Chamberlain, Alanna M.

Background Previous reports have described a leveling off of mortality from premature coronary artery disease (CAD). In recent years, the prevalence of cardiovascular risk factors has increased in rural communities and young adults. Methods and Results We extracted CAD mortality rates from the Centers for Disease Control and Prevention Wide‐Ranging Online Data for Epidemiologic Research (CDC WONDER) database from 1999 to 2017, focusing on mortality from premature CAD (defined as <65 years of age in women) and urban–rural differences. Variations in mortality rates over time, assessed with Joinpoint regression modeling, are expressed as estimated annual percentage change (95% CI) and stratified by urbanization, sex, age, and race. Age‐adjusted mortality rates decreased for women and men. Stratification by urbanization revealed that premature CAD mortality is stagnating among women in rural areas. However, this stagnation conceals a statistically significant increase in CAD mortality rates since 2009 in women aged 55 to 64 years (estimated annual percentage change: +1.4%; 95% CI, +0.3% to +2.5%) and since 1999 in women aged 45 to 54 years (estimated annual percentage change: +0.6%; 95% CI, +0.2% to 1.0%). Since 1999, mortality has been stagnating in the youngest group (aged 35–44 years; estimated annual percentage change: +0.2%; 95% CI, −0.4% to +0.8%). Stratification by race indicated an increase in mortality rates among white rural women. Premature CAD mortality remains consistently higher in the rural versus urban United States, regardless of sex, race, and age group. Conclusions Premature CAD mortality rates have declined over time. However, stratification by sex and urbanization reveals disparities that would otherwise remain concealed: CAD mortality rates have increased among women from rural areas since at least 2009.

Background Frailty increases risk for complications after total joint arthroplasty (TJA). Whether this association is influenced by anesthetic administered is unknown. We hypothesized that use of neuraxial (spinal or epidural) anesthesia is associated with better outcomes compared with general anesthesia, and that the effect of anesthesia type on outcomes differs by frailty status. Methods This single-institution cohort study included all patients (≥50 years) from January 2005 through December 2016 undergoing unilateral, primary and revision TJA. Using multivariable Cox regression, we assessed relationships between anesthesia type, a preoperative frailty deficit index (FI) categorized as non-frail (FI <0.11), vulnerable (FI 0.11 to 0.20), and frail (FI >0.20), and complications (mortality, infection, wound complications/hematoma, reoperation, dislocation, and periprosthetic fracture) within 1 year after surgery. Interactions between anesthesia type and frailty were tested, and stratified models were presented when an interaction (p<0.1) was observed. Results Among 18 458 patients undergoing TJA, more patients were classified as frail (21.5%) and vulnerable (36.2%) than non-frail (42.3%). Anesthesia type was not associated with complications after adjusting for age, joint, and revision type. However, in analyzes stratified by frailty, vulnerable patients under neuraxial block had less mortality (HR=0.49; 95% CI 0.27 to 0.89) and wound complications/hematoma (HR=0.71; 95% CI 0.55 to 0.90), whereas no difference in risk by anesthesia type was observed among patients found non-frail or frail. Conclusions Neuraxial anesthesia use among vulnerable patients was associated with improved survival and less wound complications. Calculating preoperative frailty prior to TJA informs perioperative risk and enhances shared-decision making for selection of anesthesia type.

Background Social determinants of health are relevant to cardiovascular outcomes but have had limited examination in atrial fibrillation (AF). Objectives The purpose of this study was to examine the association of annual household income and cardiovascular outcomes in individuals with AF. Methods We analysed administrative claims for individuals with AF from 2009 to 2015 captured by a health claims database. We categorised estimates of annual household income as <$40 000; $40–$59 999; $60–$74 999; $75–$99 999; and ≥$100 000. Covariates included demographics, education, cardiovascular disease risk factors, comorbid conditions and anticoagulation. We examined event rates by income category and in multivariable-adjusted models in reference to the highest income category (≥$100 000). Results Our analysis included 336 736 individuals (age 72.7±11.9 years; 44.5% women; 82.6% white, 8.4% black, 7.0% Hispanic and 2.1% Asian) with AF followed for median (25th and 75th percentile) of 1.5 (95% CI 0.6 to 3.0) years. We observed an inverse association between income and heart failure and myocardial infarction (MI) with evidence of progressive risk across decreased income categories. Individuals with household income <$40 000 had the greatest risk for heart failure (HR 1.17; 95% CI 1.05 to 1.30) and MI (HR 1.18; 95% CI 0.98 to 1.41) compared with those with income ≥$100 000. Conclusions We identified an association between lower household income and adverse outcomes in a large cohort of individuals with AF. Our findings support consideration of income in the evaluation of cardiovascular risk in individuals with AF.

Background: Uncontrolled blood pressure (BP) is a leading preventable cause of death that remains common in the US population despite the availability of effective medications. New technology and program innovation has high potential to improve BP but may be expensive and burdensome for patients, clinicians, health systems, and payers and may not produce desired results or reduce existing disparities in BP control. Methods and Results: The PCORnet Blood Pressure Control Laboratory is a platform designed to enable national surveillance and facilitate quality improvement and comparative effectiveness research. The platform uses PCORnet, the National Patient-Centered Clinical Research Network, for engagement of health systems and collection of electronic health record data, and the Eureka Research Platform for eConsent and collection of patient-reported outcomes and mHealth data from wearable devices and smartphones. Three demonstration projects are underway: BP track will conduct national surveillance of BP control and related clinical processes by measuring theory-derived pragmatic BP control metrics using electronic health record data, with a focus on tracking disparities over time; BP MAP will conduct a cluster-randomized trial comparing effectiveness of 2 versions of a BP control quality improvement program; BP Home will conduct an individual patient-level randomized trial comparing effectiveness of smartphone-linked versus standard home BP monitoring. Thus far, BP Track has collected electronic health record data from over 826 000 eligible patients with hypertension who completed ≈3.1 million ambulatory visits. Preliminary results demonstrate substantial room for improvement in BP control (<140/90 mm Hg), which was 58% overall, and in the clinical processes relevant for BP control. For example, only 12% of patients with hypertension with a high BP measurement during an ambulatory visit received an order for a new antihypertensive medication. Conclusions: The PCORnet Blood Pressure Control Laboratory is designed to be a reusable platform for efficient surveillance and comparative effectiveness research; results from demonstration projects are forthcoming.

OBJECTIVE Recent population-based and hospital cohort studies have reported a decreasing incidence of aneurysmal subarachnoid hemorrhage (aSAH) and declining aSAH-associated case-fatality rates. Principal drivers of these trends are debated, but improvements in smoking cessation and hypertension control may be critical factors. METHODS The population-based medical records linkage system of the Rochester Epidemiological Project was used to document aSAH incidence and 30-day case fatality rates during a 20-year study period (1996–2016) in Olmsted County, Minnesota. Incidence rates in the study period were compared with data from a previous Olmsted County study concerning aSAH incidence from 1965 to 1995 and with regional trends in tobacco use. RESULTS One hundred nineteen incident cases of aSAH were included. The median age at hemorrhage was 59 years (range 16–94 years), and 74 patients were female (62.2%). The overall average annual aSAH incidence rate was 4.2/100,000 person-years (P-Y). The aSAH incidence rate decreased from 5.7/100,000 in 1996 to 3.5/100,000 P-Y in 2011–2016. The overall aSAH-associated 30-day case-fatality rate was 21.9% and declined by approximately 0.5% annually. An accelerated decline in the fatality rate (0.9%/year) was observed from 2006–2016. Smoking among adult Olmsted County residents decreased from 20.4% in 2000 to 9.1% in 2018. CONCLUSIONS A decline in the incidence of aSAH and 30-day case-fatality rate from 1996 to 2016 was observed, as well as an accelerated decline of the fatality rate from 2006 to 2016. These findings confirm and extend the trends reported by prior studies in the same population. The decrease in aSAH in the years studied paralleled a noticeable reduction in the population smoking rates.

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: Polypharmacy is highly prevalent in elderly individuals with chronic conditions, including atrial fibrillation (AF). The impact of polypharmacy on adverse outcomes and on treatment effectiveness in elderly AF patients remains unaddressed. Methods: We studied 338,810 AF patients ≥75 years of age with 1,761,660 active prescriptions [mean (SD), 5.1 (3.8) per patient] enrolled in the MarketScan Medicare Supplemental database in 2007-2015. Polypharmacy was defined as ≥5 active prescriptions at AF diagnosis based on outpatient pharmacy claims. AF treatments (oral anticoagulation, rhythm and rate control) and cardiovascular endpoints (ischemic stroke, bleeding, heart failure) were defined based on inpatient, outpatient and pharmacy claims. Multivariable Cox models were used to estimate associations of polypharmacy with cardiovascular endpoints and the interaction between polypharmacy and AF treatments in relation to cardiovascular endpoints. Results: Prevalence of polypharmacy was 52% (176,007 of 338,810). Patients with polypharmacy had increased risk of major bleeding [hazard ratio (HR) 1.16, 95% confidence interval (CI) 1.12, 1.20] and heart failure (HR 1.33, 95%CI 1.29, 1.36), but not of ischemic stroke (HR 0.96, 95%CI 0.92, 1.00), compared to those not with polypharmacy (Table). Polypharmacy status did not consistently modify the effectiveness of oral anticoagulants. However, rhythm control (vs. rate control) was more effective in preventing heart failure hospitalization in patients not with polypharmacy (HR 0.87, 95%CI 0.76, 0.99) than among those with polypharmacy (HR 0.98, 95%CI 0.91, 1.07, p for interaction = 0.02). Conclusion: Polypharmacy is frequent among elderly patients with AF, associated with adverse outcomes, and potentially affecting the effectiveness of AF treatments. Optimizing management of polypharmacy in elderly AF patients may lead to improved outcomes.

Background: The focus of most existing phenotyping algorithms based on electronic health record (EHR) data has been to accurately identify cases and non-cases of specific diseases. However, a more challenging task is to accurately identify disease incidence, as identifying the first occurrence of disease is more important for efficient and valid clinical and epidemiological research. Moreover, stroke is a challenging phenotype due to diagnosis difficulty and common miscoding. This task generally requires utilization of multiple types of EHR data (e.g., diagnoses and procedure codes, unstructured clinical notes) and a more robust algorithm integrating both natural language processing and machine learning. In this study, we developed and validated an EHR-based classifier to accurately identify stroke incidence among a cohort of atrial fibrillation (AF) patients Methods: We developed a stroke phenotyping algorithm using International Classification of Diseases, Ninth Revision (ICD-9) codes, Current Procedural Terminology (CPT) codes, and expert-provided keywords as model features. Structured data was extracted from Rochester Epidemiology Project (REP) database. Natural Language Processing (NLP) was used to extract and validate keyword occurrence in clinical notes. A window of ±30 days was considered when including/excluding keywords/codes into the input vector. Frequencies of keywords/codes were used as input feature sets for model training. Multiple competing models were trained using various combinations of feature sets and two machine learning algorithms: logistic regression and random forest. Training data were provided by two nurse abstractors and included validated stroke incidences from a previously established atrial fibrillation cohort. Precision, recall, and F-score of the algorithm were calculated to assess and compare model performances. Results: Among 4,914 patients with atrial fibrillation, 1,773 patients were screened. 3,141 patients had no stroke-related codes or keywords and were presumed to be free of stroke during follow-up. Among the screened patients, 740 had validated strokes and 1,033 did not have a stroke based on review of the EHR by trained nurse abstractors. The best performing stroke incidence phenotyping classifier utilized Keywords+ICD-9+CPT features using a random forest classifier, achieving a precision of 0.942, recall of 0.943, and F-score of 0.943. Conclusion: In conclusion, we developed and validated a stroke algorithm that performed well for identifying stroke incidence in an enriched population (AF cohort), which extends beyond the typical binary case/non-case stroke identification problem. Future work will involve testing the generalizability of this algorithm in a general population.

Introduction: Women with atrial fibrillation (AF) experience greater symptomatology, worse quality of life, and have a higher risk of stroke as compared to men, but are less likely to receive rhythm control for the treatment of AF. Whether these differences exist in elderly patients with AF, and whether sex modifies the effectiveness of rhythm versus rate control therapy has not been assessed. Methods: We studied 135,850 men and 139,767 women 75 years or older diagnosed with AF in the MarketScan Medicare database between 2007-2015. Rate control was defined as use of rate control medication or atrioventricular node ablation. Rhythm control was defined by use of anti-arrhythmics, catheter ablation or cardioversion. Participants on both rate and rhythm were coded under rhythm control. We used multivariable logistic and Cox regression models to estimate 1) the association of sex and treatment strategy (within 30-day post AF diagnosis and entire follow-up) and, 2) the association of treatment strategy with incident heart failure, stroke and major bleeding. Results: Men were on average (SD) 82.5 (5.2) years old and women 83.8 (5.6) years, respectively. Women were less likely to receive rhythm control treatment as compared to men in the 30-day post AF diagnosis period (22% vs 27%), (OR 0.91, 95% CI 0.88, 0.94) and over the entire duration of follow-up (28% vs 32%) (HR 0.93, 95% CI 0.90, 0.96). Rhythm (vs. rate) control was associated with a higher risk of heart failure in women [HR 1.41, 95% CI 1.34, 1.49] than in men [HR, 1.21 95% CI 1.15, 1.28] (p for multiplicative interaction < 0.001, Table ). Sex did not modify associations between treatment and incident stroke or major bleeding events. Conclusion: Women aged 75 years and older were less likely to be prescribed rhythm control as compared to men, and experienced higher risk of heart failure than men when receiving rhythm (vs rate) control. Future studies will need to delve into the mechanisms underlying these differences.

Background: The Patient-Centered Outcomes Research Institute (PCORI) funded National Blood Pressure Surveillance System (BP Track) is a new national system that generates quarterly metrics of blood pressure (BP) control and BP-related quality metrics for participating healthcare systems from electronic health record (EHR) data. Methods: Queries against standardized EHR data in the national Patient-Centered Clinical Research Network (PCORnet) Common Data Model format produce a set of quality metrics relevant to improving BP control, including Controlling High BP (NQF 0018) and Improvement in BP (CMS65v7), and eight process measures specific to clinical management and treatment practices for improving BP control ( Table ). The metrics, aggregated overall and by health system are reported back to health systems via user-friendly Tableau dashboards, and allow for observation of metric trends. Results: To date, 19 datamarts have contributed EHR data from 1,177,232 patients who met the eligibility criteria for the BP Control measure and 4,454,729 encounters that included a BP measurement during the measurement period. Average age was 62 years; 10% were young adults (<45 years), 17% were African American, 52% female, 28% had diabetes, 15% had coronary heart disease, and 14% had depression. Results demonstrate substantial opportunity for improvement in overall BP control (60% with BP<140/<90 mmHg, range: 42-72%), and many healthcare processes, including medication intensification (12%, 0.6-22%) and use of fixed dose combination medications (24%, 0-88%, Table ). Conclusion: Major opportunities exist for improving BP control, especially in improving the frequency and quality of BP medication prescribing for patients with high BP. The BP Track National BP Surveillance System will track these metrics, by demographic subgroup and over time, and will generate data that can guide and focus quality improvement initiatives aimed at effective BP management.