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Background Opioid analgesics are among the most commonly prescribed medications in the United States. Opioids are useful in the management of pain, but their use can also adversely affect patients. However, studies reporting patterns of adverse events due to use of opioid analgesics in men and women are still scarce. Understanding the individual characteristics affecting response to opioids may allow clinicians to better individualize treatments. In this study, we investigated sex differences in the patterns of adverse events as a result of opioid use. Methods We used data from 8,457 patients participating in the Mayo Clinic Biobank “Right Drug, Right Dose, Right Time (RIGHT protocol)” study of pre‐emptive genotyping who were prescribed at least one of four opioid medications (codeine, tramadol, hydrocodone, or oxycodone) between 01/01/2004 and 12/31/2017. Adverse events due to use of these medications were collected from the allergy section in each patient’s electronical medical record, and were organized into four Medical Dictionary for Regulatory Activities (MedDRA) categories: gastrointestinal (e.g. nausea, vomiting), skin and subcutaneous tissue (e.g. rash, itching), psychiatric (e.g. anxiety, hallucinations), and nervous system (e.g. headache, dizziness). We modeled sex differences in the risk of adverse events by each opioid, and sex differences in the risk of each adverse event due to any opioid using logistic regression adjusted for age, race, ethnicity, and body mass index (BMI). Results Participants with at least one opioid prescription were 60.8% female, mostly white (94.2%) and non‐Hispanic (98.9%). Women (relative to men) were younger (median = 61.6 vs. 69.1, respectively), had lower BMI (median = 27.4 vs. 28.9), and were prescribed more codeine (18.8% vs. 15.5%). Overall, 456 (5.4%) persons had a note in the allergy section of their medical record indicating a problem with an opioid medication. Women were more likely than men to have a note in the allergy section referring to at least one opioid (6.6% and 3.5%, respectively; p < 0.001). In addition, among participants who had at least one note related to opioid use in their allergy section, women were more likely to have notes regarding gastrointestinal complications (OR [95% CI] = 2.07 [1.3 – 3.2], p = 0.002), but less likely to have notes regarding psychiatric issues (OR [95% CI] = 0.30 [0.2 – 0.5], p < 0.001). Conclusion Women were more likely than men to experience adverse events due to use of codeine, tramadol, hydrocodone, and oxycodone. In addition, the types of adverse reactions differed between men and women. These data suggest that further studies are needed to ensure that both men and women have optimal responses to opioid medications. Support or Funding Information This work was supported by the Mayo Clinic Specialized Center of Research Excellent on Sex Differences, the Mayo Clinic Center for Individualized Medicine, the Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, and the National Institutes of Health grants [U19 GM61388 (The Pharmacogenomics Research Network), R01 GM28157, U01 HG005137, R01 GM125633, R01 AG034676 (The Rochester Epidemiology Project)], and [U01 HG06379 and U01 HG06379 Supplement (The Electronic Medical Record and Genomics (eMERGE) Network)].

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: 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: 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.

Background: Multimorbidity is common in atrial fibrillation (AF); however, the impact of the number and type of comorbid conditions on death and hospitalizations is uncertain. Methods: The prevalence of 17 chronic conditions was obtained in 1430 patients with incident AF from 2000-2010 from Olmsted County, MN. Chronic conditions were ascertained electronically prior to AF and were classified into 3 groups: cardiovascular (CV), other physical, and mental. All hospitalizations and deaths were obtained through 12/31/2014. Associations of the number and type of condition and each individual condition with hospitalizations and death were determined using Andersen-Gill and Cox regression, respectively. Results: Among the 1430 patients with AF (median age 76 years, 48.6% men), the mean (SD) number of chronic conditions was 4.7 (2.7). A total of 4496 hospitalizations and 812 deaths occurred over a mean (SD) follow-up of 5.4 (4.1) years. An increase in the number of conditions of each type was associated with increased risks of death and hospitalizations (Table). Mental conditions (which included depression, anxiety, dementia, schizophrenia, and substance abuse) exhibited the strongest association with death, whereas other physical conditions exhibited the strongest association with hospitalizations. Individual predictors of death included heart failure (HF), hypertension, chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), depression, dementia, and substance abuse. Predictors of hospitalizations included HF, coronary artery disease, diabetes, COPD, CKD, arthritis, osteoporosis, and substance abuse. Conclusions: Patients with AF have many comorbid conditions which are associated with death and hospitalizations. Although conditions of each type were associated with outcomes, mental conditions exhibited strongest association with death. These data highlight the importance of management of not only CV comorbidities but other physical and mental comorbidities in patients with AF.

Background As the population with cardiovascular disease ages, geriatric conditions are of increasing relevance. A possible geriatric prognostic indicator may be a fall risk score, which is mandated by The Joint Commission to be measured on all hospitalized patients. The prognostic value of a fall risk score on outcomes after dismissal is not well known. Thus, we aimed to determine whether a fall risk score is associated with death and hospital readmissions in patients with a recent incident cardiovascular disease event. Methods and Results In this retrospective cohort study, Olmsted County, MN patients with incident heart failure, myocardial infarction, or atrial fibrillation between August 1, 2005, and December 31, 2011, who were hospitalized within 180 days after the event were studied. Fall risk was measured by the Hendrich II fall risk model. Patients were followed for death or readmission within 30 days or 1 year. Among 2456 hospitalized patients with recent incident cardiovascular disease (549 heart failure, 784 myocardial infarction, 1123 atrial fibrillation; mean [SD] age, 71 [15] years; 55% men), the fall risk score was high in 22% of patients and moderate in 38%. The risk of death was increased if the fall risk score was increased, independent of age and comorbidities (moderate hazard ratio, 1.51; 95% CI, 1.09–2.08; high hazard ratio, 3.49; 95% CI, 2.52–4.85). Similarly, the risk of 30-day readmissions was substantially increased with a greater fall risk score (moderate hazard ratio, 1.29; 95% CI, 1.03–1.62; high hazard ratio, 1.63; 95% CI, 1.23–2.15). Results were similar for readmissions within 1 year. Conclusions More than half of hospitalized patients with recent incident cardiovascular disease have an elevated fall risk score, which is associated with an increased risk in readmissions and death. These results delineate an approach for risk stratification and management that may prevent readmissions and improve survival.

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

Objectives To characterize the individual and combined effects of multimorbidity and functional limitation on healthcare use and mortality in a large, community cohort of individuals with heart failure (HF). Design Prospective cohort study. Setting Eleven southeastern Minnesota counties. Participants Individuals (mean age 74, 54% male) with a first‐ever HF code ( International Classification of Diseases, Ninth Revision code 428 or Tenth Revision code I50) between January 1, 2013 and March 31, 2016 (N=2,692). Measurements Eight activities of daily living measured using a survey on a Likert scale (1=without any difficulty, 5=unable to do; median=8). Participants with a score greater than 8 were categorized as having functional limitation. Multimorbidity was defined as having 2 or more noncardiac comorbidities. Results Twenty‐five percent of participants had neither multimorbidity nor functional limitation, 35% had multimorbidity, 9% had functional limitation, and 31% had both. After adjustment, participants with multimorbidity and functional limitation had greater risks of all outcomes (death: hazard ratio (HR)=4.92, 95% confidence interval (CI)=3.03–8.00; emergency department (ED) visit: HR=3.67, 95% CI=2.94–4.59; hospitalization: HR=3.66, 95% CI=2.85–4.70; outpatient visit: HR=1.73, 95% CI=1.52–1.96) than those with neither. Participants with functional limitation alone had greater risks of death (HR=4.84, 95% CI=2.78–8.43), ED visits (HR=2.35, 95% CI=1.75–3.16), and hospitalizations (HR=2.10, 95% CI=1.52–2.88) but not outpatient visits. Those with multimorbidity alone had similar risks of ED visits and hospitalizations as those with functional limitation alone but were more likely to have outpatient visits (HR=1.50, 95% CI=1.34–1.67). Conclusion Individuals with both multimorbidity and functional limitation have the highest risk of death and healthcare use. Individuals with only functional limitation have similar rates of hospitalizations and ED visits as those with only multimorbidity, underscoring the need to consider both when managing individuals with HF.

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