Chamberlain, Alanna M.

Background: Atrial fibrillation (AF) is the most common sustained arrhythmia with prevalence increasing over the last decade. However, data on recent temporal trends in incidence of AF have been inconsistent, with some reports of increasing trends over time and others indicating no change in incidence over time. Therefore, we aimed to determine how the incidence of AF has changed over the last decade in a community in the Midwest USA. Methods: Between 2013 and 2023, adults (aged 18 and older) with incident AF were identified in a 27-county region in the Midwest. AF was identified using diagnostic codes by employing an electronic algorithm requiring 1 inpatient code or 2 outpatient codes separated by >7 days but within 1 year. For total rates, age - and sex-adjusted incidence rates were standardized to the 2010 US total population. Poisson regression was used to calculate the incidence rate ratio of AF for 2023 vs 2013. Results: We identified 44,930 individuals with incident AF from 2013 to 2023. Of these, 56.4% were male, the mean (SD) age was 72.8 (13.5) years, and 95.8% were non-Hispanic white. The age-and sex-adjusted incidence rates (per 1,000) and 95% confidence intervals standardized to the 2010 US total population were 5.24 (5.07-5.41) in 2013, 5.73 (5.56-5.91) in 2018, and 5.44 (5.28-5.61) in 2023. Although a drop in incidence was observed corresponding to the COVID-19 pandemic, a small increase in the overall incidence of AF was observed over time. The overall incidence rate ratio (95% CI) for 2023 vs 2013 was 1.07 (1.02-1.11), P=0.003. The incidence rates were higher in men compared to women and increased with older age ( Figure 1 ). However, differences in AF incidence by sex were greatest in the youngest age group and attenuated with older age (incidence rate ratio (95% CI): 2.18 (2.10-2.28) for ages 18-64 years, 1.76 (1.70-1.83) for ages 65-74 years, 1.38 (1.33-1.42) for ages 75-84 years, and 1.23 (1.18-1.28) for ages 85 years and older). Conclusion: In this 27-county region in the Midwest, although small in magnitude, a statistically significant increase in AF incidence was observed over time from 2013 to 2023. Furthermore, the incidence of AF was higher in men compared with women, especially in younger age groups.

Introduction: Cardiovascular risks following SARS-CoV-2 infection are incompletely defined. We evaluated evolving cardiovascular outcomes across COVID-19 variant eras using a large community-based cohort to inform risk stratification and clinical care. Methods: We conducted a retrospective cohort study of 162,471 adults with COVID-19 between March 2020 and December 2023 using the Rochester Epidemiology Project. Patients were stratified by variant era (Pre-Delta, Delta, and Omicron). Cardiovascular outcomes included major adverse cardiovascular events (MACE: myocardial infarction, stroke, death), ischemic and inflammatory heart disease, thrombotic events, and dysrhythmias. Diagnoses were identified using ICD-10 codes and validated in a subset. Cumulative incidence was estimated using Kaplan-Meier and competing risk models. Cox proportional hazards regression was used to assess differences by era and age. Results: MACE occurred in 4,922 patients, primarily in those ≥80 (2-year incidence: 17%). Event rates peaked within 30 days post-infection, with marked variation by variant. In patients ≥80, 30-day MACE risk was highest in the Pre-Delta (HR 3.85; 95% CI, 3.14–4.71) and Delta (HR 2.72; 95% CI, 2.13–3.47) eras versus Omicron. After 30 days, event rates fell and era differences narrowed. Thrombotic events (n=2,090; 1.4%) decreased across eras. Ischemic and inflammatory heart disease rates were stable. Myocarditis/pericarditis were rare (0.1%) without age trends. Dysrhythmias affected 6,765 patients (2-year incidence: 4.9%) and rose with age (2.0% in <40 vs. 19.9% in ≥80). Within 30 days, risk was higher in the Pre-Delta and Delta eras for age ≥40, especially ≥80 (Delta HR 3.08; 95% CI, 2.08–4.56) and 60–79 (HR 2.23; 95% CI, 1.75–2.85). Among those 40–59, Delta posed the highest risk (HR 2.74; 95% CI, 1.94–3.86 vs. Pre-Delta HR 1.77; 95% CI, 1.26–2.49). No differences were observed in <40. Beyond 30 days, risk converged across variants. Conclusion: Cardiovascular risk after SARS-CoV-2 infection was concentrated in the first 30 days, with attenuation thereafter. While MACE and thrombotic event rates declined over time, early dysrhythmia risk varied by variant and age, especially in older adults. These findings define a time-sensitive, variant-specific risk window and support short-term, risk-stratified post-COVID monitoring. This work informs targeted follow-up protocols by infection era and age, with implications for quality improvement, resource use, and equitable care.

Abstract Alcohol misuse among women has risen compared to men. Women experience barriers to engaging in patient-centered comparative effectiveness research (CER) that, in turn, limits the evidence base for addressing alcohol misuse in this population. In this manuscript, we describe WomenWise, a community-partnered project and outline how we co-developed community focused CER training curriculum and collaboratively planned future partnered learning sessions (PLSs) with Community Advisory Board (CAB) feedback. Through this approach we aim to empower women to contribute to future patient-centered CER and enhance the stakeholder capacity for future patient-centered research.

AbstractPurposeThe Collaborative care model (CoCM) is the leading model for integrating behavioral health into primary care for patients with major depressive disorder (MDD). However, CoCM requires engagement and ongoing participation. We aimed to assess whether two area‐based measures, the area‐deprivation index (ADI) and rurality, were associated with enrollment, participation, and outcomes with CoCM.MethodsThis was an observational analysis of Mayo Clinic patients eligible for CoCM: adults aged ≥18 years, empaneled in primary care, and with a PHQ‐9 of ≥10. We operationalized ADI as quintiles with Q1 being least deprived and Q5 being most deprived and rurality using RUCA codes with two categories: urban and rural. We evaluated enrollment in CoCM, drop out defined by leaving the program early, the count and type of contacts with the care coordinator, and clinical improvement measured using the PHQ‐9.FindingsWe identified 54,030 individuals with 16,532 (30.6%) residing in rural areas and 11,122 (20.6%) residing in the most deprived ADI quintile (Q5). Living in a rural area was associated with lower enrollment in CoCM (–2.3 percentage points [95% confidence interval (CI): –2.5, 2.2]), longer length in CoCM (18.6 days [95% CI: 5.7, 31.5]), more contacts with the care coordinator (1.1 contacts [95% CI: 0.2, 2.0]), and worse response and remission. In contrast, ADI Q5 was only associated with worse response and remission.ConclusionsRurality was associated with lower enrollment, greater engagement, and worse clinical outcomes. More work may be needed to address enrollment barriers for individuals living in rural areas to improve clinical outcomes.

ABSTRACTBackgroundIdiopathic inflammatory myopathies, beyond inclusion body myositis (IBM), have demonstrated an increased risk of adverse cardiovascular outcomes, particularly myocardial infarction (MI). This study evaluated the risk of cardiovascular disease in IBM.MethodsWe conducted a non‐concurrent cohort study utilizing the expanded Rochester Epidemiologic Project, including 50 patients with IBM, matched 1:6 to age‐, sex‐, and calendar year‐matched referents without IBM. Baseline cardiovascular risk factors were recorded. Differences in baseline covariates were adjusted by the inverse probability of treatment weighting method. Participants were followed from the index date forward to determine relative risks (RR) and hazard ratios (HR) for the development of cardiovascular outcomes including MI, ischemic stroke, cardiomyopathy, congestive heart failure (CHF), and peripheral vascular disease (PVD).Results50 patients with IBM and 294 matched population referents were included. Baseline cardiovascular risk factors were similar between groups. Aspirin use was more common (28% vs. 18%, p = 0.03) and statin use less common (26% vs. 38%, p = 0.04) in IBM versus referents. Patients with IBM had an increased hazard of MI compared to referents [HR: 5.79, 95% CI (2.51, 13.36)]. The risk of MI remained consistently elevated across all models, after accounting for potential confounders. For PVD, 16/50 IBM patients versus 16/287 referents were excluded due to pre‐existing PVD at index (p < 0.001). Among remaining participants, RR for PVD was 2.38 (0.82, 6.9). IBM was not associated with an increased risk of ischemic stroke, cardiomyopathy, or CHF.ConclusionsIBM is associated with increased risk of MI compared to population referents. Heightened cardiovascular monitoring and prevention strategies are needed in IBM.

Objective: Over 3 million Americans have heart failure with preserved ejection fraction (HFpEF). Effective guideline directed medical treatments (GDMT) are increasingly available but patients with HFpEF are likely under-detected (particularly women) and not receiving GDMT. Limited data are available informing the extent of HFpEF under-detection in the community. Hypothesis: Among patients with undifferentiated dyspnea and a high risk for unrecognized HFpEF, fewer than 50% will receive a HFpEF diagnosis during two years of follow-up; underrecognition will be greater among women. Methods: We identified 22,134 patients aged ≥30 in the Rochester Epidemiology Project (a medical records linkage system comprising a 27-county region of southeastern Minnesota and western Wisconsin) with evidence of unexplained dyspnea (≥2 ICD codes for dyspnea separated by >1 day) without prior documented etiology including HF or lung disease, during the time period 2018-2022. We calculated the recently validated HFpEF-Age-BMI-Atrial Fibrillation (HFpEF-ABA) score to estimate the probability of underlying HFpEF. Cox proportional hazards models regressed risk for incident HFpEF diagnosis on HFpEF-ABA score (dichotomized as ≥80% vs. <80%) with multivariable adjustment for sex, race and ethnicity. HRs(95%CIs) are presented. Results: Patients were 59±16 yrs, 50.8% women, 88.6% white, 3.1% Black, 3.7% other race, 4.6% Hispanic. Atrial fibrillation prevalence was 9.4% and mean BMI=31.4±7.8. Prevalence of HFpEF-ABA≥80% was 22.4%(n=4,958): 22.7% among women and 22.1% among men. The cumulative incidence of clinically-recognized HFpEF diagnosis at two years follow-up was 9.7% among women and 12.8% among men (log-rank p<0.01). HFpEF incidence was elevated with high HFpEF-ABA scores(≥80%): HR(95%CI) among women=3.72 (3.35, 4.14), and men=3.42 (3.11, 3.76). Among those with clinically diagnosed HFpEF during follow-up, mean time from date of first dyspnea ICD code to HFpEF diagnosis was 1.26 years overall: 1.31 and 1.21 years in women and men, respectively (p=0.05). Conclusions: One in five patients with undifferentiated dyspnea have probable undiagnosed HFpEF, and of that group, only 30% receive a clinical diagnosis, requiring an average of over 1 year to be recognized. The rate of diagnosis is even lower among women than men. Further study is warranted to implement evidence-based algorithms supporting detection of undiagnosed HFpEF in the community, especially in women.

Background Multimorbidity is common in patients with atrial fibrillation (AF), yet comorbidity patterns are not well documented. Methods The prevalence of 18 chronic conditions (6 cardiometabolic, 7 other somatic, 5 mental health) was obtained in patients with new-onset AF from 2013-2017 from a 27-county region and controls matched 1:1 on age, sex, and county of residence. For AF patients and controls separately, clustering of conditions and co-occurrence beyond chance was estimated (using the asymmetric Somers’ D statistic), overall and for ages <65, 65-74, 75-84, and ≥85 years. Results Among 16,509 patients with AF (median age 76 years, 57% men), few (4%) did not have any of the 18 chronic conditions, whereas nearly one-quarter of controls (23%) did not have any chronic conditions. Clustering of cardiometabolic conditions was common in both AF patients and controls, but clustering of other somatic conditions was more common in AF. Although the prevalence of most condition pairs was higher in AF patients, controls had a larger number of condition pairs occurring together beyond chance. In persons aged <65 years, AF patients more frequently exhibited concordance of condition pairs that included either pairs of somatic conditions or a combination of conditions from different condition groups. In persons aged 65-74 years, AF patients more frequently had pairs of other somatic conditions. Conclusion Patterns of co-existing conditions differed between patients with AF and controls, particularly in younger ages. A better understanding of the clinical consequences of multimorbidity in AF patients, including those diagnosed at younger ages, is needed.

Background: Nationally, many ASCVD patients fail to achieve an LDL-C <70 mg/dL, and uptake of both statin and non-statin therapies is low. The degree to which this varies across health systems is less clear. Methods: A cross sectional analysis was performed where lipid levels and lipid lowering therapies (LLT) were assessed using electronic health record data in patients with a previous diagnosis of ASCVD. The data was obtained across 14 US healthcare systems between 1/1/2021-12/31/2022. Proportions of patients with an active prescription of any statin, high intensity statin, ezetimibe, PCSK9i, and combination therapy (two or more agents) within 395 days of the most recent LDL-C value (index date) was evaluated overall and by participating site. Additionally, the proportion of patients with an LDL-C <70 mg/dL at the index date was also assessed. Results: Across 14 health systems, 1,118,623 patients with ASCVD were identified (median 61,840 per health system, range 8,161-182,315). Overall, 675,776 (60.4%) had an LDL-C level in the past year (range 39.1% - 70.8%). Of those with a lipid level, achievement of LDL-C <70 mg/dL ranged from 34.6-47.2%. In total, 42.6% were on any statin, 20.1% were on a high intensity statin, 4.3% on ezetimibe, and 1.2% on a PCSK9i. Only 2.9% were on combination therapy of a statin with ezetimibe or a PCSK9i. Variability was seen across health systems in utilization of each of these therapies, however even in the highest performing health systems, LLT uptake and achievement of LDL-C < 70mg/dL remained low ( Figure). Conclusion: Variability in utilization of LLT in ASCVD patients between health systems suggests that system-level factors may impact achieving guideline-based LDL-C goals. Despite the variability, the highest proportion of patients achieving an LDL-C <70mg/dL remained under 50% indicating the need for aggressive implementation efforts.

Introduction: Living in an area with high Area Deprivation Index (ADI) is linked to worse cardiovascular disease (CVD) outcomes. However, the association of ADI with type 2 diabetes (T2D), a major CVD risk factor, is incompletely described. This knowledge may guide primary CVD prevention. Method: Rochester Epidemiology Project is a medical record linkage system of persons in southeast Minnesota and southwest Wisconsin. We identified 253,890 persons (aged 4–98 yrs on July 1, 2015) in 9 counties with >90% population coverage. ADI scores, from 2015 home addresses, were grouped into quartiles of low (Q1) to high (Q4) deprivation. We excluded persons with type 1 diabetes (T1D) or history of T2D and identified new T2D cases (2015-2020) using ICD codes, HbA1c and medications. We examined the association between ADI quartile and risk of incident T2D using Cox regression with persons right censored at death, T2D, T1D or last visit. Models were adjusted for age and gender, and reported adjusted hazard ratios (aHR [95% confidence interval]). Results: Age, gender, and race statistically differed across ADI quartiles (Table). Age × ADI interaction was significant ( P <.001). T2D incidence ranged from 6.3 (Q1) to 9.0 (Q4) per 1000 person-years ( P <.001). Women vs. men/non-binary persons (combined due to limited non-binary persons) had 30% lower risk of incident T2D (aHR 0.70 [0.67–0.72]). Risk of incident T2D was higher in persons from higher ADI areas. At median age of 48.6 yrs, the risk was 30% higher in Q2 (aHR 1.3 [1.22–1.38]), 38% higher in Q3 (aHR 1.38 [1.30–1.47]) and 53% higher in Q4 (aHR 1.53 [1.43–1.62]) vs. Q1. Higher ADI was associated with higher incident T2D in younger persons, with risk attenuation with increasing age (Figure). Conclusion: In this population cohort, persons, particularly of younger age, living in more deprived areas had a higher risk of incident T2D. ADI may help identify areas for targeted T2D screening, with implications for CVD screening and prevention.

Background: Data on prevalence of hypertension in the United States come primarily from in-person data collected by the National Health and Nutrition Examination Survey and self-reports in the Behavioral Risk Factor Surveillance Survey. Electronic phenotypic algorithms for hypertension that include diagnosis codes, blood pressure values, and antihypertensive treatment have been proposed and tested. Objective: To describe prevalence of hypertension in Minnesota adults using data from a statewide electronic health record (EHR) consortium, the Minnesota EHR Consortium (MNEHRC). Methods: Data from 11 health systems participating in the MNEHRC were standardized to a common data model allowing for distributed querying of EHR data. Data were de-duplicated using a one-way hash algorithm. Preliminary prevalence of hypertension in 2023 was estimated in Minnesota residents with ≥ 1 encounter in the past 3 years who had ≥1 diagnosis of hypertension in the past 5 years. Medicaid insurance status was determined via linkage with state enrollment files. Residential addresses of patients were geocoded to census tracts and social vulnerability index (SVI) of census tracts was determined. Results: Among 4,369,470 Minnesotan age 18 and older in 2023, 23.6% had hypertension based on ≥1 diagnosis code. Prevalence increased with age, was higher in men (26% vs. 22% in women), and adjusted for age and sex was highest in Black (30%) and Native American (27%) compared with White (23%) and Hispanic (21%) Minnesotans. Within each race/ethnic group, those insured by Medicaid had a higher adjusted hypertension prevalence than those with other insurance types. The prevalence of hypertension in census tracts with moderate to high SVI ranged from 3% to 43%, but on average was similar to the statewide prevalence of 24% (see image 1). Prevalence of hypertension in race/ethnicity, sex, and age subgroups in higher SVI census tracts was similar to the statewide prevalence in those subgroups. Conclusions: The prevalence of hypertension in Minnesota was described in detail by demographic characteristics, geography and social vulnerability. Future work will expand the electronic hypertension phenotype and examine quality of care.