Patient self-management in chronic heart failure – establishing concordance between guidelines and practice

 Chronic heart failure (CHF) is a progressive and debilitating disease with a broad symptom profile, intermittently marked by periods of acute decompensation. CHF patients are encouraged to self-manage their illness, such as adhering to medical regimens and monitoring symptoms, to optimise health outcomes and quality of life. In so doing, patients are asked to collaborate with their health service providers with regard to their care. However, patients generally do not self-manage well, even with specialist support. Moreover, self- management interventions are yet to demonstrate morbidity or mortality benefits. Social network approaches to self-management consider the availability and mobilisation of all resources, beyond those of only the patient and healthcare providers. Used in conjunction with e-health platforms, social network approaches may offer a means by which to optimise self-management programmes of the future.

A new two-stage fuzzy inference system-based approach to prioritize failures in failure mode and effect analysis

This paper presents a new Fuzzy Inference System (FIS)-based Risk Priority Number (RPN) model for the prioritization of failures in Failure Mode and Effect Analysis (FMEA). In FMEA, the monotonicity property of the RPN scores is important. To maintain the monotonicity property of an FIS-based RPN model, a complete and monotonically-ordered fuzzy rule base is necessary. However, it is impractical to gather all (potentially a large number of) fuzzy rules from FMEA users. In this paper, we introduce a new two-stage approach to reduce the number of fuzzy rules that needs to be gathered, and to satisfy the monotonicity property. In stage-1, a Genetic Algorithm (GA) is used to search for a small set of fuzzy rules to be gathered from FMEA users. In stage-2, the remaining fuzzy rules are deduced approximately by a monotonicity-preserving similarity reasoning scheme. The monotonicity property is exploited as additional qualitative information for constructing the FIS-based RPN model. To assess the effectiveness of the proposed approach, a real case study with information collected from a semiconductor manufacturing plant is conducted. The outcomes indicate that the proposed approach is effective in developing an FIS-based RPN model with only a small set of fuzzy rules, which is able to satisfy the monotonicity property for prioritization of failures in FMEA.

Nurse-led titration of angiotensin converting enzyme inhibitors, beta-adrenergic blocking agents, and angiotensin receptor blockers for people with heart failure with reduced ejection fraction

BACKGROUND: Heart failure is associated with high mortality and hospital readmissions. Beta-adrenergic blocking agents, angiotensin converting enzyme inhibitors (ACEIs), and angiotensin receptor blockers (ARBs) can improve survival and reduce hospital readmissions and are recommended as first-line therapy in the treatment of heart failure. Evidence has also shown that there is a dose-dependent relationship of these medications with patient outcomes. Despite this evidence, primary care physicians are reluctant to up-titrate these medications. New strategies aimed at facilitating this up-titration are warranted. Nurse-led titration (NLT) is one such strategy. OBJECTIVES: To assess the effects of NLT of beta-adrenergic blocking agents, ACEIs, and ARBs in patients with heart failure with reduced ejection fraction (HFrEF) in terms of safety and patient outcomes. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials in the Cochrane Library (CENTRAL Issue 11 of 12, 19/12/2014), MEDLINE OVID (1946 to November week 3 2014), and EMBASE Classic and EMBASE OVID (1947 to 2014 week 50). We also searched reference lists of relevant primary studies, systematic reviews, clinical trial registries, and unpublished theses sources. We used no language restrictions. SELECTION CRITERIA: Randomised controlled trials (RCTs) comparing NLT of beta-adrenergic blocking agents, ACEIs, and/or ARBs comparing the optimisation of these medications by a nurse to optimisation by another health professional in patients with HFrEF. DATA COLLECTION AND ANALYSIS: Two review authors (AD & JC) independently assessed studies for eligibility and risk of bias. We contacted primary authors if we required additional information. We examined quality of evidence using the GRADE rating tool for RCTs. We analysed extracted data by risk ratio (RR) with 95% confidence interval (CI) for dichotomous data to measure effect sizes of intervention group compared with usual-care group. Meta-analyses used the fixed-effect Mantel-Haenszel method. We assessed heterogeneity between studies by Chi(2) and I(2). MAIN RESULTS: We included seven studies (1684 participants) in the review. One study enrolled participants from a residential care facility, and the other six studies from primary care and outpatient clinics. All-cause hospital admission data was available in four studies (556 participants). Participants in the NLT group experienced a lower rate of all-cause hospital admissions (RR 0.80, 95% CI 0.72 to 0.88, high-quality evidence) and fewer hospital admissions related to heart failure (RR 0.51, 95% CI 0.36 to 0.72, moderate-quality evidence) compared to the usual-care group. Six studies (902 participants) examined all-cause mortality. All-cause mortality was also lower in the NLT group (RR 0.66, 95% CI 0.48 to 0.92, moderate-quality evidence) compared to usual care. Approximately 27 deaths could be avoided for every 1000 people receiving NLT of beta-adrenergic blocking agents, ACEIs, and ARBs. Only three studies (370 participants) reported outcomes on all-cause and heart failure-related event-free survival. Participants in the NLT group were more likely to remain event free compared to participants in the usual-care group (RR 0.60, 95% CI 0.46 to 0.77, moderate-quality evidence). Five studies (966 participants) reported on the number of participants reaching target dose of beta-adrenergic blocking agents. This was also higher in the NLT group compared to usual care (RR 1.99, 95% CI 1.61 to 2.47, low-quality evidence). However, there was a substantial degree of heterogeneity in this pooled analysis. We rated the risk of bias in these studies as high mainly due to a lack of clarity regarding incomplete outcome data, lack of reporting on adverse events associated with the intervention, and the inability to blind participants and personnel. Participants in the NLT group reached maximal dose of beta-adrenergic blocking agents in half the time compared with participants in usual care. Two studies reported on adverse events; one of these studies stated there were no adverse events, and the other study found one adverse event but did not specify the type or severity of the adverse event. AUTHORS' CONCLUSIONS: Participants in the NLT group experienced fewer hospital admissions for any cause and an increase in survival and number of participants reaching target dose within a shorter time period. However, the quality of evidence regarding the proportion of participants reaching target dose was low and should be interpreted with caution. We found high-quality evidence supporting NLT as one strategy that may improve the optimisation of beta-adrenergic blocking agents resulting in a reduction in hospital admissions. Despite evidence of a dose-dependent relationship of beta-adrenergic blocking agents, ACEIs, and ARBs with improving outcomes in patients with HFrEF, the translation of this evidence into clinical practice is poor. NLT is one strategy that facilitates the implementation of this evidence into practice.

Failure to respond to food resource decline has catastrophic consequences for koalas in a high-density population in Southern Australia

Understanding the ability of koalas to respond to changes in their environment is critical for conservation of the species and their habitat. We monitored the behavioural response of koalas to declining food resources in manna gum (Eucalyptus viminalis) woodland at Cape Otway, Victoria, Australia, from September 2011 to November 2013. Over this period, koala population density increased from 10.1 to 18.4 koalas.ha-1. As a result of the high browsing pressure of this population, manna gum canopy condition declined with 71.4% manna gum being completely or highly defoliated in September 2013. Despite declining food resources, radio collared koalas (N = 30) exhibited high fidelity to small ranges (0.4-1.2 ha). When trees became severely defoliated in September 2013, koalas moved relatively short distances from their former ranges (mean predicted change in range centroid = 144 m) and remained in areas of 0.9 to 1.0 ha. This was despite the high connectivity of most manna gum woodland, and close proximity of the study site (< 3 km) to the contiguous mixed forest of the Great Otway National Park. Limited movement had catastrophic consequences for koalas with 71% (15/21) of radio collared koalas dying from starvation or being euthanased due to their poor condition between September and November 2013.

What factors contribute to failure of fieldwork placement? Perspectives of supervisors and university fieldwork educators

Failing a fieldwork placement can be a challenging and emotional experience. This study aimed to explore the perspectives of placement supervisors and university fieldwork educators (UFEs) of the factors that contribute to occupational therapy students failing placement. Twenty placement supervisors and four UFEs participated, and completed single instance surveys and interviews. Failure of a placement was noted to be a stressful experience for all stakeholders. Reasons identified for student failure included poor communication and reflection skills; non-disclosure of health issues and an inability to accept feedback. Placement supervisors highlighted that although failing a student was difficult, there was a need to uphold the values and standards of the profession. Strategies to facilitate placement success were identified.

Structural health monitoring: a practical approach to achieving in-situ and site-specific warning of pipeline corrosion and coating failure

An approach to achieving the ambitious goal of cost effectively extending the safe operation life of energy pipelines to, for instance, 100 years is the application of structural health monitoring and life prediction tools that are able to provide long-term remnant pipeline life prediction and in-situ pipeline condition monitoring. A critical step in pipeline structural health monitoring is the enhancement of technological capabilities that are required for quantifying the effects of key factors influencing buried pipeline corrosion and environmentally assisted materials degradation, and the development of condition monitoring technologies that are able to provide in-situ monitoring and site-specific warning of pipeline damage. This paper provides an overview of our current research aimed at developing new sensors for monitoring, categorising and quantifying the level and nature of external pipeline and coating damages under the combined effects of various inter-related variables and processes such as localised corrosion, coating damage and disbondment, cathodic shielding. The concept of in-situ monitoring and site-specific warning of pipeline corrosion is illustrated by a case of monitoring localised corrosion under disbonded coatings using a new corrosion monitoring probe. A basic principle that underpins the use of sensors to monitor localised corrosion has been presented: Localised corrosion and coating failure are not an accidental occurrence, it occurs as the result of fundamental thermodynamic instability of a metal exposed to a specific environment. Therefore corrosion and coating disbondment occurring on a pipeline will also occur on a sensor made of the same material and exposed to the same pipeline condition. Although the exact location of localised corrosion or coating disbondment could be difficult to pinpoint along the length of a buried pipeline, the ‘worst-case scenario’ and high risk pipeline sections and sites are predictable. Sensors can be embedded at these strategic sites to collect data that contain ‘predictor features’ signifying the occurrence of localised corrosion, CP failure, coating disbondment and degradation. Information from these sensors will enable pipeline owners to prioritise site survey and inspection operations, and to develop maintenance strategy to manage aged pipelines, rather than replace them.