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

Introduction Population-level screening has been shown to reduce the incidence and mortality of colorectal cancer (CRC). Unfortunately, adherence to screening recommendations among eligible US adults remains below national goals. A relatively new non-invasive screening modality, the Food and Drug Administration–approved multi-target stool DNA (mt-sDNA) assay (commercialised as Cologuard), which combines the detection of haemoglobin and DNA abnormalities, has been completed by more than 3 million individuals. Given mt-sDNA’s recent availability, the effectiveness of mt-sDNA screening with respect to CRC incidence and mortality reduction has not yet been established. Methods and analysis Through an academic–industry collaboration, a prospective cohort study (Voyage) was designed with an initial enrolment target of 150 000 individuals with mt-sDNA ordered by their healthcare provider for CRC screening. Consented participants will be asked to complete a baseline questionnaire to collect sociodemographic and health information. Additional questionnaires will be provided after 1 year, and every 3 years thereafter, to collect data regarding CRC screening follow-up in order to estimate rates of CRC incidence and other health outcomes. Linkage to the National Death Index will be used to estimate mortality rates. Ethics and dissemination The Voyage study will be conducted in accordance with international guidelines and local regulatory requirements and laws. Data will be stored and retained at Mayo Clinic. Only limited data elements required for research purposes will be transmitted between Mayo Clinic and Exact Sciences Laboratories. Results of the Voyage study will be disseminated through scientific presentations and publications. Trial registration number NCT04124406.

Background. Despite extensive evaluation processes to determine candidacy for kidney transplantation, variability in graft failure exists. The role of patient socioeconomic status (SES) in transplantation outcomes is poorly understood because of limitations of conventional SES measures. Methods. This population-based retrospective cohort study assessed whether a validated objective and individual-level housing-based SES index (HOUSES) would serve as a predictive tool for graft failure in patients (n = 181) who received a kidney transplant in Olmsted County, MN (January 1, 1998 to December 8, 2016). Associations were assessed between HOUSES (quartiles: Q1 [lowest] to Q4 [highest]) and graft failure until last follow-up date (December 31, 2016) using Cox proportional hazards. The mean age (SD) was 46.1 (17.2) years, 109 (60.2%) were male, 113 (62.4%) received a living kidney donor transplant, and 40 (22.1%) had a graft failure event. Results. Compared with Q1, patients with higher HOUSES (Q2–Q4) had significantly lower graft failure rates (adjusted hazard ratio, 0.47; 95% confidence interval, 0.24-0.92; P < 0.029), controlling for age, sex, race, previous kidney transplantation, and donor type. Conclusions. Although criteria for kidney transplant recipients are selective, patients with higher HOUSES had lower graft failure rates. Thus, HOUSES may enable transplantation programs to identify a target group for improving kidney transplantation outcomes.

Purpose The Mayo Clinic Biobank was established to provide a large group of patients from which comparison groups (ie, controls) could be selected for case–control studies, to create a prospective cohort with sufficient power for common outcomes and to support electronic health record (EHR) studies. Participants A total of 56 862 participants enrolled (21% response rate) into the Mayo Clinic Biobank from Rochester, Minnesota (77%, n=43 836), Jacksonville, Florida (18%, n=10 368) and La Crosse, Wisconsin (5%, n=2658). Participants were all Mayo Clinic patients, 18 years of age or older and US residents. Findings to date Overall, 43% of participants were 65 years of age or older and female participants were more frequent (59%) than males at all sites. Most participants resided in the Upper Midwest regions of the USA (Minnesota, Iowa, Illinois or Wisconsin), Florida or Georgia. Self-reported race among Biobank participants was 90% white. Here we provide examples of the types of studies that have successfully utilised the resource, including (1) investigations of the population itself, (2) provision of controls for case–control studies, (3) genotype-driven research, (4) EHR-based research and (5) prospective recruitment to other studies. Over 270 projects have been approved to date to access Biobank data and/or samples; over 200 000 sample aliquots have been approved for distribution. Future plans The data and samples in the Mayo Clinic Biobank can be used for various types of epidemiological and clinical studies, especially in the setting of case–control studies for which the Biobank samples serve as control samples. We are planning cohort studies with additional follow-up and acquisition of genetic information on a large scale.

Objective: To understand the interaction of multimorbidity and functional limitations in determining health-care utilization and survival in older adults. Methods: Olmsted County, Minnesota, residents aged 60–89 years in 2005 were categorized into four cohorts based on the presence or absence of multimorbidity (≥3 chronic conditions from a list of 18) and functional limitations (≥1 limitation in an activity of daily living from a list of 9), and were followed through December 31, 2016. Andersen–Gill and Cox regression estimated hazard ratios (HRs) for emergency department (ED) visits, hospitalizations, and death using persons with neither multimorbidity nor functional limitations as the reference (interaction analyses). Results: Among 13,145 persons, 34% had neither multimorbidity nor functional limitations, 44% had multimorbidity only, 4% had functional limitations only, and 18% had both. Over a median follow-up of 11 years, 5906 ED visits, 2654 hospitalizations, and 4559 deaths occurred. Synergistic interactions on an additive scale of multimorbidity and functional limitations were observed for all outcomes; however, the magnitude of the interactions decreased with advancing age. The HR (95% confidence interval) for death among persons with both multimorbidity and functional limitations was 5.34 (4.40–6.47) at age 60–69, 4.16 (3.59–4.83) at age 70–79, and 2.86 (2.45–3.35) at age 80–89 years. Conclusion: The risk of ED visits, hospitalizations, and death among persons with both multimorbidity and functional limitations is greater than additive. The magnitude of the interaction was strongest for the youngest age group, highlighting the importance of interventions to prevent and effectively manage multimorbidity and functional limitations early in life.