Healthcare professionals’ response to cachexia in advanced cancer

Background: Cancer cachexia is a complex metabolic syndrome characterised by severe and progressive weight loss which is predominantly muscle mass. It is a devastating complication of advanced cancer with profound bio-psycho-social implications for patients and their families. At present, there is no curative treatment for cachexia in advanced cancer therefore, the most important healthcare response entails the minimisation of the psycho-social distress associated with it. However, the literature suggests healthcare professionals’ are missing opportunities to respond to the multi-dimensional needs of this population.

Aim: The objective of this study was to explore healthcare professionals’ experience, understanding and perception of need of patients with advanced cancer who have cachexia and their families.

Methods: An interpretative qualitative approach based on symbolic interactionism was adopted. A purposive sample of doctors, nurses, specialist nurses, and dieticians were recruited from a cancer centre in a large teaching hospital in Northern Ireland. Data collection consisted of two phases: focus group interviews followed by individual semi-structured interviews.

Results: Findings from the focus group interviews were used as a framework for the semi structured interview schedule. Results centred on the influence of a variable combination of knowledge, culture, and resources on the management of cachexia in advanced cancer. Data revealed that variation in healthcare professionals’ perceptions of cachexia in advanced cancer, along with their professional ethos, influenced their response to it in clinical practice.

Conclusions: This study has revealed that cancer cachexia is a complex and challenging syndrome which needs to be addressed from a holistic model of care to reflect the multidimensional needs of patients and their families. Effective management will require a combination of knowledge, a supportive culture, and adequate resources.

Uncovering the challenges of managing cachexia in advanced cancer: Preliminary results from semi-structured interviews with healthcare professionals in a regional cancer centre

Background: Cancer cachexia is a complex metabolic syndrome characterised by severe and progressive weight loss which is predominantly muscle mass. It is a devastating and distressing complication of advanced cancer with profound bio-psycho-social implications for patients and their families. At present there is no curative treatment for cachexiain advanced cancer therefore the most important healthcare response entails the minimisation of the psycho-social distress associated with it. However the literature suggests healthcare professionals’are missing opportunities to intervene and respond to the multi-dimensional needs of this population.

Objective:The objective of this study was to explore healthcare professionals’ response to cachexia in advanced cancer.

Methods: An interpretative qualitative approach was adopted in this study. A purposive sample of doctors, nurses, specialist nurses and dieticians were recruited from a regional cancer centre between November 2009 and November 2010. Data was collection was twofold: two multi-professional focus groups were conducted first to uncover the main themes and issues in cachexia management. This data then informed the interview schedule for the following 25 individual semi-structured interviews.

Results: Preliminary data analysis of the semi-structured interviews revealed distinct differences between disciplines in their perceptions of cancer cachexia which influenced their response to it in clinical practice. The commonality between disciplines, with the exception of palliative care, was a reliance on the biomedical approach to cancer cachexia management.

Discussion and Conclusions: Cancer cachexia is a complex and challenging syndrome which needs to be addressed from a holistic model of care to reflect the multi-dimensional needs of this patient group. The perspectives of those involved in care delivery is required in order to inform the development of interventions aimed at minimising the distress associated with this devastating syndrome.

Ethical issues experienced by healthcare workers in nursing homes: Literature review

BACKGROUND: Ethical issues are increasingly being reported by care-providers; however, little is known about the nature of these issues within the nursing home. Ethical issues are unavoidable in healthcare and can result in opportunities for improving work and care conditions; however, they are also associated with detrimental outcomes including staff burnout and moral distress.

OBJECTIVES: The purpose of this review was to identify prior research which focuses on ethical issues in the nursing home and to explore staffs' experiences of ethical issues.

METHODS: Using a systematic approach based on Aveyard (2014), a literature review was conducted which focused on ethical and moral issues, nurses and nursing assistants, and the nursing home.

FINDINGS: The most salient themes identified in the review included clashing ethical principles, issues related to communication, lack of resources and quality of care provision. The review also identified solutions for overcoming the ethical issues that were identified and revealed the definitional challenges that permeate this area of work.

CONCLUSIONS: The review highlighted a need for improved ethics education for care-providers.

Particle-in-cell simulation study of the interaction between a relativistically moving leptonic micro-cloud and ambient electrons

Context. The jets of compact accreting objects are composed of electrons and a mixture of positrons and ions. These outflows impinge on the interstellar or intergalactic medium and both plasmas interact via collisionless processes. Filamentation (beam-Weibel) instabilities give rise to the growth of strong electromagnetic fields. These fields thermalize the interpenetrating plasmas. 

Aims. Hitherto, the effects imposed by a spatial non-uniformity on filamentation instabilities have remained unexplored. We examine the interaction between spatially uniform background electrons and a minuscule cloud of electrons and positrons. The cloud size is comparable to that created in recent laboratory experiments and such clouds may exist close to internal and external shocks of leptonic jets. The purpose of our study is to determine the prevalent instabilities, their ability to generate electromagnetic fields and the mechanism, by which the lepton micro-cloud transfers energy to the background plasma. 

Methods. A square micro-cloud of equally dense electrons and positrons impinges in our particle-in-cell (PIC) simulation on a spatially uniform plasma at rest. The latter consists of electrons with a temperature of 1 keV and immobile ions. The initially charge- and current neutral micro-cloud has a temperature of 100 keV and a side length of 2.5 plasma skin depths of the micro-cloud. The side length is given in the reference frame of the background plasma. The mean speed of the micro-cloud corresponds to a relativistic factor of 15, which is relevant for laboratory experiments and for relativistic astrophysical outflows. The spatial distributions of the leptons and of the electromagnetic fields are examined at several times. 

Results. A filamentation instability develops between the magnetic field carried by the micro-cloud and the background electrons. The electromagnetic fields, which grow from noise levels, redistribute the electrons and positrons within the cloud, which boosts the peak magnetic field amplitude. The current density and the moduli of the electromagnetic fields grow aperiodically in time and steadily along the direction that is anti-parallel to the cloud's velocity vector. The micro-cloud remains conjoined during the simulation. The instability induces an electrostatic wakefield in the background plasma. 

Conclusions. Relativistic clouds of leptons can generate and amplify magnetic fields even if they have a microscopic size, which implies that the underlying processes can be studied in the laboratory. The interaction of the localized magnetic field and high-energy leptons will give rise to synchrotron jitter radiation. The wakefield in the background plasma dissipates the kinetic energy of the lepton cloud. Even the fastest lepton micro-clouds can be slowed down by this collisionless mechanism. Moderately fast charge- and current neutralized lepton micro-clouds will deposit their energy close to relativistic shocks and hence they do not constitute an energy loss mechanism for the shock.

A Lightweight Tool for Anomaly Detection in Cloud Data Centres

Cloud data centres are critical business infrastructures and the fastest growing service providers. Detecting anomalies in Cloud data centre operation is vital. Given the vast complexity of the data centre system software stack, applications and workloads, anomaly detection is a challenging endeavour. Current tools for detecting anomalies often use machine learning techniques, application instance behaviours or system metrics distribu- tion, which are complex to implement in Cloud computing environments as they require training, access to application-level data and complex processing. This paper presents LADT, a lightweight anomaly detection tool for Cloud data centres that uses rigorous correlation of system metrics, implemented by an efficient corre- lation algorithm without need for training or complex infrastructure set up. LADT is based on the hypothesis that, in an anomaly-free system, metrics from data centre host nodes and virtual machines (VMs) are strongly correlated. An anomaly is detected whenever correlation drops below a threshold value. We demonstrate and evaluate LADT using a Cloud environment, where it shows that the hosting node I/O operations per second (IOPS) are strongly correlated with the aggregated virtual machine IOPS, but this correlation vanishes when an application stresses the disk, indicating a node-level anomaly.

Uncertainty in the Cloud: An Angel-Daemon Approach to Modelling Performance

Uncertainty profiles are used to study the effects of contention within cloud and service-based environments. An uncertainty profile provides a qualitative description of an environment whose quality of service (QoS) may fluctuate unpredictably. Uncertain environments are modelled by strategic games with two agents; a daemon is used to represent overload and high resource contention; an angel is used to represent an idealised resource allocation situation with no underlying contention. Assessments of uncertainty profiles are useful in two ways: firstly, they provide a broad understanding of how environmental stress can effect an application’s performance (and reliability); secondly, they allow the effects of introducing redundancy into a computation to be assessed

Impact of an enhanced antibiotic stewardship on reducing methicillin-resistant Staphylococcus aureus in primary and secondary healthcare settings

The objective of this study was to evaluate the impact of restricting high-risk antibiotics on methicillin-resistant Staphylococcus aureus (MRSA) incidence rates in a hospital setting. A secondary objective was to assess the impact of reducing fluoroquinolone use in the primary-care setting on MRSA incidence in the community. This was an interventional, retrospective, ecological investigation in both hospital and community (January 2006 to June 2010). Segmented regression analysis of interrupted time-series was employed to evaluate the intervention. The restriction of high-risk antibiotics was associated with a significant change in hospital MRSA incidence trend (coefficient=-0·00561, P=0·0057). Analysis showed that the intervention relating to reducing fluoroquinolone use in the community was associated with a significant trend change in MRSA incidence in community (coefficient=-0·00004, P=0·0299). The reduction in high-risk antibiotic use and fluoroquinolone use contributed to both a reduction in incidence rates of MRSA in hospital and community (primary-care) settings. 

A modified method for measuring antibiotic use in healthcare settings: implications for antibiotic stewardship and benchmarking

Objectives: To determine whether adjusting the denominator of the common hospital antibiotic use measurement unit (defined daily doses/100 bed-days) by including age-adjusted comorbidity score (100 bed-days/age-adjusted comorbidity score) would result in more accurate and meaningful assessment of hospital antibiotic use. 

Methods: The association between the monthly sum of age-adjusted comorbidity and monthly antibiotic use was measured using time-series analysis (January 2008 to June 2012). For the purposes of conducting internal benchmarking, two antibiotic usage datasets were constructed, i.e. 2004-07 (first study period) and 2008-11 (second study period). Monthly antibiotic use was normalized per 100 bed-days and per 100 bed-days/age-adjusted comorbidity score. 

Results: Results showed that antibiotic use had significant positive relationships with the sum of age-adjusted comorbidity score (P = 0.0004). The results also showed that there was a negative relationship between antibiotic use and (i) alcohol-based hand rub use (P = 0.0370) and (ii) clinical pharmacist activity (P = 0.0031). Normalizing antibiotic use per 100 bed-days contributed to a comparative usage rate of 1.31, i.e. the average antibiotic use during the second period was 31% higher than during the first period. However, normalizing antibiotic use per 100 bed-days per age-adjusted comorbidity score resulted in a comparative usage rate of 0.98, i.e. the average antibiotic use was 2% lower in the second study period. Importantly, the latter comparative usage rate is independent of differences in patient density and case mix characteristics between the two studied populations. 

Conclusions: The proposed modified antibiotic measure provides an innovative approach to compare variations in antibiotic prescribing while taking account of patient case mix effects. 

Towards Automated Data-Driven Model Creation for Cloud Computing Simulation

The increasing complexity and scale of cloud computing environments due to widespread data centre heterogeneity makes measurement-based evaluations highly difficult to achieve. Therefore the use of simulation tools to support decision making in cloud computing environments to cope with this problem is an increasing trend. However the data required in order to model cloud computing environments with an appropriate degree of accuracy is typically large, very difficult to collect without some form of automation, often not available in a suitable format and a time consuming process if done manually. In this research, an automated method for cloud computing topology definition, data collection and model creation activities is presented, within the context of a suite of tools that have been developed and integrated to support these activities.