PROPEL: implementation of an evidence based pelvic floor muscle training intervention for women with pelvic organ prolapse: a realist evaluation and outcomes study protocol

Abstract Background Pelvic Organ Prolapse (POP) is estimated to affect 41%–50% of women aged over 40. Findings from the multi-centre randomised controlled “Pelvic Organ Prolapse PhysiotherapY” (POPPY) trial showed that individualised pelvic floor muscle training (PFMT) was effective in reducing symptoms of prolapse, improved quality of life and showed clear potential to be cost-effective. However, provision of PFMT for prolapse continues to vary across the UK, with limited numbers of women’s health physiotherapists specialising in its delivery. Implementation of this robust evidence from the POPPY trial will require attention to different models of delivery (e.g. staff skill mix) to fit with differing care environments. Methods A Realist Evaluation (RE) of implementation and outcomes of PFMT delivery in contrasting NHS settings will be conducted using multiple case study sites. Involving substantial local stakeholder engagement will permit a detailed exploration of how local sites make decisions on how to deliver PFMT and how these lead to service change. The RE will track how implementation is working; identify what influences outcomes; and, guided by the RE-AIM framework, will collect robust outcomes data. This will require mixed methods data collection and analysis. Qualitative data will be collected at four time-points across each site to understand local contexts and decisions regarding options for intervention delivery and to monitor implementation, uptake, adherence and outcomes. Patient outcome data will be collected at baseline, six months and one year follow-up for 120 women. Primary outcome will be the Pelvic Organ Prolapse Symptom Score (POP-SS). An economic evaluation will assess the costs and benefits associated with different delivery models taking account of further health care resource use by the women. Cost data will be combined with the primary outcome in a cost effectiveness analysis, and the EQ-5D-5L data in a cost utility analysis for each of the different models of delivery. Discussion Study of the implementation of varying models of service delivery of PFMT across contrasting sites combined with outcomes data and a cost effectiveness analysis will provide insight into the implementation and value of different models of PFMT service delivery and the cost benefits to the NHS in the longer term

Brain age predicts mortality

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, ‘brain-predicted age’, derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death

Characteristics of outdoor falls among older people: A qualitative study

Background Falls are a major threat to older people’s health and wellbeing. Approximately half of falls occur in outdoor environments but little is known about the circumstances in which they occur. We conducted a qualitative study to explore older people’s experiences of outdoor falls to develop understanding of how they may be prevented. Methods We conducted nine focus groups across the UK (England, Wales, and Scotland). Our sample was from urban and rural settings and different environmental landscapes. Participants were aged 65+ and had at least one outdoor fall in the past year. We analysed the data using framework and content analyses. Results Forty-four adults aged 65 – 92 took part and reported their experience of 88 outdoor falls. Outdoor falls occurred in a variety of contexts, though reports suggested the following scenarios may have been more frequent: when crossing a road, in a familiar area, when bystanders were around, and with an unreported or unknown attribution. Most frequently, falls resulted in either minor or moderate injury, feeling embarrassed at the time of the fall, and anxiety about falling again. Ten falls resulted in fracture, but no strong pattern emerged in regard to the contexts of these falls. Anxiety about falling again appeared more prevalent among those that fell in urban settings and who made more visits into their neighbourhood in a typical week. Conclusions This exploratory study has highlighted several aspects of the outdoor environment that may represent risk factors for outdoor falls and associated fear of falling. Health professionals are recommended to consider outdoor environments as well as the home setting when working to prevent falls and increase mobility among older people

A Markov blanket-based method for detecting causal SNPs in GWAS

<p>Abstract</p> <p>Background</p> <p>Detecting epistatic interactions associated with complex and common diseases can help to improve prevention, diagnosis and treatment of these diseases. With the development of genome-wide association studies (GWAS), designing powerful and robust computational method for identifying epistatic interactions associated with common diseases becomes a great challenge to bioinformatics society, because the study of epistatic interactions often deals with the large size of the genotyped data and the huge amount of combinations of all the possible genetic factors. Most existing computational detection methods are based on the classification capacity of SNP sets, which may fail to identify SNP sets that are strongly associated with the diseases and introduce a lot of false positives. In addition, most methods are not suitable for genome-wide scale studies due to their computational complexity.</p> <p>Results</p> <p>We propose a new Markov Blanket-based method, DASSO-MB (Detection of ASSOciations using Markov Blanket) to detect epistatic interactions in case-control GWAS. Markov blanket of a target variable T can completely shield T from all other variables. Thus, we can guarantee that the SNP set detected by DASSO-MB has a strong association with diseases and contains fewest false positives. Furthermore, DASSO-MB uses a heuristic search strategy by calculating the association between variables to avoid the time-consuming training process as in other machine-learning methods. We apply our algorithm to simulated datasets and a real case-control dataset. We compare DASSO-MB to other commonly-used methods and show that our method significantly outperforms other methods and is capable of finding SNPs strongly associated with diseases.</p> <p>Conclusions</p> <p>Our study shows that DASSO-MB can identify a minimal set of causal SNPs associated with diseases, which contains less false positives compared to other existing methods. Given the huge size of genomic dataset produced by GWAS, this is critical in saving the potential costs of biological experiments and being an efficient guideline for pathogenesis research.</p

What are we measuring? A critique of range of motion methods currently in use for Dupuytren's disease and recommendations for practice

Background: Range of motion is the most frequently reported measure used in practice to evaluate outcomes. A goniometer is the most reliable tool to assess range of motion yet, the lack of consistency in reporting prevents comparison between studies. The aim of this study is to identify how range of motion is currently assessed and reported in Dupuytren’s disease literature. Following analysis recommendations for practice will be made to enable consistency in future studies for comparability. This paper highlights the variation in range of motion reporting in Dupuytren’s disease. Methods: A Participants, Intervention, Comparison, Outcomes and Study design format was used for the search strategy and search terms. Surgery, needle fasciotomy or collagenase injection for primary or recurrent Dupuytren’s disease in adults were included if outcomes were monitored using range of motion to record change. A literature search was performed in May 2013 using subject heading and free-text terms to also capture electronic publications ahead of print. In total 638 publications were identified and following screening 90 articles met the inclusion criteria. Data was extracted and entered onto a spreadsheet for analysis. A thematic analysis was carried out to establish any duplication, resulting in the final range of motion measures identified. Results: Range of motion measurement lacked clarity, with goniometry reportedly used in only 43 of the 90 studies, 16 stated the use of a range of motion protocol. A total of 24 different descriptors were identified describing range of motion in the 90 studies. While some studies reported active range of motion, others reported passive or were unclear. Eight of the 24 categories were identified through thematic analysis as possibly describing the same measure, ‘lack of joint extension’ and accounted for the most frequently used. Conclusions: Published studies lacked clarity in reporting range of motion, preventing data comparison and meta-analysis. Percentage change lacks context and without access to raw data, does not allow direct comparison of baseline characteristics. A clear description of what is being measured within each study was required. It is recommended that range of motion measuring and reporting for Dupuytren’s disease requires consistency to address issues that fall into 3 main categories:- Definition of terms Protocol statement Outcome reportin

The Maltase Involved in Starch Metabolism in Barley Endosperm Is Encoded by a Single Gene

During germination and early seedling growth of barley (Hordeum vulgare), maltase is responsible for the conversion of maltose produced by starch degradation in the endosperm to glucose for seedling growth. Despite the potential relevance of this enzyme for malting and the production of alcoholic beverages, neither the nature nor the role of maltase is fully understood. Although only one gene encoding maltase has been identified with certainty, there is evidence for the existence of other genes and for multiple forms of the enzyme. It has been proposed that maltase may be involved directly in starch granule degradation as well as in maltose hydrolysis. The aim of our work was to discover the nature of maltase in barley endosperm. We used ion exchange chromatography to fractionate maltase activity from endosperm of young seedlings, and we partially purified activity for protein identification. We compared maltase activity in wild-type barley and transgenic lines with reduced expression of the previously-characterised maltase gene Agl97, and we used genomic and transcriptomic information to search for further maltase genes. We show that all of the maltase activity in the barley endosperm can be accounted for by a single gene, Agl97. Multiple forms of the enzyme most likely arise from proteolysis and other post-translational modifications

A role for CETP TaqIB polymorphism in determining susceptibility to atrial fibrillation: a nested case control study

BACKGROUND: Studies investigating the genetic and environmental characteristics of atrial fibrillation (AF) may provide new insights in the complex development of AF. We aimed to investigate the association between several environmental factors and loci of candidate genes, which might be related to the presence of AF. METHODS: A nested case-control study within the PREVEND cohort was conducted. Standard 12 lead electrocardiograms were recorded and AF was defined according to Minnesota codes. For every case, an age and gender matched control was selected from the same population (n = 194). In addition to logistic regression analyses, the multifactor-dimensionality reduction (MDR) method and interaction entropy graphs were used for the evaluation of gene-gene and gene-environment interactions. Polymorphisms in genes from the Renin-angiotensin, Bradykinin and CETP systems were included. RESULTS: Subjects with AF had a higher prevalence of electrocardiographic left ventricular hypertrophy, ischemic heart disease, hypertension, renal dysfunction, elevated levels of C-reactive protein (CRP) and increased urinary albumin excretion as compared to controls. The polymorphisms of the Renin-angiotensin system and Bradykinin gene did not show a significant association with AF (p > 0.05). The TaqIB polymorphism of the CETP gene was significantly associated with the presence of AF (p < 0.05). Using the MDR method, the best genotype-phenotype models included the combination of micro- or macroalbuminuria and CETP TaqIB polymorphism, CRP >3 mg/L and CETP TaqIB polymorphism, renal dysfunction and the CETP TaqIB polymorphism, and ischemic heart disease and CETP TaqIB polymorphism (1000 fold permutation testing, P < 0.05). Interaction entropy graph showed that the combination of albuminuria and CETP TaqIB polymorphism removed the most entropy. CONCLUSION: CETP TaqIB polymorphism is significantly associated with the presence of AF in the context of micro- or macroalbuminuria, elevated C-reactive protein, renal dysfunction, and ischemic heart disease