Nursing sensitive outcomes in patients with rheumatoid arthritis: A systematic literature review

© 2017 Elsevier Ltd Background Although rheumatology nursing has been shown to be effective in managing patients with rheumatoid arthritis, patient outcomes sensitive to nursing interventions (nursing sensitive outcomes) have not been systematically studied. Objectives The objective of this study was to identify and delineate relevant patient outcomes measured in studies that reported nursing interventions in patients with rheumatoid arthritis. Design A systematic search was conducted from 1990 to 2016. Inclusion criteria were (i) patients with rheumatoid arthritis, (ii) adult population age ≥16 years, (iii) nurse as part of the care team or intervention delivery, (iv) primary research only, (v) English language, and (vi) quantitative studies with nursing sensitive outcomes. Data sources Medline, CINAHL, Ovid nursing, Cochrane library and PsycINFO databases were searched for relevant studies. Review methods Using the predetermined inclusion/exclusion criteria, nine reviewers working in pairs assessed the eligibility of the identified studies based on titles and abstracts. Papers meeting the inclusion criteria were retrieved and full texts were further assessed. Critical Appraisal Skills Programme tools were used to assess the quality of the included studies. Data on nursing sensitive outcomes were extracted independently by two reviewers. The Outcome Measures in Rheumatology comprehensive conceptual framework for health was used to contextualise and present findings. Results Of the 820 articles retrieved, 7 randomised controlled trials and 3 observational studies met the inclusion criteria. Seventeen nursing sensitive outcomes were identified (disease activity, clinical effects, pain, early morning stiffness duration, fatigue, patient safety issues, function, knowledge, patient satisfaction, confidence in care received, mental health status, self-efficacy, patient attitude/perception of ability to control arthritis, quality of life, health utility, health care resources, death). These fitted into 10 health intervention domains in keeping with the pre-specified conceptual framework for health: disease status, effectiveness, safety, function, knowledge, satisfaction, psychological status, quality of life, cost, death. A total of 59 measurement instruments were identified comprising patient reported outcome measures (n = 31), and biologic measures and reports (n = 28). Conclusions This review is notable in that it is the first to have identified, and reported, a set of multidimensional outcome measures that are sensitive to nursing interventions in rheumatology specifically. Further research is required to determine a core set of outcomes to be used in all rheumatology nursing intervention studies

Assessing road effects on bats: the role of landscape, road features, and bat activity on road-kills

Recent studies suggest that roads can significantly impact bat populations. Though bats are one of the most threatened groups of European vertebrates, studies aiming to quantify bat mortality and determine the main factors driving it remain scarce. Between March 16 and October 31 of 2009, we surveyed road-killed bats daily along a 51-km-long transect that incorporates different types of roads in southern Portugal. We found 154 road-killed bats of 11 species. The two most common species in the study area, Pipistrellus kuhlii and P. pygmaeus, were also the most commonly identified road-kill, representing 72 % of the total specimens collected. About two-thirds of the total mortality occurred between mid July and late September, peaking in the second half of August. We also recorded casualties of threatened and rare species, including Miniopterus schreibersii, Rhinolophus ferrumequinum, R. hipposideros, Barbastella barbastellus, and Nyctalus leisleri. These species were found mostly in early autumn, corresponding to the mating and swarming periods. Landscape features were the most important variable subset for explaining bat casualties. Road stretches crossing or in the vicinity of high-quality habitats for bats—including dense Mediterranean woodland (‘‘montado’’) areas, water courses with riparian gallery, and water reservoirs—yielded a significantly higher number of casualties. Additionally, more roadkilled bats were recorded on high-traffic road stretches with viaducts, in areas of higher bat activity and near known roosts

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose.

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D

Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin

Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loc

Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function

BACKGROUND: Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function. METHODS: A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function. RESULTS: The discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue. CONCLUSION: The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies. FUNDING: For detailed information per study, see Acknowledgments.This work was supported by a grant from the US National Heart, Lung, and Blood Institute (N01-HL-25195; R01HL 093328 to RSV), a MAIFOR grant from the University Medical Center Mainz, Germany (to PSW), the Center for Translational Vascular Biology (CTVB) of the Johannes Gutenberg-University of Mainz, and the Federal Ministry of Research and Education, Germany (BMBF 01EO1003 to PSW). This work was also supported by the research project Greifswald Approach to Individualized Medicine (GANI_MED). GANI_MED was funded by the Federal Ministry of Education and Research and the Ministry of Cultural Affairs of the Federal State of Mecklenburg, West Pomerania (contract 03IS2061A). We thank all study participants, and the colleagues and coworkers from all cohorts and sites who were involved in the generation of data or in the analysis. We especially thank Andrew Johnson (FHS) for generation of the gene annotation database used for analysis. We thank the German Center for Cardiovascular Research (DZHK e.V.) for supporting the analysis and publication of this project. RSV is a member of the Scientific Advisory Board of the DZHK. Data on CAD and MI were contributed by CARDIoGRAMplusC4D investigators. See Supplemental Acknowledgments for consortium details. PSW, JFF, AS, AT, TZ, RSV, and MD had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis

Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting.

OBJECTIVE: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. METHODS: We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. RESULTS: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p [BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p [BI] = 4.4 × 10-10; p [SSBI] = 1.2 × 10-4), diabetes (p [BI] = 1.7 × 10-8; p [SSBI] = 2.8 × 10-3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10-24), and MRI-defined white matter hyperintensity burden (p [BI] = 1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. CONCLUSION: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI

Acute-phase serum amyloid a in osteoarthritis: regulatory mechanism and proinflammatory properties

OBJECTIVE: To determine if serum amyloid A (A-SAA) could be detected in human osteoarthritic (OA) joints and further clarify if high A-SAA level in joints result from a local production or from a diffusion process from abnormally elevated plasma concentration. Regulatory mechanism of A-SAA expression and its pro-inflammatory properties were also investigated. METHODS: A-SAA levels in serum and synovial fluid of OA (n = 29) and rheumatoid arthritis (RA) (n = 27) patients were measured and compared to matched-healthy volunteers (HV) (n = 35). In vitro cell cultures were performed on primary joint cells provided from osteoarthritis patients. Regulatory mechanisms were studied using Western-blotting, ELISA and lentiviral transfections. RESULTS: A-SAA was statistically increased in OA plasma patients compared to HV. Moreover, A-SAA level in OA plasma and synovial fluid increased with the Kellgren & Lauwrence grade. For all OA and RA patients, A-SAA plasma level was higher and highly correlated with its corresponding level in the synovial fluid, therefore supporting that A-SAA was mainly due to the passive diffusion process from blood into the joint cavity. However, A-SAA expression was also observed in vitro under corticosteroid treatment and/or under IL-1beta stimuli. A-SAA expression was down-regulated by PPAR-γ agonists (genistein and rosiglitazone) and up-regulated by TGF-β1 through Alk1 (Smad1/5) pathway. RhSAA induced proinflammatory cytokines (IL-6, IL-8, GRO-α and MCP-1) and metalloproteinases (MMP-1, MMP-3 and MMP-13) expression in FLS and chondrocytes, which expression was downregulated by TAK242, a specific TLR4 inhibitor. CONCLUSION: Systemic or local A-SAA expression inside OA joint cavity may play a key role in inflammatory process seen in osteoarthritis, which could be counteracted by TLR4 inhibition