The costs, resource use, and cost-effectiveness of Clinical Nurse Specialist (CNSs) led interventions for patients with palliative care needs: a systematic review of international evidence

Background: Patients with palliative care (PC) needs do not access specialist palliative care services according to their necessities. Clinical Nurse Specialists (CNS) working across a variety of fields are playing an increasingly important role in the care of such patients, but there is limited knowledge of the extent to which their interventions are cost-effective. Objectives: To present results from a systematic review of the international evidence on the costs, resource use and cost effectiveness of CNS led interventions for patients palliative care needs, defined as seriously ill patients and those with advanced disease or frailty who are unlikely to be cured, recover, or stabilize. Design: Systematic review following PRISMA methodology. Data sources: Medline, Embase, Cinahl and Cochrane library up to 2015. Studies focusing on the outcomes of CNS interventions for patients with PC needs, and including at least one economic outcome, were considered. The quality of studies was assessed using tools from the Joanna-Briggs-Institute. Results: A total of 79 papers were included: 37 RCTs, 22 quasi-experimental studies, 7 service evaluations and other studies, and 13 economic analyses. The studies included a wide variety of interventions including clinical, support and education, as well as care coordination activities. The quality of the studies varied greatly. Conclusions: CNSs interventions may be effective in reducing specific resource use such as hospitalizations /re-hospitalizations/admissions, length of stay, and health care costs. There is mixed evidence regarding their cost-effectiveness. Future studies should ensure that clinical nurse specialists’ roles and activities are clearly described and evaluated

Predictive gene lists for breast cancer prognosis: A topographic visualisation study

<p>Abstract</p> <p>Background</p> <p>The controversy surrounding the non-uniqueness of predictive gene lists (PGL) of small selected subsets of genes from very large potential candidates as available in DNA microarray experiments is now widely acknowledged <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>. Many of these studies have focused on constructing discriminative semi-parametric models and as such are also subject to the issue of random correlations of sparse model selection in high dimensional spaces. In this work we outline a different approach based around an unsupervised patient-specific nonlinear topographic projection in predictive gene lists.</p> <p>Methods</p> <p>We construct nonlinear topographic projection maps based on inter-patient gene-list relative dissimilarities. The Neuroscale, the Stochastic Neighbor Embedding(SNE) and the Locally Linear Embedding(LLE) techniques have been used to construct two-dimensional projective visualisation plots of 70 dimensional PGLs per patient, classifiers are also constructed to identify the prognosis indicator of each patient using the resulting projections from those visualisation techniques and investigate whether <it>a-posteriori </it>two prognosis groups are separable on the evidence of the gene lists.</p> <p>A literature-proposed predictive gene list for breast cancer is benchmarked against a separate gene list using the above methods. Generalisation ability is investigated by using the mapping capability of Neuroscale to visualise the follow-up study, but based on the projections derived from the original dataset.</p> <p>Results</p> <p>The results indicate that small subsets of patient-specific PGLs have insufficient prognostic dissimilarity to permit a distinction between two prognosis patients. Uncertainty and diversity across multiple gene expressions prevents unambiguous or even confident patient grouping. Comparative projections across different PGLs provide similar results.</p> <p>Conclusion</p> <p>The random correlation effect to an arbitrary outcome induced by small subset selection from very high dimensional interrelated gene expression profiles leads to an outcome with associated uncertainty. This continuum and uncertainty precludes any attempts at constructing discriminative classifiers.</p> <p>However a patient's gene expression profile could possibly be used in treatment planning, based on knowledge of other patients' responses.</p> <p>We conclude that many of the patients involved in such medical studies are <it>intrinsically unclassifiable </it>on the basis of provided PGL evidence. This additional category of 'unclassifiable' should be accommodated within medical decision support systems if serious errors and unnecessary adjuvant therapy are to be avoided.</p

Review: Allelochemicals as multi-kingdom plant defence compounds: towards an integrated approach

© 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. The capability of synthetic pesticides to manage weeds, insect pests and pathogens in crops has diminished due to evolved resistance. Sustainable management is thus becoming more challenging. Novel solutions are needed and, given the ubiquity of biologically active secondary metabolites in nature, such compounds require further exploration as leads for novel crop protection chemistry. Despite improving understanding of allelochemicals, particularly in terms of their potential for use in weed control, their interactions with multiple biotic kingdoms have to date largely been examined in individual compounds and not as a recurrent phenomenon. Here, multi-kingdom effects in allelochemicals are introduced by defining effects on various organisms, before exploring current understanding of the inducibility and possible ecological roles of these compounds with regard to the evolutionary arms race and dose–response relationships. Allelochemicals with functional benefits in multiple aspects of plant defence are described. Gathering these isolated areas of science under the unified umbrella of multi-kingdom allelopathy encourages the development of naturally-derived chemistries conferring defence to multiple discrete biotic stresses simultaneously, maximizing benefits in weed, insect and pathogen control, while potentially circumventing resistance. © 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry

Developmental morphology of cover crop species exhibit contrasting behaviour to changes in soil bulk density, revealed by X-ray computed tomography

Plant roots growing through soil typically encounter considerable structural heterogeneity, and local variations in soil dry bulk density. The way the in situ architecture of root systems of different species respond to such heterogeneity is poorly understood due to challenges in visualising roots growing in soil. The objective of this study was to visualise and quantify the impact of abrupt changes in soil bulk density on the roots of three cover crop species with contrasting inherent root morphologies, viz. tillage radish (Raphanus sativus), vetch (Vicia sativa) and black oat (Avena strigosa). The species were grown in soil columns containing a two-layer compaction treatment featuring a 1.2 g cm-3 (uncompacted) zone overlaying a 1.4 g cm-3 (compacted) zone. Three-dimensional visualisations of the root architecture were generated via X-ray computed tomography, and an automated root-segmentation imaging algorithm. Three classes of behaviour were manifest as a result of roots encountering the compacted interface, directly related to the species. For radish, there was switch from a single tap-root to multiple perpendicular roots which penetrated the compacted zone, whilst for vetch primary roots were diverted more horizontally with limited lateral growth at less acute angles. Black oat roots penetrated the compacted zone with no apparent deviation. Smaller root volume, surface area and lateral growth were consistently observed in the compacted zone in comparison to the uncompacted zone across all species. The rapid transition in soil bulk density had a large effect on root morphology that differed greatly between species, with major implications for how these cover crops will modify and interact with soil structure

Growth and Asymmetry of Soil Microfungal Colonies from “Evolution Canyon,” Lower Nahal Oren, Mount Carmel, Israel

Fluctuating asymmetry is a contentious indicator of stress in populations of animals and plants. Nevertheless, it is a measure of developmental noise, typically obtained by measuring asymmetry across an individual organism's left-right axis of symmetry. These individual, signed asymmetries are symmetrically distributed around a mean of zero. Fluctuating asymmetry, however, has rarely been studied in microorganisms, and never in fungi.We examined colony growth and random phenotypic variation of five soil microfungal species isolated from the opposing slopes of “Evolution Canyon,” Mount Carmel, Israel. This canyon provides an opportunity to study diverse taxa inhabiting a single microsite, under different kinds and intensities of abiotic and biotic stress. The south-facing “African” slope of “Evolution Canyon” is xeric, warm, and tropical. It is only 200 m, on average, from the north-facing “European” slope, which is mesic, cool, and temperate. Five fungal species inhabiting both the south-facing “African” slope, and the north-facing “European” slope of the canyon were grown under controlled laboratory conditions, where we measured the fluctuating radial asymmetry and sizes of their colonies. from the “African” slope were more asymmetric than those from the “European” slope.Our study suggests that fluctuating radial asymmetry has potential as an indicator of random phenotypic variation and stress in soil microfungi. Interaction of slope and species for both growth rate and asymmetry of microfungi in a common environment is evidence of genetic differences between the “African” and “European” slopes of “Evolution Canyon.

Prevalence of asymptomatic bacteriuria in type 2 diabetic subjects with and without microalbuminuria

<p>Abstract</p> <p>Background</p> <p>Diabetic subjects, especially women, show high prevalence of asymptomatic bacteriuria (ASB). The aim of the present study was to evaluate the prevalence of ASB in subjects with type 2 diabetes mellitus (T2D) with and without microalbuminuria (MA).</p> <p>Findings</p> <p>A hundred diabetic subjects with MA (53 males/47 females, mean age ± standard deviation: 65.5 ± 11.1 years) and 100 diabetic subjects without MA (52 males/48 females, mean age ± standard deviation: 65.4 ± 11.3 years), consecutively attending the outpatient diabetes clinic of our hospital were recruited in the study. Subjects with overt diabetic nephropathy or nephropathy from other causes were excluded. In addition, subjects with symptoms of urinary track infection or use of antimicrobial drugs in the last 14 days were excluded by the study.</p> <p>Diabetic subjects with MA showed increased prevalence of ASB compared to diabetic subjects without MA (21% versus 8%, P < 0.001, respectively). <it>Escherichia coli </it>was the most prevalent pathogen isolated in diabetic subjects with and without MA (12% versus 3.0%, P = 0.01, respectively) followed by <it>Proteus mirabilis </it>(6% versus 5%, P = 0.75, respectively) and <it>Klebsiella </it>spp (5% versus 1%, P = 0.09, respectively). Univariate logistic analysis showed that ASB was associated with the presence of coronary artery disease [odds ratio (OR): 0.29, 95% Confidence Intervals (95% CI): 0.09-0.95, P = 0.04] and gender (OR: 0.09, 95% CI: 0.02-0.35, P < 0.001) in the diabetic study group with MA.</p> <p>Conclusions</p> <p>ASB is more prevalent among T2D subjects with MA. Screening for ASB is warranted in diabetic patients especially if pyuria is detected in urine analysis since ASB has been found to be a risk factor for developing symptomatic urinary tract infection.</p

Case management used to optimize cancer care pathways: A systematic review

<p>Abstract</p> <p>Background</p> <p>Reports of inadequate cancer patient care have given rise to various interventions to support cancer care pathways which, overall, seem poorly studied. Case management (CM) is one method that may support a cost-effective, high-quality patient-centred treatment and care.</p> <p>The purpose of this article was to summarise intervention characteristics, outcomes of interest, results, and validity components of the published randomized controlled trials (RCTs) examining CM as a method for optimizing cancer care pathways.</p> <p>Methods</p> <p>PubMed, Embase, Web of Science, CINAHL and The Cochrane Central Register of Controlled Trials were systematically searched for RCTs published all years up to August 2008. Identified papers were included if they passed the following standards. Inclusion criteria: 1) The intervention should meet the criteria for CM which includes multidisciplinary collaboration, care co-ordination, and it should include in-person meetings between patient and the case manager aimed at supporting, informing and educating the patient. 2) The intervention should focus on cancer patient care. 3) The intervention should aim to improve subjective or objective quality outcomes, and effects should be reported in the paper.</p> <p>Exclusion criteria: Studies centred on cancer screening or palliative cancer care.</p> <p>Data extraction was conducted in order to obtain a descriptive overview of intervention characteristics, outcomes of interest and findings. Elements of CONSORT guidelines and checklists were used to assess aspects of study validity.</p> <p>Results</p> <p>The searches identified 654 unique papers, of which 25 were retrieved for scrutiny. Seven papers were finally included. Intervention characteristics, outcomes studied, findings and methodological aspects were all very diverse.</p> <p>Conclusion</p> <p>Due to the scarcity of papers included (seven), significant heterogeneity in target group, intervention setting, outcomes measured and methodologies applied, no conclusions can be drawn about the effect of CM on cancer patient care.</p> <p>It is a major challenge that CM shrouds in a "black box", which means that it is difficult to determine which aspect(s) of interventions contribute to overall effects. More trials on rigorously developed CM interventions (opening up the "black box") are needed as is the re-testing of interventions and outcomes studied in various settings.</p

Risk of Parkinson's disease after tamoxifen treatment

<p>Abstract</p> <p>Background</p> <p>Women have a reduced risk of developing Parkinson's disease (PD) compared with age-matched men. Neuro-protective effects of estrogen potentially explain this difference. Tamoxifen, commonly used in breast cancer treatment, may interfere with the protective effects of estrogen and increase risk of PD. We compared the rate of PD in Danish breast cancer patients treated with tamoxifen to the rate among those not treated with tamoxifen.</p> <p>Methods</p> <p>A cohort of 15,419 breast cancer patients identified from the Danish Breast Cancer Collaborative Group database was linked to the National Registry of Patients to identify PD diagnoses. Overall risk and rate of PD following identification into the study was compared between patients treated with tamoxifen as adjuvant hormonal therapy and patients not receiving tamoxifen. Time-dependent effects of tamoxifen treatment on PD rate were examined to estimate the likely induction period for tamoxifen.</p> <p>Results</p> <p>In total, 35 cases of PD were identified among the 15,419 breast cancer patients. No overall effect of tamoxifen on rate of PD was observed (HR = 1.3, 95% CI: 0.64-2.5), but a PD hazard ratio of 5.1 (95% CI: 1.0-25) was seen four to six years following initiation of tamoxifen treatment.</p> <p>Conclusions</p> <p>These results provide evidence that the neuro-protective properties of estrogen against PD occurrence may be disrupted by tamoxifen therapy. Tamoxifen treatments may be associated with an increased rate of PD; however these effects act after four years, are of limited duration, and the adverse effect is overwhelmed by the protection against breast recurrence conferred by tamoxifen therapy.</p

Motor Deficits and Decreased Striatal Dopamine Receptor 2 Binding Activity in the Striatum-Specific Dyt1 Conditional Knockout Mice

DYT1 early-onset generalized dystonia is a hyperkinetic movement disorder caused by mutations in DYT1 (TOR1A), which codes for torsinA. Recently, significant progress has been made in studying pathophysiology of DYT1 dystonia using targeted mouse models. Dyt1 ΔGAG heterozygous knock-in (KI) and Dyt1 knock-down (KD) mice exhibit motor deficits and alterations of striatal dopamine metabolisms, while Dyt1 knockout (KO) and Dyt1 ΔGAG homozygous KI mice show abnormal nuclear envelopes and neonatal lethality. However, it has not been clear whether motor deficits and striatal abnormality are caused by Dyt1 mutation in the striatum itself or the end results of abnormal signals from other brain regions. To identify the brain region that contributes to these phenotypes, we made a striatum-specific Dyt1 conditional knockout (Dyt1 sKO) mouse. Dyt1 sKO mice exhibited motor deficits and reduced striatal dopamine receptor 2 (D2R) binding activity, whereas they did not exhibit significant alteration of striatal monoamine contents. Furthermore, we also found normal nuclear envelope structure in striatal medium spiny neurons (MSNs) of an adult Dyt1 sKO mouse and cerebral cortical neurons in cerebral cortex-specific Dyt1 conditional knockout (Dyt1 cKO) mice. The results suggest that the loss of striatal torsinA alone is sufficient to produce motor deficits, and that this effect may be mediated, at least in part, through changes in D2R function in the basal ganglia circuit

A voting approach to identify a small number of highly predictive genes using multiple classifiers

<p>Abstract</p> <p>Background</p> <p>Microarray gene expression profiling has provided extensive datasets that can describe characteristics of cancer patients. An important challenge for this type of data is the discovery of gene sets which can be used as the basis of developing a clinical predictor for cancer. It is desirable that such gene sets be compact, give accurate predictions across many classifiers, be biologically relevant and have good biological process coverage.</p> <p>Results</p> <p>By using a new type of multiple classifier voting approach, we have identified gene sets that can predict breast cancer prognosis accurately, for a range of classification algorithms. Unlike a wrapper approach, our method is not specialised towards a single classification technique. Experimental analysis demonstrates higher prediction accuracies for our sets of genes compared to previous work in the area. Moreover, our sets of genes are generally more compact than those previously proposed. Taking a biological viewpoint, from the literature, most of the genes in our sets are known to be strongly related to cancer.</p> <p>Conclusion</p> <p>We show that it is possible to obtain superior classification accuracy with our approach and obtain a compact gene set that is also biologically relevant and has good coverage of different biological processes.</p