Citations

Introduction: Shared decision making (SDM) incorporates patient and physician values and preferences into treatment selection. While multiple therapeutic options are available for stroke prevention in atrial fibrillation (AF), few studies have examined factors associated with SDM regarding choice of antithrombotic strategy. Methods: We evaluated survey data from 1006 patients with new-onset AF enrolled at 56 sites participating in a substudy of the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT II), an outpatient AF registry in the US. Patients were asked: “When choosing your blood thinner(s), who made this treatment decision?”, and SDM was defined as a response of “equally me and my healthcare provider (HCP)”, “mostly me” or “entirely me”, while no SDM was defined as a response of “mostly my HCP” or “entirely my HCP”. Multivariable logistic regression models evaluated associations between 13 patient-level factors, self-reported understanding of treatment options, and SDM for antithrombotic therapy. Results: Most patients allowed their HCP to make the therapeutic decisions on antithrombotic strategy, with 246 (24.5%) reporting SDM. Patients reporting SDM were more often female (47.2% vs. 40.5%) and were more frequently insured by Medicare (40.2% vs. 34.5%) than patients reporting no SDM. Among patients taking warfarin, median time in therapeutic range was higher among patients reporting SDM than among those not reporting SDM. In multivariable models, chronic obstructive pulmonary disease was associated with lower odds of SDM while self-reported understanding of blood thinner options was associated with higher odds of SDM (Table). Conclusion: One in four patients in an outpatient AF registry reported that their current antithrombotic strategy was the result of a shared decision making process. Additional work is need to determine whether patient-reported SDM is associated with medication adherence and outcomes of therapy.

Introduction: Accurately balancing risks of interventional treatment and intracranial hemorrhage (ICH) in the untreated course of unruptured brain arteriovenous malformation (uBAVM) patients is critical for optimal management. Observational studies of uBAVM afford an opportunity to address important gaps and previous criticisms of randomized data to help guide treatment decisions and assess long-term risk/benefit ratio. We previously published an individual patient data meta-analysis (IPDMA) in 4 MARS cohorts and identified ICH presentation and increasing age as significant predictors of ICH during follow-up, but was not powered to detect predictors in those with uBAVM. Thus, the goals of this project are to identify risk factors for ICH in uBAVMs, to estimate the risk with precision, and to create personalized, risk-prediction models. Methods: MARS is an international, multi-center study of 11 cohorts with target enrollment of 4,500 uBAVM patients ascertained through population-based or referral-based studies. We are harmonizing both retrospective and prospective data, including clinical, lifestyle, imaging, and angiographic factors. Treatments, complications, and functional outcomes (physician and patient-reported) will be updated annually between 2018-2022. We propose to: 1) identify predictors of outcome in uBAVMs using IPDMA; 2) test whether long-term outcomes differ by treatment using statistical approaches for causal inference and unbiased estimates; 3) compare treatment outcomes in randomized and non-randomized data to address generalizability; and 4) validate models and provide a novel tool for calculating individualized risks. Eligible sites have: a) prior BAVM publications; b) data from a minimum of 100 uBAVM patients; c) agree to random outcome adjudication; and d) agree to MARS data sharing policy. Discussion: The NIH-funded MARS consortium will provide important and comprehensive characterization of the untreated and treated course of uBAVMs, using large observational datasets and sophisticated epidemiological approaches. The data and models generated will be a useful resource for decision-making. We welcome participation from eligible sites with longitudinal data on uBAVM patients

Background: High blood pressure (BP), particularly in mid-life, increases the risk for late-life cognitive impairment and dementia (CID). The extent to which Blacks’ and Hispanics’ worse BP control starting in young adulthood contributes to their greater risk of CID compared to Whites is uncertain. Objective: To describe a pooled, multi-ethnic cohort created to determine the associations between BP levels over the life course and CID risk in Blacks, Hispanics, and Whites. Methods: We pooled individual-level data from 35,473 adults (22.6% Blacks, 8.1% Hispanics, 67.3% Whites, 2% Other) with baseline age ≥18 and cognitive assessments across 6 longitudinal cohorts in the United States from 1971 to 2016: Atherosclerosis Risk in Communities Study (ARIC), Coronary Artery Risk Development in Young Adults Study (CARDIA), Cardiovascular Health Study (CHS), Framingham Offspring Study (FOS), Multi-Ethnic Study of Atherosclerosis (MESA), and Northern Manhattan Study (NOMAS). We harmonized cognitive tests across studies into 3 factors representing global cognitive performance, executive function, and memory using statistically appropriate confirmatory factor analysis. Mean (SD) follow up was 17.1 (10.9) years. Results: The mean (SD) baseline age was 54.3 (16.4) years and 19554 (55.1%) participants were female (Table). There were 3193 (9.0%) first incident strokes (2651 ischemic, 348 hemorrhagic, and 117 other or undetermined type) and 15147 (42.7%) deaths. The Table presents mean BPs at the first and last visits by cohort and the pooled sample. From the initial to the last assessment, mean global cognition decreased over time (p<0.001), as did mean executive function (p<0.001) and mean memory scores (p<0.001) in the pooled sample. Conclusion: This will be the first comprehensive, large investigation of the association of BP levels from young adulthood to late-life and CID risk in Blacks, Hispanics, and Whites.

Branchial anomalies are common cervical pathologic entities encountered in the field of otolaryngology and are typical in the pediatric and young adult populations. In most cases, these anomalies present as a cyst, sinus, or fistula in a rather stereotypical fashion. When a branchial anomaly deviates from the classic presentation, an improper diagnosis and inadequate management are more likely to occur, leading to an increased recurrence rate. We present a case of a 6-year-old girl with an incidental finding of a right posterior oropharyngeal wall mass, distinctly separate from the tonsillar fossa, which was found on pathologic analysis to be a branchial cleft anomaly. The theories regarding the pathogenesis of branchial anomalies are presented, along with other cases of atypical branchial anomalies.

Background: Proteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a “virtual proteomic” approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals. Methods: We used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651). Results: In the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate q<0.1. Among these, 13 associations involved lipid (n=7) or atherosclerosis (n=6) phenotypes. We tested each association for validation in MDCS using directly measured protein levels. At Bonferroni-adjusted significance thresholds, levels of apolipoprotein E isoforms were associated with hyperlipidemia, and circulating C-type lectin domain family 1 member B and platelet-derived growth factor receptor-β predicted subclinical atherosclerosis. Odds ratios for carotid atherosclerosis were 1.31 (95% CI, 1.08–1.58; P =0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66–0.94; P =0.008) per 1-SD increment in platelet-derived growth factor receptor-β. Conclusions: We demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.