-up was 2.82±1.7 years. After multivariate analysis grip strength (difference of 5 kg, 5× kg) emerged as an independent predictor of cardiac death (OR 0.84, 95% CI 0.79 to 0.89, p<0.0001), all-cause death (OR 0.87, 95% CI 0.85 to 0.89, p<0.0001) and hospital admission for HF (OR 0.88, 95% CI 0.84 to 0.92, p<0.0001). On the contrary, we did not find any relationship between grip strength and occurrence of MI or CVA. Conclusion In patients with cardiac disorders, grip strength predicted cardiac death, all-cause death and hospital admission for HF. Trial registration number CRD42015025280.