Donna Jo McCloskey

Selective serotonin reuptake inhibitors: measurement of effect on platelet function

Selective serotonin reuptake inhibitors (SSRIs) reduce platelet serotonin and are associated with increased gastrointestinal bleeding, an effect that is enhanced when taken with NSAIDs or aspirin. The best method to evaluate hemorrhagic events in patients taking SSRIs has not been determined. Platelet aggregation, which is not widely available, shows SSRI inhibition of platelet function; we tested whether a platelet function analyzer could detect SSRI inhibition of platelet function. Two groups of outpatients with mood disorders were recruited; each patient was taking a stable dose of either an SSRI or bupropion for at least 6 weeks. They were tested using the platelet function analyzer-100 (PFA-100; Dade International Inc, Miami, Fla) concomitantly with platelet aggregation. Fifty-eight patients were analyzed. We detected significant differences between the groups using aggregation methods with arachidonic acid (aggregation, P = 0.00001; release, P = 0.009) and collagen (aggregation, P = 0.016; release, P = 0.006). The PFA-100 did not detect differences between the groups or results outside the reference range. The PFA-100 does not detect the inhibitory effects of SSRIs on platelet function, but it can be used to direct evaluation of bleeding in a patient taking an SSRI. Abnormal PFA-100 results suggest additional evaluation for von Willebrand disease, other platelet inhibitory medications, or underlying intrinsic platelet dysfunction.

Advancing Symptom Science Through Use of Common Data Elements.

BACKGROUND Use of common data elements (CDEs), conceptually defined as variables that are operationalized and measured in identical ways across studies, enables comparison of data across studies in ways that would otherwise be impossible. Although healthcare researchers are increasingly using CDEs, there has been little systematic use of CDEs for symptom science. CDEs are especially important in symptom science because people experience common symptoms across a broad range of health and developmental states, and symptom management interventions may have common outcomes across populations. PURPOSES The purposes of this article are to (a) recommend best practices for the use of CDEs for symptom science within and across centers; (b) evaluate the benefits and challenges associated with the use of CDEs for symptom science; (c) propose CDEs to be used in symptom science to serve as the basis for this emerging science; and (d) suggest implications and recommendations for future research and dissemination of CDEs for symptom science. DESIGN The National Institute of Nursing Research (NINR)-supported P20 and P30 Center directors applied published best practices, expert advice, and the literature to identify CDEs to be used across the centers to measure pain, sleep, fatigue, and affective and cognitive symptoms. FINDINGS We generated a minimum set of CDEs to measure symptoms. CONCLUSIONS The CDEs identified through this process will be used across the NINR Centers and will facilitate comparison of symptoms across studies. We expect that additional symptom CDEs will be added and the list will be refined in future work. CLINICAL RELEVANCE Symptoms are an important focus of nursing care. Use of CDEs will facilitate research that will lead to better ways to assist people to manage their symptoms.

Use of heparin versus lepirudin flushes to prevent withdrawal occlusion of central venous access devices

Study Objective. To determine whether lepirudin flushes are more effective than heparinized saline in preventing withdrawal occlusion of central venous access devices.

Recommendations of Common Data Elements to Advance the Science of Self‐Management of Chronic Conditions

PURPOSE Common data elements (CDEs) are increasingly being used by researchers to promote data sharing across studies. The purposes of this article are to (a) describe the theoretical, conceptual, and definition issues in the development of a set of CDEs for research addressing self-management of chronic conditions; (b) propose an initial set of CDEs and their measures to advance the science of self-management; and (c) recommend implications for future research and dissemination. DESIGN AND METHODS Between July 2014 and December 2015 the directors of the National Institute of Nursing Research (NINR)-funded P20 and P30 centers of excellence and NINR staff met in a series of telephone calls and a face-to-face NINR-sponsored meeting to select a set of recommended CDEs to be used in self-management research. A list of potential CDEs was developed from examination of common constructs in current self-management frameworks, as well as identification of variables frequently used in studies conducted in the centers of excellence. FINDINGS The recommended CDEs include measures of three self-management processes: activation, self-regulation, and self-efficacy for managing chronic conditions, and one measure of a self-management outcome, global health. CONCLUSIONS The self-management of chronic conditions, which encompasses a considerable number of processes, behaviors, and outcomes across a broad range of chronic conditions, presents several challenges in the identification of a parsimonious set of CDEs. This initial list of recommended CDEs for use in self-management research is provisional in that it is expected that over time it will be refined. Comment and recommended revisions are sought from the research and practice communities. CLINICAL RELEVANCE The use of CDEs can facilitate generalizability of research findings across diverse population and interventions.

The Contributions and Challenges of NINR Centers: Perspectives of Directors

The National Institute of Nursing Researchs (NINR) Research Centers program is an extramural funding approach to increase research capability in nursing science by supporting skilled new investigators and promoting collaboration between groups and across institutions, through shared resources and expertise. The Committee for the Assessment of the National Institutes of Health (NIH) Centers of Excellence Programs (Manning, McGeary, & Estabrook, 2004, p. 1) confirmed the value of Centers in “supporting research that benefits from a multidisciplinary, team-based approach, especially research aimed at understanding complex biomedical systems, and for translating basic scientific discoveries into useful clinical application.” In its over-20-year history, the Centers program has contributed significantly to the advancement of NINRs goals to build research infrastructure, expand research capacity, and increase training opportunities (Grady, 2009). In this article, we draw from the insights of directors of 25 Centers on their challenges and successes, and we share their recommendations to enable current and future Centers to enhance science to support the health of individuals, families, and communities.

Parameters of coagulant and fibrinolytic capacity and activity in postmenopausal women: within-subject variability.

We have analyzed the within-subject variability of a battery of parameters of coagulant and fibrinolytic capacity and activity in postmenopausal women. We observed large differences in within-subject variability among the tests and have demonstrated how such data can be used to estimate the number of times a parameter must be measured to produce a statistically adequate sample.

Evolution of the National Institute of Nursing Research Logic Model for Center Sustainability

BACKGROUND Logic models are tools to evaluate the effectiveness of programs. In 2013, the National Institute of Nursing Research (NINR) Logic Model for Center Sustainability was developed. PURPOSE The purpose of this paper is to describe the process of revision and implementation of the NINR Logic Model across a continuum of NINR Exploratory Centers and Centers of Excellence. METHODS The process for incorporating common data elements for symptom, self-management, biomarker science and precision health in the logic model is outlined. Information about the NINR Logic Model was gleaned from the National Institutes of Health Reporter, annual NINR Center Directors meetings, and from individual Center Directors. FINDINGS Centers utilized the model for funding applications and to guide Core administration, evaluation, Center sustainability, and/or other Center metrics. DISCUSSION The revised NINR Logic Model for Center Sustainability can be a useful tool for planning and implementing center activities for center impact and sustainability.

Feasibility of Combining Common Data Elements Across Studies to Test a Hypothesis

PURPOSE The purpose of this article is to describe the outcomes of a collaborative initiative to share data across five schools of nursing in order to evaluate the feasibility of collecting common data elements (CDEs) and developing a common data repository to test hypotheses of interest to nursing scientists. This initiative extended work already completed by the National Institute of Nursing Research CDE Working Group that successfully identified CDEs related to symptoms and self-management, with the goal of supporting more complex, reproducible, and patient-focused research. DESIGN Two exemplars describing the groups efforts are presented. The first highlights a pilot study wherein data sets from various studies by the represented schools were collected retrospectively, and merging of the CDEs was attempted. The second exemplar describes the methods and results of an initiative at one school that utilized a prospective design for the collection and merging of CDEs. METHODS Methods for identifying a common symptom to be studied across schools and for collecting the data dictionaries for the related data elements are presented for the first exemplar. The processes for defining and comparing the concepts and acceptable values, and for evaluating the potential to combine and compare the data elements are also described. Presented next are the steps undertaken in the second exemplar to prospectively identify CDEs and establish the data dictionaries. Methods for common measurement and analysis strategies are included. FINDINGS Findings from the first exemplar indicated that without plans in place a priori to ensure the ability to combine and compare data from disparate sources, doing so retrospectively may not be possible, and as a result hypothesis testing across studies may be prohibited. Findings from the second exemplar, however, indicated that a plan developed prospectively to combine and compare data sets is feasible and conducive to merged hypothesis testing. CONCLUSIONS Although challenges exist in combining CDEs across studies into a common data repository, a prospective, well-designed protocol for identifying, coding, and comparing CDEs is feasible and supports the development of a common data repository and the testing of important hypotheses to advance nursing science. CLINICAL RELEVANCE Incorporating CDEs across studies will increase sample size and improve data validity, reliability, transparency, and reproducibility, all of which will increase the scientific rigor of the study and the likelihood of impacting clinical practice and patient care.