Conceptualising a model to guide nursing and midwifery in the community guided by an evidence review

Background: Successful models of nursing and midwifery in the community delivering healthcare throughout the lifespan and across a health and illness continuum are limited, yet necessary to guide global health services. Primary and community health services are the typical points of access for most people and the location where most care is delivered. The scope of primary healthcare is complex and multifaceted and therefore requires a practice framework with sound conceptual and theoretical underpinnings. The aim of this paper is to present a conceptual model informed by a scoping evidence review of the literature. Methods: A scoping evidence review of the literature was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. Databases included CINAHL, MEDLINE, PsycINFO and SocINDEX using the EBSCO platform and the Cochrane Library using the keywords: model, nursing, midwifery, community, primary care. Grey literature for selected countries was searched using the Google ‘advanced’ search interface. Data extraction and quality appraisal for both empirical and grey literature were conducted independently by two reviewers. From 127 empirical and 24 non-empirical papers, data extraction parameters, in addition to the usual methodological features, included: the nature of nursing and midwifery; the population group; interventions and main outcomes; components of effective nursing and midwifery outcomes. Results: The evidence was categorised into six broad areas and subsequently synthesised into four themes. These were not mutually exclusive: (1) Integrated and Collaborative Care; (2) Organisation and Delivery of Nursing and Midwifery Care in the Community; (3) Adjuncts to Nursing Care and (4) Overarching Conceptual Model. It is the latter theme that is the focus of this paper. In essence, the model depicts a person/client on a lifespan and preventative-curative trajectory. The health related needs of the client, commensurate with their point position, relative to both trajectories, determines the nurse or midwife intervention. Consequently, it is this need, that determines the discipline or speciality of the nurse or midwife with the most appropriate competencies. Conclusion: Use of a conceptual model of nursing and midwifery to inform decision-making in primary/community based care ensures clinical outcomes are meaningful and more sustainable. Operationalising this model for nursing and midwifery in the community demands strong leadership and effective clinical governance

The Role of Practice Research Networks (PRN) in the Development and Implementation of Evidence: The Northern Improving Access to Psychological Therapies PRN Case Study

Practice research networks (PRNs) can support the implementation of evidence based practice in routine services and generate practice based evidence. This paper describes the structure, processes and learning from a new PRN in the Improving Access to Psychological Therapies programme in England, in relation to an implementation framework and using one study as a case example. Challenges related to: ethics and governance processes; communications with multiple stakeholders; competing time pressures and linking outcome data. Enablers included: early tangible outputs and impact; a collaborative approach; engaging with local research leads; clarity of processes; effective dissemination; and committed leadership

Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants with Treatment Resistance in Schizophrenia

Importance: About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective: To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants: Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10501) and individuals with non-TRS (n = 20325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures: GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results: The study included a total of 85490 participants (48635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P =.001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P =.04). Conclusions and Relevance: In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome

Conceptualising a model to guide nursing and midwifery in the community guided by an evidence review

Background: Successful models of nursing and midwifery in the community delivering healthcare throughout the lifespan and across a health and illness continuum are limited, yet necessary to guide global health services. Primary and community health services are the typical points of access for most people and the location where most care is delivered. The scope of primary healthcare is complex and multifaceted and therefore requires a practice framework with sound conceptual and theoretical underpinnings. The aim of this paper is to present a conceptual model informed by a scoping evidence review of the literature. Methods: A scoping evidence review of the literature was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. Databases included CINAHL, MEDLINE, PsycINFO and SocINDEX using the EBSCO platform and the Cochrane Library using the keywords: model, nursing, midwifery, community, primary care. Grey literature for selected countries was searched using the Google 'advanced' search interface. Data extraction and quality appraisal for both empirical and grey literature were conducted independently by two reviewers. From 127 empirical and 24 non-empirical papers, data extraction parameters, in addition to the usual methodological features, included: the nature of nursing and midwifery; the population group; interventions and main outcomes; components of effective nursing and midwifery outcomes. Results: The evidence was categorised into six broad areas and subsequently synthesised into four themes. These were not mutually exclusive: (1) Integrated and Collaborative Care; (2) Organisation and Delivery of Nursing and Midwifery Care in the Community; (3) Adjuncts to Nursing Care and (4) Overarching Conceptual Model. It is the latter theme that is the focus of this paper. In essence, the model depicts a person/client on a lifespan and preventative-curative trajectory. The health related needs of the client, commensurate with their point position, relative to both trajectories, determines the nurse or midwife intervention. Consequently, it is this need, that determines the discipline or speciality of the nurse or midwife with the most appropriate competencies. Conclusion: Use of a conceptual model of nursing and midwifery to inform decision-making in primary/community based care ensures clinical outcomes are meaningful and more sustainable. Operationalising this model for nursing and midwifery in the community demands strong leadership and effective clinical governance.Department of Health, Irelan

A chemical genetic approach identifies piperazine antipsychotics as promoters of CNS neurite growth on inhibitory substrates

Injury to the central nervous system (CNS) can result in lifelong loss of function due in part to the regenerative failure of CNS neurons. Inhibitory proteins derived from myelin and the astroglial scar are major barriers for the successful regeneration of injured CNS neurons. Previously, we described the identification of a novel compound, F05, which promotes neurite growth from neurons challenged with inhibitory substrates in vitro, and promotes axonal regeneration in vivo (Usher et al., 2010). To identify additional regeneration-promoting compounds, we used F05-induced gene expression profiles to query the Broad Institute Connectivity Map, a gene expression database of cells treated with >1300 compounds. Despite no shared chemical similarity, F05-induced changes in gene expression were remarkably similar to those seen with a group of piperazine phenothiazine antipsychotics (PhAPs). In contrast to antipsychotics of other structural classes, PhAPs promoted neurite growth of CNS neurons challenged with two different glial derived inhibitory substrates. Our pharmacological studies suggest a mechanism whereby PhAPs promote growth through antagonism of calmodulin signaling, independent of dopamine receptor antagonism. These findings shed light on mechanisms underlying neurite-inhibitory signaling, and suggest that clinically approved antipsychotic compounds may be repurposed for use in CNS injured patients

Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R2 increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase

Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R2 increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase