The clinical impact of estimating low-density lipoprotein cholesterol (LDL-C) using different equations in the general population.

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 < 70 mg/dL between the Sampson and Friedewald equations. CONCLUSIONS: Discordance at clinically significant LDL-C cutpoints in both the general population and high-risk subgroups were observed across the three equations. These results show that using different methods of LDL-C calculation or switching between different methods could have clinical implications for many patients.

The impact of multimorbidity and functional limitation on quality of life in patients with heart failure: A multi-site study.

BACKGROUND: Multimorbidity and functional limitation are associated with poor outcomes in heart failure (HF). However, the individual and combined effect of these on health-related quality of life in patients with HF is not well understood. METHODS: Patients aged ≥30 years with two or more HF diagnostic codes and one or more HF-related prescription drugs from four U.S. institutions were mailed a survey to measure patient-centric factors including functional status (activities of daily living [ADLs]) and health-related quality of life (PROMIS-29 Health Profile). Patients with HF from January 1, 2013 to February 1, 2018 were included. Multimorbidity was defined as ≥2 non-cardiovascular comorbidities; functional limitation as any limitation in at least one of eight ADLs. Patients were categorized into four groups by multimorbidity (Yes/No) and functional limitation (Yes/No). We dichotomized the PROMIS-29 sub-scale scores at the median and calculated odd ratios for the four multimorbidity/functional limitation groups. RESULTS: A total of 3330 patients with HF returned the survey (response rate 31%); 3020 completed the questions of interest and were retained. Among these patients (45% female; mean age 73 [standard deviation: 12] years), 29% had neither multimorbidity nor functional limitation, 24% had multimorbidity only, 22% had functional limitation only, and 25% had both. After adjustment, having functional limitation only was associated with higher anxiety (odds ratio [OR]: 3.44, 95% confidence interval [CI]: 2.66-4.45), depression (OR: 3.11, 95% CI: 2.39-4.06), and fatigue (OR: 4.19, 95% CI: 3.25-5.40); worse sleep (OR: 2.14, 95% CI: 1.69-2.72) and pain (OR: 6.73, 95% CI: 5.15-8.78); and greater difficulty with social activities (OR: 9.40, 95% CI: 7.19-12.28) compared with having neither. Results were similar for having both multimorbidity and functional limitation. CONCLUSION: Patients with only functional limitation have similar poor health-related quality of life scores as those with both multimorbidity and functional limitation, underscoring the important role that physical functioning plays in the well-being of patients with HF.

A large, multi-center survey assessing health, social support, literacy, and self-management resources in patients with heart failure.

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.

Discordance Between Very Low-Density Lipoprotein Cholesterol and Low-Density Lipoprotein Cholesterol Increases Cardiovascular Disease Risk in a Geographically Defined Cohort.

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<0.001]) after adjustment for traditional risk factors. The interaction between LDL-C and VLDL-C was not statistically significant (P=0.11). Discordant individuals with high VLDL-C and low LDL-C experienced the highest rate of incident ASCVD events, 16.9 per 1000 person-years, during follow-up. CONCLUSIONS: VLDL-C and lipid discordance are associated with a greater risk of ASCVD and can be estimated from clinically ordered lipid panels to improve ASCVD risk assessment.

The Importance of Estimating Excess Deaths Regionally During the COVID-19 Pandemic.

National or statewide estimates of excess deaths have limited value to understanding the impact of the COVID-19 pandemic regionally. We assessed excess deaths in a 9-county geographically defined population that had low rates of COVID-19 and widescale availability of testing early in the pandemic, well-annotated clinical data, and coverage by 2 medical examiner's offices. We compared mortality rates (MRs) per 100,000 person-years in 2020 and 2021 with those in the 2019 reference period and MR ratios (MRRs). In 2020 and 2021, 177 and 219 deaths, respectively, were attributed to COVID-19 (MR = 52 and 66 per 100,000 person-years, respectively). COVID-19 MRs were highest in males, older persons, those living in rural areas, and those with 7 or more chronic conditions. Compared with 2019, we observed a 10% excess death rate in 2020 (MRR = 1.10 [95% CI, 1.04 to 1.15]), with excess deaths in females, older adults, and those with 7 or more chronic conditions. In contrast, we did not observe excess deaths overall in 2021 compared with 2019 (MRR = 1.04 [95% CI, 0.99 to 1.10]). However, those aged 18 to 39 years (MRR = 1.36 [95% CI, 1.03 to 1.80) and those with 0 or 1 chronic condition (MRR = 1.28 [95% CI, 1.05 to 1.56]) or 7 or more chronic conditions (MRR = 1.09 [95% CI, 1.03 to 1.15]) had increased mortality compared with 2019. This work highlights the value of leveraging regional populations that experienced a similar pandemic wave timeline, mitigation strategies, testing availability, and data quality.

The Metabolic Vulnerability Index: A Novel Marker for Mortality Prediction in Heart Failure.

BACKGROUND: Inflammation and protein energy malnutrition are associated with heart failure (HF) mortality. The metabolic vulnerability index (MVX) is derived from markers of inflammation and malnutrition and measured by nuclear magnetic resonance spectroscopy. MVX has not been examined in HF. OBJECTIVES: The authors sought to examine the prognostic value of MVX in patients with HF. METHODS: The authors prospectively assembled a population-based cohort of patients with HF from 2003 to 2012 and measured MVX scores with a nuclear magnetic resonance scan from plasma collected at enrollment. Patients were divided into 4 MVX score groups and followed until March 31, 2021. RESULTS: The authors studied 1,382 patients (median age: 78 years; 48% women). The median MVX score was 64.6. Patients with higher MVX were older, more likely to be male, have atrial fibrillation, have higher NYHA functional class, and have HF duration of >18 months. Higher MVX was associated with mortality independent of Meta-analysis Global Group in Chronic Heart Failure score, ejection fraction, and other prognostic biomarkers. Compared to those with the lowest MVX, the HRs for MVX groups 2, 3, and 4 were 1.2 (95% CI: 0.9-1.4), 1.6 (95% CI: 1.3-2.0), and 1.8 (95% CI: 1.4-2.2), respectively (Ptrend < 0.001). Measures of model improvement document the added value of MVX in HF for classifying the risk of death beyond the Meta-analysis Global Group in Chronic Heart Failure score and other biomarkers. CONCLUSIONS: In this HF community cohort, MVX was strongly associated with mortality independently of established clinical factors and improved mortality risk classification beyond clinically validated markers. These data underscore the potential of MVX to stratify risk in HF.

Patient Awareness of Heart Failure Diagnosis: A Community Study.

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.

Co-Occurrence of Social Risk Factors and Associated Outcomes in Patients With Heart Failure.

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.

Association Between Fluctuations in Blood Lipid Levels Over Time With Incident Alzheimer Disease and Alzheimer Disease-Related Dementias.

BACKGROUND AND OBJECTIVES: Prevention strategies for Alzheimer disease and Alzheimer disease-related dementias (AD/ADRDs) are urgently needed. Lipid variability, or fluctuations in blood lipid levels at different points in time, has not been examined extensively and may contribute to the risk of AD/ADRD. Lipid panels are a part of routine screening in clinical practice and routinely available in electronic health records (EHR). Thus, in a large geographically defined population-based cohort, we investigated the variation of multiple lipid types and their association to the development of AD/ADRD. METHODS: All residents living in Olmsted County, Minnesota on the index date January 1, 2006, aged 60 years or older without an AD/ADRD diagnosis were identified. Persons with ≥3 lipid measurements including total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), or high-density lipoprotein cholesterol (HDL-C) in the 5 years before index date were included. Lipid variation was defined as any change in individual's lipid levels over time regardless of direction and was measured using variability independent of the mean (VIM). Associations between lipid variation quintiles and incident AD/ADRD were assessed using Cox proportional hazards regression. Participants were followed through 2018 for incident AD/ADRD. RESULTS: The final analysis included 11,571 participants (mean age 71 years; 54% female). Median follow-up was 12.9 years with 2,473 incident AD/ADRD cases. After adjustment for confounding variables including sex, race, baseline lipid measurements, education, BMI, and lipid-lowering treatment, participants in the highest quintile of total cholesterol variability had a 19% increased risk of incident AD/ADRD, and those in highest quintile of triglycerides, variability had a 23% increased risk. DISCUSSION: In a large EHR derived cohort, those in the highest quintile of variability for total cholesterol and triglyceride levels had an increased risk of incident AD/ADRD. Further studies to identify the mechanisms behind this association are needed.

Health Care Utilization and Death in Patients With Heart Failure During the COVID-19 Pandemic.

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.

Variability in Lipid Levels and Risk for Cardiovascular Disease: An Electronic Health Record-Based Population Cohort Study.

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.

Predicting Alzheimer's Disease and Related Dementias in Heart Failure and Atrial Fibrillation.

BACKGROUND: The Framingham Heart Study Dementia Risk Score (FDRS) was developed in a general population of older persons. It is unknown how the FDRS variables predict Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD) in heart failure and atrial fibrillation populations. We aimed to evaluate the predictive ability of the FDRS variables in population-based cohorts of heart failure and atrial fibrillation and to determine whether the addition of other comorbidities and risk factors improves risk prediction for AD/ADRD. METHODS: Residents aged ≥50 years from 7 southeastern Minnesota counties with a first diagnosis of heart failure or atrial fibrillation between January 1, 2013, and December 31, 2017, were identified. Patients with AD/ADRD before or within 6 months after index atrial fibrillation or heart failure and patients who died within 6 months after index were excluded. For both cohorts, models were constructed to predict AD/ADRD after index including the variables in the FDRS. Additional comorbidities and risk factors were added to the models. For all models, c-statistics using 5-fold cross-validation were calculated. RESULTS: Among 3052 patients with heart failure (mean age 75 years, 53% male), 626 developed AD/ADRD; among 4107 patients with atrial fibrillation (mean age 74 years, 57% male), 736 developed AD/ADRD. Among patients with heart failure, the FDRS variables predicted AD/ADRD with c-statistic = 0.69. Adding comorbidities and risk factors improved the c-statistic slightly to 0.70. The FDRS variables also performed well (c-statistic = 0.73) in patients with atrial fibrillation; adding comorbidities and risk factors slightly improved performance (c-statistic = 0.75). CONCLUSIONS: The variables from the FDRS predict AD/ADRD well in both heart failure and atrial fibrillation populations. The addition of comorbidities and risk factors only modestly improved prediction, indicating that the FDRS variables are appropriate to predict AD/ADRD in patients with heart failure and atrial fibrillation.

Rethinking blood eosinophil counts: Epidemiology, associated chronic diseases, and increased risks of cardiovascular disease.

Background: The distribution and determinants of blood eosinophil counts in the general population are unclear. Furthermore, whether elevated blood eosinophil counts increase risk for cardiovascular disease (CVD) and other chronic diseases, other than atopic conditions, remains uncertain. Objective: We sought to describe the distribution of eosinophil counts in the general population and determine the association of eosinophil count with prevalent chronic disease and incident CVD. Methods: A population-based adult cohort was followed from January 1, 2006, to December 31, 2020. Electronic health record data regarding demographic characteristics, prevalent clinical characteristics, and incident CVD were extracted. Associations between blood eosinophil counts and demographic characteristics, chronic diseases, laboratory values, and risks of incident CVD were assessed using chi-square test, ANOVA, and Cox proportional hazards regression. Results: Blood eosinophil counts increased with age, body mass index, and reported smoking and tobacco use. The prevalence of chronic obstructive pulmonary disease, hypertension, cardiac arrhythmias, hyperlipidemia, diabetes mellitus, chronic kidney disease, and cancer increased as eosinophil counts increased. Eosinophil counts were significantly associated with coronary heart disease (hazard ratio [HR], 1.44; 95% CI, 1.12-1.84) and heart failure (HR, 1.62; 95% CI, 1.30-2.01) in fully adjusted models and with stroke/transient ischemic attack (HR, 1.37; 95% CI, 1.16-1.61) and CVD death (HR, 1.49; 95% CI, 1.10-2.00) in a model adjusting for age, sex, race, and ethnicity. Conclusions: Blood eosinophil counts differ by demographic and clinical characteristics as well as by prevalent chronic disease. Moreover, elevated eosinophil counts are associated with risk of CVD. Further prospective investigations are needed to determine the utility of eosinophil counts as a biomarker for CVD risk.

Alzheimer's disease and related dementias and heart failure: A community study.

BACKGROUND: Cognitive function is essential to effective self-management of heart failure (HF). Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD) can coexist with HF, but its exact prevalence and impact on health care utilization and death are not well defined. METHODS: Residents from 7 southeast Minnesota counties with a first-ever diagnosis code for HF between January 1, 2013 and December 31, 2018 were identified. Clinically diagnosed AD/ADRD was ascertained using the Centers for Medicare and Medicaid (CMS) Chronic Conditions Data Warehouse algorithm. Patients were followed through March 31, 2020. Cox and Andersen-Gill models were used to examine associations between AD/ADRD (before and after HF) and death and hospitalizations, respectively. RESULTS: Among 6336 patients with HF (mean age [SD] 75 years [14], 48% female), 644 (10%) carried a diagnosis of AD/ADRD at index HF diagnosis. The 3-year cumulative incidence of AD/ADRD after HF diagnosis was 17%. During follow-up (mean [SD] 3.2 [1.9] years), 2618 deaths and 15,475 hospitalizations occurred. After adjustment, patients with AD/ADRD before HF had nearly a 2.7 times increased risk of death, but no increased risk of hospitalization compared to those without AD/ADRD. When AD/ADRD was diagnosed after the index HF date, patients experienced a 3.7 times increased risk of death and a 73% increased risk of hospitalization compared to those who remain free of AD/ADRD. CONCLUSIONS: In a large, community cohort of patients with incident HF, the burden of AD/ADRD is quite high as more than one-fourth of patients with HF received a diagnosis of AD/ADRD either before or after HF diagnosis. AD/ADRD markedly increases the risk of adverse outcomes in HF underscoring the need for future studies focused on holistic approaches to improve outcomes.

Bridging the Granularity Gap in Family History Information Extracted from Clinical Narratives.

Family history (FH) is important for disease risk assessment and prevention. However, incorporating FH information derived from electronic health records (EHRs) for downstream analytics is challenging due to the lack of standardization. We aimed to automatically align FH concepts derived from a clinical corpus to disease category resources popularly used, including Clinical Classification System (CCS), Phecode, Comparative Toxicogenomics Database (CTD), Human phenotype ontology, and Human disease ontology (HDO). Leveraging the Unified Medical Language System (UMLS), we achieved high mapping coverages of FH concepts in those resources, using the parent and broader/alike relations available in the UMLS. Among the five resources, CTD has the best coverage (93%) of FH concepts, HDO has the coarsest granularity of FH disease categories, while CCS showed the finest-grained regarding disease categories. The study suggests that we can mitigate the challenge of various degrees of granularity of NLP-derived FH using those ontology or terminological resources.

Minnesota COVID-19 Lockdowns: The Effect on Acute Myocardial Infarctions and Revascularizations in the Community.

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.

Adhesion pathway proteins and risk of atrial fibrillation in the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: The cellular adhesion pathway has been suggested as playing an important role in the pathogenesis of atrial fibrillation (AF). However, prior studies that have investigated the role of adhesion pathway proteins in risk of AF have been limited in the number of proteins that were studied and in the ethnic and racial diversity of the study population. Therefore we aimed to study the associations of fifteen adhesion pathway proteins with incident AF in a large, diverse population. METHODS: Multi-Ethnic Study of Atherosclerosis participants from four races/ethnicities (n = 2504) with protein levels measured were followed for incident AF (n = 253). HGF protein was measured on Exam 1 samples (N = 6669; AF n = 851). Cox proportional hazards regression was used to assess the association of AF with 15 adhesion pathway proteins. Bonferroni correction was applied to account for multiple comparisons. RESULTS: After adjusting for potential confounding variables (age, sex, race/ethnicity, height, body mass index, systolic blood pressure, antihypertension therapy, diabetes status, current smoker, current alcohol use, and total and HDL cholesterol), and accounting for multiple testing (P < 0.05/15 = 0.0033), circulating levels of the following proteins were positively associated with a higher risk of AF: MMP-2 (HR per standard deviation increment, 1.27; 95% CI 1.11‒1.45), TIMP-2 (HR 1.28; 95% CI 1.12‒1.46), VCAM-1 (HR 1.32; 95% CI 1.16‒1.50), and SLPI (HR 1.22; 95% CI 1.07‒1.38). The association between proteins and AF did not differ by race/ethnicity. CONCLUSIONS: Circulating levels of MMP-2, TIMP-2, VCAM-1, and SLPI were positively associated with an increased risk of incident AF in a diverse population. Our findings suggest that adhesion pathway proteins may be important risk predictors of AF.

Longitudinal cohorts for harnessing the electronic health record for disease prediction in a US population.

PURPOSE: The depth and breadth of clinical data within electronic health record (EHR) systems paired with innovative machine learning methods can be leveraged to identify novel risk factors for complex diseases. However, analysing the EHR is challenging due to complexity and quality of the data. Therefore, we developed large electronic population-based cohorts with comprehensive harmonised and processed EHR data. PARTICIPANTS: All individuals 30 years of age or older who resided in Olmsted County, Minnesota on 1 January 2006 were identified for the discovery cohort. Algorithms to define a variety of patient characteristics were developed and validated, thus building a comprehensive risk profile for each patient. Patients are followed for incident diseases and ageing-related outcomes. Using the same methods, an independent validation cohort was assembled by identifying all individuals 30 years of age or older who resided in the largely rural 26-county area of southern Minnesota and western Wisconsin on 1 January 2013. FINDINGS TO DATE: For the discovery cohort, 76 255 individuals (median age 49; 53% women) were identified from which a total of 9 644 221 laboratory results; 9 513 840 diagnosis codes; 10 924 291 procedure codes; 1 277 231 outpatient drug prescriptions; 966 136 heart rate measurements and 1 159 836 blood pressure (BP) measurements were retrieved during the baseline time period. The most prevalent conditions in this cohort were hyperlipidaemia, hypertension and arthritis. For the validation cohort, 333 460 individuals (median age 54; 52% women) were identified and to date, a total of 19 926 750 diagnosis codes, 10 527 444 heart rate measurements and 7 356 344 BP measurements were retrieved during baseline. FUTURE PLANS: Using advanced machine learning approaches, these electronic cohorts will be used to identify novel sex-specific risk factors for complex diseases. These approaches will allow us to address several challenges with the use of EHR.

Recent trends in cardiovascular disease deaths: a state specific perspective.

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.

Premature Myocardial Infarction: A Community Study.

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.