Palliative care phase : inter-rater reliability and acceptability in a national study

Background: The concept of palliative care consisting of five distinct, clinically meaningful, phases (stable, unstable, deteriorating, terminal and bereavement) was developed in Australia about 20 years ago and is used routinely for communicating clinical status, care planning, quality improvement and funding. Aim: To test the reliability and acceptability of revised definitions of Palliative Care Phase. Design: Multi-centre cross-sectional study involving pairs of clinicians independently rating patients according to revised definitions of Palliative Care Phase. Setting/participants: Clinicians from 10 Australian palliative care services, including 9 inpatient units and 1 mixed inpatient/community-based service. Results: A total of 102 nursing and medical clinicians participated, undertaking 595 paired assessments of 410 patients, of which 90.7% occurred within 2 h. Clinicians rated 54.8% of patients in the stable phase, 15.8% in the unstable phase, 20.8% in the deteriorating phase and 8.7% in the terminal phase. Overall agreement between clinicians’ rating of Palliative Care Phase was substantial (kappa = 0.67; 95% confidence interval = 0.61–0.70). A moderate level of inter-rater reliability was apparent across all participating sites. The results indicated that Palliative Care Phase was an acceptable measure, with no significant difficulties assigning patients to a Palliative Care Phase and a good fit between assessment of phase and the definition of that phase. The most difficult phase to distinguish from other phases was the deteriorating phase. Conclusion: Policy makers, funders and clinicians can be confident that Palliative Care Phase is a reliable and acceptable measure that can be used for care planning, quality improvement and funding purposes.

A two-stage item recommendation method using probabilistic ranking with reconstructed tensor model

In a tag-based recommender system, the multi-dimensional correlation should be modeled effectively for finding quality recommendations. Recently, few researchers have used tensor models in recommendation to represent and analyze latent relationships inherent in multi-dimensions data. A common approach is to build the tensor model, decompose it and, then, directly use the reconstructed tensor to generate the recommendation based on the maximum values of tensor elements. In order to improve the accuracy and scalability, we propose an implementation of the -mode block-striped (matrix) product for scalable tensor reconstruction and probabilistically ranking the candidate items generated from the reconstructed tensor. With testing on real-world datasets, we demonstrate that the proposed method outperforms the benchmarking methods in terms of recommendation accuracy and scalability.

A tag-based personalized item recommendation system using tensor modeling and topic model approaches

This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

eHealth and the modern society

The integration of Information and Communication Technologies (ICT) into healthcare processes “eHealth” is driving enormous change in healthcare delivery and productivity. The transformations empower patients and present opportunities for new synergies between healthcare professionals, clinical decision makers, policy makers and educators. Technologies that are directly driving changes include Tele-medicine, Electronic health records (EHR), Standards to ensure computer systems inter-operate, Decision support systems, Data mining and easy access to medical information. This workshop provides an introduction to key informatics initiatives in eHealth using real examples and suggests how applications can be applied to modern society.

Information and communication technologies transform the practice of medicine

Information and Communication Technologies are dramatically transforming Allopathic medicine. Technological developments including Tele-medicine, Electronic health records, Standards to ensure computer systems inter-operate, Data mining, Simulation, Decision Support and easy access to medical information each contribute to empowering patients in new ways and change the practice of medicine. To date, informatics has had little impact on Ayurvedic medicine. This tutorial provides an introduction to key informatics initiatives in Allopothic medicine using real examples and suggests how applications can be applied to Ayurvedic medicine.

Modeling conditional correlations of asset returns : a smooth transition approach

In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM–test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five frequently traded stocks in the S&P 500 stock index completes the paper.

A high and low fear phenotype mouse model

Fear-related illnesses such as post-traumatic stress disorder (PTSD) impose a tremendous burden on individual quality of life, families, and the national economy. In the military population, 17-20% of services members returning from deployment are diagnosed with PTSD. While treatments have improved for PTSD and are helpful for some, many people continue to suffer despite therapy. The aim of this research is to examine fear memory behaviourally and at the cellular level in the amygdala by using a unique inter-cross strain of high and low fear phenotype mice. An extended outcross C57BL/6J x DBA/2J (F8) are selected for high or low Pavlovian fear memory to context and cue. On presentation of either the original learning context or the cue (tone) mice display high or low levels of freezing as a behavioural measure of fear. In order to identify key aspects of the cellular basis of this difference in fear memory behaviour we are making measurements of protein levels and neuron numbers of a known pathway involved in the consolidation of a long term fear memory (pMAPK). Ongoing studies aim to determine if high fear behaviour is associated with differential signalling in the lateral amygdala compared to low fear behaviour. Additionally, by blocking this pathway in the lateral amygdala (LA), we aim to reduce fear behaviour following Pavlovian fear conditioning. This research will help to unravel the cellular mechanisms underlying high fear behaviour and advance the field toward targeted treatment and improved outcomes, ultimately improving human quality of life.

Structure and palaeoenvironmental implications of inter-branch coenosteum-rich skeleton in corymbose Acropora species

Coral reefs provide an increasingly important archive of palaeoclimate data that can be used to constrain climate model simulations. Reconstructing past environmental conditions may also provide insights into the potential of reef systems to survive changes in the Earth’s climate. Reef-based palaeoclimate reconstructions are predominately derived from colonies of massive Porites, with the most abundant genus in the Indo-Pacific—Acropora—receiving little attention owing to their branching growth trajectories, high extension rates and secondary skeletal thickening. However, inter-branch skeleton (consisting of both coenosteum and corallites) near the bases of corymbose Acropora colonies holds significant potential as a climate archive. This region of Acropora skeleton is atypical, having simple growth trajectories with parallel corallites, approximately horizontal density banding, low apparent extension rates and a simple microstructure with limited secondary thickening. Hence, inter-branch skeleton in Acropora bears more similarities to the coralla of massive corals, such as Porites, than to traditional Acropora branches. Cyclic patterns of Sr/Ca ratios in this structure suggest that the observed density banding is annual in nature, thus opening up the potential to use abundant corymbose Acropora for palaeoclimate reconstruction.

Item reputation-aware recommender systems

Recommender systems provide personalized advice for customers online based on their own preferences, while reputation systems generate a community advice on the quality of items on the Web. Both systems use users’ ratings to generate their output. In this paper, we propose to combine reputation models with recommender systems to enhance the accuracy of recommendations. The main contributions include two methods for merging two ranked item lists which are generated based on recommendation scores and reputation scores, respectively, and a personalized reputation method to generate item reputations based on users’ interests. The proposed merging methods can be applicable to any recommendation methods and reputation methods, i.e., they are independent from generating recommendation scores and reputation scores. The experiments we conducted showed that the proposed methods could enhance the accuracy of existing recommender systems.

An efficient tagging data interpretation and representation scheme for item recommendation

A tag-based item recommendation method generates an ordered list of items, likely interesting to a particular user, using the users past tagging behaviour. However, the users tagging behaviour varies in different tagging systems. A potential problem in generating quality recommendation is how to build user profiles, that interprets user behaviour to be effectively used, in recommendation models. Generally, the recommendation methods are made to work with specific types of user profiles, and may not work well with different datasets. In this paper, we investigate several tagging data interpretation and representation schemes that can lead to building an effective user profile. We discuss the various benefits a scheme brings to a recommendation method by highlighting the representative features of user tagging behaviours on a specific dataset. Empirical analysis shows that each interpretation scheme forms a distinct data representation which eventually affects the recommendation result. Results on various datasets show that an interpretation scheme should be selected based on the dominant usage in the tagging data (i.e. either higher amount of tags or higher amount of items present). The usage represents the characteristic of user tagging behaviour in the system. The results also demonstrate how the scheme is able to address the cold-start user problem.

An acute cough-specific quality of life questionnaire for children: Development and validation

Background Patient-relevant outcome measures are essential for high-quality clinical research, and quality-of-life (QoL) tools are the current standard. Currently, there is no validated children's acute cough-specific QoL questionnaire. Objective The objective of this study was to develop and validate the Parent-proxy Children's Acute Cough-specific QoL Questionnaire (PAC-QoL). Methods Using focus groups, a 48-item PAC-QoL questionnaire was developed and later reduced to 16 items by using the clinical impact method. Parents of children with a current acute cough (<2 weeks) at enrollment completed 2 validated cough score measures, the preliminary 48-item PAC-QoL, and 3 other questionnaires (the State Trait Anxiety Inventory [STAI], the Short-Form 8-item 24-hour recall Health Survey [SF-8], and the Depression, Anxiety, and Stress 21-item Scale [DASS21]). All measures were repeated on days 3 and 14. Results The median age of the 155 children enrolled was 2.3 years (interquartile range, 1.3-4.6). Median cough duration at enrollment was 3 days (interquartile range, 2-5). The reduced 16-item scale had high internal consistency (Cronbach α = 0.95). Evidence for repeatability and criterion validity was shown by significant correlations between the domains and total PAC-QoL scores and the SF-8 (r = −0.36 and −0.51), STAI (r = −0.27 and −0.39), and DASS21 (r = −0.32 and −0.41) scales on days 0 and 3, respectively. The final PAC-QoL questionnaire was sensitive to change over time, with changes significantly relating to changes in cough score measures (P < .001). Conclusion The 16-item PAC-QoL is a reliable and valid outcome measure that assesses QoL related to childhood acute cough at a given time point and reflects changes in acute cough-specific QoL over time.

Comparison of eight published lumbar spine finite element models

Due to its ability to represent intricate systems with material nonlinearities as well as irregular loading, boundary, geometrical and material domains, the finite element (FE) method has been recognized as an important computational tool in spinal biomechanics. Current FE models generally account for a single distinct spinal geometry with one set of material properties despite inherently large inter-subject variability. The uncertainty and high variability in tissue material properties, geometry, loading and boundary conditions has cast doubt on the reliability of their predictions and comparability with reported in vitro and in vivo values. A multicenter study was undertaken to compare the results of eight well-established models of the lumbar spine that have been developed, validated and applied for many years. Models were subjected to pure and combined loading modes and their predictions were compared to in vitro and in vivo measurements for intervertebral rotations, disc pressures and facet joint forces. Under pure moment loading, the predicted L1-5 rotations of almost all models fell within the reported in vitro ranges; their median values differed on average by only 2° for flexion-extension, 1° for lateral bending and 5° for axial rotation. Predicted median facet joint forces and disc pressures were also in good agreement with previously published median in vitro values. However, the ranges of predictions were larger and exceeded the in vitro ranges, especially for facet joint forces. For all combined loading modes, except for flexion, predicted median segmental intervertebral rotations and disc pressures were in good agreement with in vivo values. The simulations yielded median facet joint forces of 0 N in flexion, 38 N in extension, 14 N in lateral bending and 60 N in axial rotation that could not be validated due to the paucity of in vivo facet joint forces. In light of high inter-subject variability, one must be cautious when generalizing predictions obtained from one deterministic model. This study demonstrates however that the predictive power increases when FE models are combined together. The median of individual numerical results can hence be used as an improved tool in order to estimate the response of the lumbar spine.

Three-dimensional geological modelling of the Galilee and central Eromanga basins, Australia: New insights into aquifer/aquitard geometry and potential influence of faults on inter-connectivity

Study region The Galilee and Eromanga basins are located in central Queensland, Australia. Both basins are components of the Great Artesian Basin which host some of the most significant groundwater resources in Australia. Study focus This study evaluates the influence of regional faults on groundwater flow in an aquifer/aquitard interbedded succession that form one of the largest Artesian Basins in the world. In order to assess the significance of regional faults as potential barriers or conduits to groundwater flow, vertical displacements of the major aquifers and aquitards were studied at each major fault and the general hydraulic relationship of units that are juxtaposed by the faults were considered. A three-dimensional (3D) geological model of the Galilee and Eromanga basins was developed based on integration of well log data, seismic surfaces, surface geology and elevation data. Geological structures were mapped in detail and major faults were characterised. New hydrological insights for the region Major faults that have been described in previous studies have been confirmed within the 3D geological model domain and a preliminary assessment of their hydraulic significance has been conducted. Previously unknown faults such as the Thomson River Fault (herein named) have also been identified in this study.