The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

How much to purchase? - A cognitive adaptive decision making account

Repeated purchase decisions often violate assumptions of stan-dard economic or rational choice models, such as demonstrat-ing asymmetric or unstable responses to changes in underlyingpolicy, price, or tax variables. I propose a novel frameworkfor how such decisions can be interpreted through the lens of acognitive process model. This provides psychologically inter-pretable characterizations of individuals or population groups.It incorporates mental accounting, hedonic adaptation, confir-mation bias, and the influence of perceived trust and fairness.It shows how sequential experiences and contextual aspectssuch as political affiliation, are mediated by this cognitive pro-cess to produce evolving consumption patterns. This novel ap-proach can account for empirically observed violations of con-ventional choice models. The model is quantitatively fit to ex-perimental data for individual purchase decisions and demon-strates improved descriptive, predictive, and inference capabil-ities. A proof-of-concept analysis using this model to accountfor real world consumption trends is also demonstrated

Perspectives on Cognitive Modeling of Adaptive Behavior

Many experimental and statistical paradigms collect and analyze behavioral data under steady-state assumptions. Such paradigms may have low external validity, since real-world decisions are often made in situations when people are still learning and adapting, or their beliefs and preferences are in a state of flux, or where the decision environment is constantly changing. I focus on experimental and real-world paradigms that represent some form of adaptive behavior. Under such situations, factoring in structural adaptivity into cognitive modeling frameworks can improve their descriptive and predictive performance, and allow us to make superior inferences about the underlying latent cognitive processes. Towards this endeavor, first, a novel probabilistic framework is proposed for representation of heuristic strategies of information search and multi-attribute choice within a model of learning. Second, a novel adaptive reference point mechanism is introduced, and I show how this can be used in a variety of different tasks and applications, and be incorporated into cognitive frameworks to structurally capture the adaptive process. This mechanism provides superior predictive performance along with psychologically meaningful parameter inference in tasks ranging from signal detection, bandit problems, judgments about estimating true values, consumption behavior, probability tracking, and expectation formation. Third, I show how cognitive modeling can be applied to adaptive population behavior in the real world. Real world data is used to make inferences about the latent processes involved in aspects such as the changing nature of cycles of violence, and the impact of tax policies on changing consumption patterns. Incorporating cognitive modeling frameworks and psychological insights to constrain econometric models yields possibly simpler models, but with directly interpretable parameter inferences. Fourth, cognitive modeling approaches are used to design choice architecture frames to create behavioral nudges within a risk allocation paradigm, where people change their behavior based on representational, rather than meaningful changes in their environment