353 research outputs found

    PDB27 HOSPITALIZATIONS WITHIN THE VA AMONG VETERANS WITH DIABETES

    Get PDF

    Genome-wide differentiation in closely related populations: the roles of selection and geographic isolation.

    Get PDF
    Population divergence in geographic isolation is due to a combination of factors. Natural and sexual selection may be important in shaping patterns of population differentiation, a pattern referred to as 'Isolation by Adaptation' (IBA). IBA can be complementary to the well-known pattern of 'Isolation by Distance' (IBD), in which the divergence of closely related populations (via any evolutionary process) is associated with geographic isolation. The barn swallow Hirundo rustica complex comprises six closely related subspecies, where divergent sexual selection is associated with phenotypic differentiation among allopatric populations. To investigate the relative contributions of selection and geographic distance to genome-wide differentiation, we compared genotypic and phenotypic variation from 350 barn swallows sampled across eight populations (28 pairwise comparisons) from four different subspecies. We report a draft whole genome sequence for H. rustica, to which we aligned a set of 9,493 single nucleotide polymorphisms (SNPs). Using statistical approaches to control for spatial autocorrelation of phenotypic variables and geographic distance, we find that divergence in traits related to migratory behavior and sexual signaling, as well as geographic distance together, explain over 70% of genome-wide divergence among populations. Controlling for IBD, we find 42% of genome-wide divergence is attributable to IBA through pairwise differences in traits related to migratory behavior and sexual signaling alone. By (i) combining these results with prior studies of how selection shapes morphological differentiation and (ii) accounting for spatial autocorrelation, we infer that morphological adaptation plays a large role in shaping population-level differentiation in this group of closely related populations. This article is protected by copyright. All rights reserved

    How Does Facilitation in Healthcare Work? Using Mechanism Mapping to Illuminate the Black Box of a Meta-Implementation Strategy

    Get PDF
    BACKGROUND: Healthcare facilitation, an implementation strategy designed to improve the uptake of effective clinical innovations in routine practice, has produced promising yet mixed results in randomized implementation trials and has not been fully researched across different contexts. OBJECTIVE: Using mechanism mapping, which applies directed acyclic graphs that decompose an effect of interest into hypothesized causal steps and mechanisms, we propose a more concrete description of how healthcare facilitation works to inform its further study as a meta-implementation strategy. METHODS: Using a modified Delphi consensus process, co-authors developed the mechanistic map based on a three-step process. First, they developed an initial logic model by collectively reviewing the literature and identifying the most relevant studies of healthcare facilitation components and mechanisms to date. Second, they applied the logic model to write vignettes describing how facilitation worked (or did not) based on recent empirical trials that were selected via consensus for inclusion and diversity in contextual settings (US, international sites). Finally, the mechanistic map was created based on the collective findings from the vignettes. FINDINGS: Theory-based healthcare facilitation components informing the mechanistic map included staff engagement, role clarification, coalition-building through peer experiences and identifying champions, capacity-building through problem solving barriers, and organizational ownership of the implementation process. Across the vignettes, engagement of leaders and practitioners led to increased socialization of the facilitator\u27s role in the organization. This in turn led to clarifying of roles and responsibilities among practitioners and identifying peer experiences led to increased coherence and sense-making of the value of adopting effective innovations. Increased trust develops across leadership and practitioners through expanded capacity in adoption of the effective innovation by identifying opportunities that mitigated barriers to practice change. Finally, these mechanisms led to eventual normalization and ownership of the effective innovation and healthcare facilitation process. IMPACT: Mapping methodology provides a novel perspective of mechanisms of healthcare facilitation, notably how sensemaking, trust, and normalization contribute to quality improvement. This method may also enable more efficient and impactful hypothesis-testing and application of complex implementation strategies, with high relevance for lower-resourced settings, to inform effective innovation uptake

    Reciprocal learning and chronic care model implementation in primary care: results from a new scale of learning in primary care

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Efforts to improve the care of patients with chronic disease in primary care settings have been mixed. Application of a complex adaptive systems framework suggests that this may be because implementation efforts often focus on education or decision support of individual providers, and not on the dynamic system as a whole. We believe that learning among clinic group members is a particularly important attribute of a primary care clinic that has not yet been well-studied in the health care literature, but may be related to the ability of primary care practices to improve the care they deliver.</p> <p>To better understand learning in primary care settings by developing a scale of learning in primary care clinics based on the literature related to learning across disciplines, and to examine the association between scale responses and chronic care model implementation as measured by the Assessment of Chronic Illness Care (ACIC) scale.</p> <p>Methods</p> <p>Development of a scale of learning in primary care setting and administration of the learning and ACIC scales to primary care clinic members as part of the baseline assessment in the ABC Intervention Study. All clinic clinicians and staff in forty small primary care clinics in South Texas participated in the survey.</p> <p>Results</p> <p>We developed a twenty-two item learning scale, and identified a five-item subscale measuring the construct of reciprocal learning (Cronbach alpha 0.79). Reciprocal learning was significantly associated with ACIC total and sub-scale scores, even after adjustment for clustering effects.</p> <p>Conclusions</p> <p>Reciprocal learning appears to be an important attribute of learning in primary care clinics, and its presence relates to the degree of chronic care model implementation. Interventions to improve reciprocal learning among clinic members may lead to improved care of patients with chronic disease and may be relevant to improving overall clinic performance.</p

    Analysis of Muscle and Ovary Transcriptome of Sus scrofa: Assembly, Annotation and Marker Discovery

    Get PDF
    Pig (Sus scrofa) is an important organism for both agricultural and medical purpose. This study aims to investigate the S. scrofa transcriptome by the use of Roche 454 pyrosequencing. We obtained a total of 558 743 and 528 260 reads for the back-leg muscle and ovary tissue each. The overall 1 087 003 reads give rise to 421 767 341 bp total residues averaging 388 bp per read. The de novo assemblies yielded 11 057 contigs and 60 270 singletons for the back-leg muscle, 12 204 contigs and 70 192 singletons for the ovary and 18 938 contigs and 102 361 singletons for combined tissues. The overall GC content of S. scrofa transcriptome is 42.3% for assembled contigs. Alternative splicing was found within 4394 contigs, giving rise to 1267 isogroups or genes. A total of 56 589 transcripts are involved in molecular function (40 916), biological process (38 563), cellular component (35 787) by further gene ontology analyses. Comparison analyses showed that 336 and 553 genes had significant higher expression in the back-leg muscle and ovary each. In addition, we obtained a total of 24 214 single-nucleotide polymorphisms and 11 928 simple sequence repeats. These results contribute to the understanding of the genetic makeup of S. scrofa transcriptome and provide useful information for functional genomic research in future

    Whole Body Mechanics of Stealthy Walking in Cats

    Get PDF
    The metabolic cost associated with locomotion represents a significant part of an animal's metabolic energy budget. Therefore understanding the ways in which animals manage the energy required for locomotion by controlling muscular effort is critical to understanding limb design and the evolution of locomotor behavior. The assumption that energetic economy is the most important target of natural selection underlies many analyses of steady animal locomotion, leading to the prediction that animals will choose gaits and postures that maximize energetic efficiency. Many quadrupedal animals, particularly those that specialize in long distance steady locomotion, do in fact reduce the muscular contribution required for walking by adopting pendulum-like center of mass movements that facilitate exchange between kinetic energy (KE) and potential energy (PE) [1]–[4]. However, animals that are not specialized for long distance steady locomotion may face a more complex set of requirements, some of which may conflict with the efficient exchange of mechanical energy. For example, the “stealthy” walking style of cats may demand slow movements performed with the center of mass close to the ground. Force plate and video data show that domestic cats (Felis catus, Linnaeus, 1758) have lower mechanical energy recovery than mammals specialized for distance. A strong negative correlation was found between mechanical energy recovery and diagonality in the footfalls and there was also a negative correlation between limb compression and diagonality of footfalls such that more crouched postures tended to have greater diagonality. These data show a previously unrecognized mechanical relationship in which crouched postures are associated with changes in footfall pattern which are in turn related to reduced mechanical energy recovery. Low energy recovery was not associated with decreased vertical oscillations of the center of mass as theoretically predicted, but rather with posture and footfall pattern on the phase relationship between potential and kinetic energy. An important implication of these results is the possibility of a tradeoff between stealthy walking and economy of locomotion. This potential tradeoff highlights the complex and conflicting pressures that may govern the locomotor choices that animals make

    Differential Effects of Comorbidity on Antihypertensive and Glucose-Regulating Treatment in Diabetes Mellitus – A Cohort Study

    Get PDF
    BACKGROUND: Comorbidity is often mentioned as interfering with "optimal" treatment decisions in diabetes care. It is suggested that diabetes- related comorbidity will increase adequate treatment, whereas diabetes- unrelated comorbidity may decrease this process of care. We hypothesized that these effects differ according to expected priority of the conditions. METHODS: We evaluated the relationship between comorbidity and treatment intensification in a study of 11,248 type 2 diabetes patients using the GIANTT (Groningen Initiative to Analyse type 2 diabetes Treatment) database. We formed a cohort of patients with a systolic blood pressure >/= 140 mmHg (6,820 hypertensive diabetics), and a cohort of patients with an HbA1c >/= 7% (3,589 hyperglycemic diabetics) in 2007. We differentiated comorbidity by diabetes-related or unrelated conditions and by priority. High priority conditions include conditions that are life- interfering, incident or requiring new medication treatment. We performed Cox regression analyses to assess association with treatment intensification, defined as dose increase, start, or addition of drugs. RESULTS: In both the hypertensive and hyperglycemic cohort, only patients with incident diabetes-related comorbidity had a higher chance of treatment intensification (HR 4.48, 2.33-8.62 (p<0.001) for hypertensives; HR 2.37, 1.09-5.17 (p = 0.030) for hyperglycemics). Intensification of hypertension treatment was less likely when a new glucose-regulating drug was prescribed (HR 0.24, 0.06-0.97 (p = 0.046)). None of the prevalent or unrelated comorbidity was significantly associated with treatment intensification. CONCLUSIONS: Diabetes-related comorbidity induced better risk factor treatment only for incident cases, implying that appropriate care is provided more often when complications occur. Diabetes- unrelated comorbidity did not affect hypertension or hyperglycemia management, even when it was incident or life-interfering. Thus, the observed "undertreatment" in diabetes care cannot be explained by constraints caused by such comorbidity
    corecore