Radiographer-led discharge for emergency care patients, requiring projection radiography of minor musculoskeletal injuries: a scoping review.

This is the final version. Available on open access from BMC via the DOI in this recordAvailability of data and materials: All data used and analysed during this study are included in this published article.BACKGROUND: Pressure on emergency departments (EDs) from increased attendance for minor injuries has been recognised in the United Kingdom. Radiographer-led discharge (RLD) has potential for improving efficiency, through radiographers trained to discharge patients or refer them for treatment at the point of image assessment. This review aims to scope all RLD literature and identify research assessing the merits of RLD and requirements to enable implementation. METHODS: We conducted a scoping review of studies relating to RLD of emergency care patients requiring projection radiography of minor musculoskeletal (MSK) injuries. MEDLINE, Embase and CINAHL, relevant radiography journals and grey literature were searched. Articles were reviewed and the full texts of selected studies were screened against eligibility criteria. The data were extracted, collated and a narrative synthesis completed. RESULTS: Seven studies with varying study designs were included in the review. The small number of studies was possibly due to a generally low research uptake in radiography. The main outcome for four studies was reduced length of stay in ED, with recall and re-attendance to ED a primary outcome in one study and secondary outcome for two other studies. The potential for increased efficiency in the minor MSK pathway patient pathway and capacity for ED staff was recognised. Radiographers identified a concern regarding the risk of litigation and incentive of increased salary when considering RLD. The studies were broadly radiographer focussed, despite RLD spanning ED and Radiology. CONCLUSION: There were a low number of RLD active radiographers, likely to be motivated individuals. However, RLD has potential for generalisability with protocol variations evident, all producing similar positive outcomes. Understanding radiography and ED culture could clarify facilitators for RLD to be utilised more sustainably into the future. Cost effectiveness studies, action research within ED, and cluster randomised controlled trial with process evaluation are needed to fully understand the potential for RLD. The cost effectiveness of RLD may provide financial support for training radiographers and increasing their salary, with potential future benefit of reduction in workload within ED. RLD implementation would require an inter-professional approach achieved by understanding ED staff and patient perspectives and ensuring these views are central to RLD implementation

Correction: Radiographer-led discharge for emergency care patients, requiring projection radiography of minor musculoskeletal injuries: a scoping review

This is the final version. Available on open access from BMC via the DOI in this recordThe article to which this is the correction is available in ORE at http://hdl.handle.net/10871/131862The original article contained errors affecting correct attribution of the citations to their respective references which has since been corrected

Stroke and dementia risk: A systematic review and meta-analysis

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordIntroduction: Stroke is an established risk factor for all-cause dementia, though meta-analyses are needed to quantify this risk. Methods: We searched Medline, PsycINFO, and Embase for studies assessing prevalent or incident stroke versus a no-stroke comparison group and the risk of all-cause dementia. Random effects meta-analysis was used to pool adjusted estimates across studies, and meta-regression was used to investigate potential effect modifiers. Results: We identified 36 studies of prevalent stroke (1.9 million participants) and 12 studies of incident stroke (1.3 million participants). For prevalent stroke, the pooled hazard ratio for all-cause dementia was 1.69 (95% confidence interval: 1.49–1.92; P <.00001; I2 = 87%). For incident stroke, the pooled risk ratio was 2.18 (95% confidence interval: 1.90–2.50; P <.00001; I2 = 88%). Study characteristics did not modify these associations, with the exception of sex which explained 50.2% of between-study heterogeneity for prevalent stroke. Discussion: Stroke is a strong, independent, and potentially modifiable risk factor for all-cause dementia.Mary Kinross Charitable TrustHalpin TrustNational Institute for Health Research (NIHR)National Institute on Aging (NIA)/National Institutes of Health (NIH)National Institute of Neurological Disorders and Stroke (NIH/NINDS

Association of Lifestyle and Genetic Risk With Incidence of Dementia

This is the final version. Available from the American Medical Association via the DOI in this recordImportance: Genetic factors increase risk of dementia, but the extent to which this can be offset by lifestyle factors is unknown. Objective: To investigate whether a healthy lifestyle is associated with lower risk of dementia regardless of genetic risk. Design, Setting, and Participants: A retrospective cohort study that included adults of European ancestry aged at least 60 years without cognitive impairment or dementia at baseline. Participants joined the UK Biobank study from 2006 to 2010 and were followed up until 2016 or 2017. Exposures: A polygenic risk score for dementia with low (lowest quintile), intermediate (quintiles 2 to 4), and high (highest quintile) risk categories and a weighted healthy lifestyle score, including no current smoking, regular physical activity, healthy diet, and moderate alcohol consumption, categorized into favorable, intermediate, and unfavorable lifestyles. Main Outcomes and Measures: Incident all-cause dementia, ascertained through hospital inpatient and death records. Results: A total of 196 383 individuals (mean [SD] age, 64.1 [2.9] years; 52.7% were women) were followed up for 1 545 433 person-years (median [interquartile range] follow-up, 8.0 [7.4-8.6] years). Overall, 68.1% of participants followed a favorable lifestyle, 23.6% followed an intermediate lifestyle, and 8.2% followed an unfavorable lifestyle. Twenty percent had high polygenic risk scores, 60% had intermediate risk scores, and 20% had low risk scores. Of the participants with high genetic risk, 1.23% (95% CI, 1.13%-1.35%) developed dementia compared with 0.63% (95% CI, 0.56%-0.71%) of the participants with low genetic risk (adjusted hazard ratio, 1.91 [95% CI, 1.64-2.23]). Of the participants with a high genetic risk and unfavorable lifestyle, 1.78% (95% CI, 1.38%-2.28%) developed dementia compared with 0.56% (95% CI, 0.48%-0.66%) of participants with low genetic risk and favorable lifestyle (hazard ratio, 2.83 [95% CI, 2.09-3.83]). There was no significant interaction between genetic risk and lifestyle factors (P = .99). Among participants with high genetic risk, 1.13% (95% CI, 1.01%-1.26%) of those with a favorable lifestyle developed dementia compared with 1.78% (95% CI, 1.38%-2.28%) with an unfavorable lifestyle (hazard ratio, 0.68 [95% CI, 0.51-0.90]). Conclusions and Relevance: Among older adults without cognitive impairment or dementia, both an unfavorable lifestyle and high genetic risk were significantly associated with higher dementia risk. A favorable lifestyle was associated with a lower dementia risk among participants with high genetic risk.James Tudor FoundationMary Kinross Charitable TrustHalpin TrustNational Institute for Health Research (NIHR)National Health and Medical Research Council, AustraliaNational Institute on Aging/National Institutes of HealthEngineering and Physical Sciences Research Council (EPSRC

Parathyroid hormone, cognitive function and dementia: a systematic review

BACKGROUND: Metabolic factors are increasingly recognized to play an important role in the pathogenesis of Alzheimer's disease and dementia. Abnormal parathyroid hormone (PTH) levels play a role in neuronal calcium dysregulation, hypoperfusion and disrupted neuronal signaling. Some studies support a significant link between PTH levels and dementia whereas others do not. METHODS: We conducted a systematic review through January 2014 to evaluate the association between PTH and parathyroid conditions, cognitive function and dementia. Eleven electronic databases and citation indexes were searched including Medline, Embase and the Cochrane Library. Hand searches of selected journals, reference lists of primary studies and reviews were also conducted along with websites of key organizations. Two reviewers independently screened titles and abstracts of identified studies. Data extraction and study quality were performed by one and checked by a second reviewer using predefined criteria. A narrative synthesis was performed due to the heterogeneity of included studies. RESULTS: The twenty-seven studies identified were of low and moderate quality, and challenging to synthesize due to inadequate reporting. Findings from six observational studies were mixed but suggest a link between higher serum PTH levels and increased odds of poor cognition or dementia. Two case-control studies of hypoparathyroidism provide limited evidence for a link with poorer cognitive function. Thirteen pre-post surgery studies for primary hyperparathyroidism show mixed evidence for improvements in memory though limited agreement in other cognitive domains. There was some degree of cognitive impairment and improvement postoperatively in observational studies of secondary hyperparathyroidism but no evident pattern of associations with specific cognitive domains. CONCLUSIONS: Mixed evidence offers weak support for a link between PTH, cognition and dementia due to the paucity of high quality research in this area.NIHR PenCLAHRCAlzheimer’s AssociationRosetrees TrustMary Kinross Charitable TrustJames Tudor FoundationHalpin TrustNorman Family Charitable Trus

Patients with early rheumatoid arthritis exhibit elevated autoantibody titers against mildly oxidized low-density lipoprotein and exhibit decreased activity of the lipoprotein-associated phospholipase A(2)

Rheumatoid arthritis is a chronic inflammatory disease, associated with an excess of cardiovascular morbidity and mortality due to accelerated atherosclerosis. Oxidized low-density lipoprotein (oxLDL), the antibodies against oxLDL and the lipoprotein-associated phospholipase A(2 )(Lp-PLA(2)) may play important roles in inflammation and atherosclerosis. We investigated the plasma levels of oxLDL and Lp-PLA(2 )activity as well as the autoantibody titers against mildly oxLDL in patients with early rheumatoid arthritis (ERA). The long-term effects of immunointervention on these parameters in patients with active disease were also determined. Fifty-eight ERA patients who met the American College of Rheumatology criteria were included in the study. Patients were treated with methotrexate and prednisone. Sixty-three apparently healthy volunteers also participated in the study and served as controls. Three different types of mildly oxLDL were prepared at the end of the lag, propagation and decomposition phases of oxidation. The serum autoantibody titers of the IgG type against all types of oxLDL were determined by an ELISA method. The plasma levels of oxLDL and the Lp-PLA(2 )activity were determined by an ELISA method and by the trichloroacetic acid precipitation procedure, respectively. At baseline, ERA patients exhibited elevated autoantibody titers against all types of mildly oxLDL as well as low activity of the total plasma Lp-PLA(2 )and the Lp-PLA(2 )associated with the high-density lipoprotein, compared with controls. Multivariate regression analysis showed that the elevated autoantibody titers towards oxLDL at the end of the decomposition phase of oxidation and the low plasma Lp-PLA(2 )activity are independently associated with ERA. After immunointervention autoantibody titers against all types of oxLDL were decreased in parallel to the increase in high-density lipoprotein-cholesterol and high-density lipoprotein-Lp-PLA(2 )activity. We conclude that elevated autoantibody titers against oxLDL at the end of the decomposition phase of oxidation and low plasma Lp-PLA(2 )activity are feature characteristics of patients with ERA, suggesting an important role of these parameters in the pathophysiology of ERA as well as in the accelerated atherosclerosis observed in these patients

Which Risk Factors Causally Influence Dementia? A Systematic Review of Mendelian Randomization Studies

This is the final version. Available from IOS Press via the DOI in this record.BACKGROUND: Numerous risk factors for dementia are well established, though the causal nature of these associations remains unclear. OBJECTIVE: To systematically review Mendelian randomization (MR) studies investigating causal relationships between risk factors and global cognitive function or dementia. METHODS: We searched five databases from inception to February 2017 and conducted citation searches including MR studies investigating the association between any risk factor and global cognitive function, all-cause dementia or dementia subtypes. Two reviewers independently assessed titles and abstracts, full-texts, and study quality. RESULTS: We included 18 MR studies investigating education, lifestyle factors, cardiovascular factors and related biomarkers, diabetes related and other endocrine factors, and telomere length. Studies were of predominantly good quality, however eight received low ratings for sample size and statistical power. The most convincing causal evidence was found for an association of shorter telomeres with increased risk of Alzheimer's disease (AD). Causal evidence was weaker for smoking quantity, vitamin D, homocysteine, systolic blood pressure, fasting glucose, insulin sensitivity, and high-density lipoprotein cholesterol. Well-replicated associations were not present for most exposures and we cannot fully discount survival and diagnostic bias, or the potential for pleiotropic effects. CONCLUSIONS: Genetic evidence supported a causal association between telomere length and AD, whereas limited evidence for other risk factors was largely inconclusive with tentative evidence for smoking quantity, vitamin D, homocysteine, and selected metabolic markers. The lack of stronger evidence for other risk factors may reflect insufficient statistical power. Larger well-designed MR studies would therefore help establish the causal status of these dementia risk factors.This work was supported by the Mary Kinross Charitable Trust (DJL and EK), Halpin Trust (DJL, EK and IL), the James Tudor Foundation (DJL and EK), National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) for the South West Peninsula (IL, JTC, AB and DJL) and the National Institute on Aging of the National Institutes of Health under Award Number RF1AG055654 (DJL)

Artificial intelligence for dementia drug discovery and trials optimization

Drug discovery and clinical trial design for dementia have historically been challenging. In part these challenges have arisen from patient heterogeneity, length of disease course, and the tractability of a target for the brain. Applying big data analytics and machine learning tools for drug discovery and utilizing them to inform successful clinical trial design has the potential to accelerate progress. Opportunities arise at multiple stages in the therapy pipeline and the growing availability of large medical data sets opens possibilities for big data analyses to answer key questions in clinical and therapeutic challenges. However, before this goal is reached, several challenges need to be overcome and only a multi-disciplinary approach can promote data-driven decision-making to its full potential. Herein we review the current state of machine learning applications to clinical trial design and drug discovery, while presenting opportunities and recommendations that can break down the barriers to implementation

Artificial intelligence for dementia drug discovery and trials optimization

Drug discovery and clinical trial design for dementia have historically been challenging. In part these challenges have arisen from patient heterogeneity, length of disease course, and the tractability of a target for the brain. Applying big data analytics and machine learning tools for drug discovery and utilizing them to inform successful clinical trial design has the potential to accelerate progress. Opportunities arise at multiple stages in the therapy pipeline and the growing availability of large medical data sets opens possibilities for big data analyses to answer key questions in clinical and therapeutic challenges. However, before this goal is reached, several challenges need to be overcome and only a multi-disciplinary approach can promote data-driven decision-making to its full potential. Herein we review the current state of machine learning applications to clinical trial design and drug discovery, while presenting opportunities and recommendations that can break down the barriers to implementation