Pressure ulcers in the adult intensive care unit : a literature review of patient risk factors and risk assessment scales

Background: Critically ill patients are at high risk for pressure ulcer (PrU) development due to their high acuity and the invasive nature of the multiple interventions and therapies they receive. With reported incidence rates of PrU development in the adult critical care population as high as 56%, the identification of patients at high risk of PrU development is essential. This paper will explore the association between PrU development and risk factors. It will also explore PrU development and the use of risk assessment scales for critically ill patients in adult intensive care units. Method: A literature search from 2000 to 2012 using the CINHAL, Cochrane Library, EBSCOHost, Medline (via EBSCOHost), PubMed, ProQuest and Google Scholar databases was conducted. Key words used were: pressure ulcer/s; pressure sore/s; decubitus ulcer/s; bed sore/s; critical care; intensive care; critical illness; prevalence; incidence; prevention; management; risk factor; risk assessment scale. Results: Nineteen articles were included in this review; eight studies addressing PrU risk factors, eight studies addressing risk assessment scales and three studies overlapping both. Results from the studies reviewed identified 28 intrinsic and extrinsic risk factors which may lead to PrU development. Development of a risk factor prediction model in this patient population, although beneficial, appears problematic due to many issues such as diverse diagnoses and subsequent patient needs. Additionally, several risk assessment instruments have been developed for early screening of patients at higher risk of developing PrU in the ICU. No existing risk assessment scales are valid for identification high risk critically ill patient,with the majority of scales potentially over-predicting patients at risk for PrU development. Conclusion: Research studies to inform the risk factors for potential pressure ulcer development are inconsistent. Additionally, there is no consistent or clear evidence which demonstrates any scale to better or more effective than another when used to identify the patients at risk for PrU development. Furthermore robust research is needed to identify the risk factors and develop valid scales for measuring the risk of PrU development in ICU.

The ability of YSR DSM-oriented depression scales to predict DSM-IV depression in young adults : a longitudinal study

Background The Achenbach child behaviour checklist (CBCL/YSR) is a widely used screening tool for affective problems. Several studies report good association between the checklists and psychiatric diagnoses; although with varying degrees of agreement. Most are cross-sectional studies involving adolescents referred to mental health services. This paper aims to evaluate the performance of the youth self report (YSR) empirical and DSM-oriented internalising scales in predicting later depressive disorders in young adults. Methods Sample was 2431 young adults from an Australian birth cohort study. The strength of association between the empirical and DSM-oriented scales assessed at 14 and 21 years and structured-interview derived depression in young adulthood (18 to 22 years) were tested using odds ratios, ROC analyses and related diagnostic efficiency tests (sensitivity, specificity, positive and negative predictive values). Results Adolescents with internalising symptoms were twice (OR 2.3, 95%CI 1.7 to 3.1) as likely to be diagnosed with DSM-IV depression by age 21. Use of DSM-oriented depressive scales did not improve the concordance between the internalising behaviour and DSM-IV diagnosed depression at age 14 (ORs ranged from 1.9 to 2.5). Limitations Some loss to follow-up over the 7-year gap between the two waves of follow-up. Conclusion DSM-oriented scales perform no better than the standard internalising or anxious/depressed scales in identifying young adults with later DSM-IV depressive disorder.

Predicting depressive and anxiety disorders with the YASR internalising scales (empirical and DSM-oriented)

Background The Achenbach problem behaviour scales (CBCL/YSR) are widely used. The DSM-oriented anxiety and depression scales have been created to improve concordance between Achenbach’s internalising scales and DSM-IV depression and anxiety. To date no study has examined the concurrent utility of the young adult (YASR) internalising scales, either the empirical or newly developed DSM-oriented depressive or anxiety scales. Methods A sample of 2,551 young adults, aged 18–23 years, from an Australian cohort study. The association between the empirical and DSM-oriented anxiety and depression scales were individually assessed against DSMIV depression and anxiety diagnoses derived from structured interview. Odds ratios, ROC analyses and diagnostic efficiency tests (sensitivity, specificity, positive and negative predictive values) were used to report findings. Results YASR empirical internalising scale predicted DSM-IV mood disorders (depression OR = 6.9, 95% CI 5.0–9.5; anxiety OR = 5.1, 95% CI 3.8–6.7) in the previous 12 months. DSM-oriented depressive or anxiety scales did not appear to improve the concordance with DSM-IV diagnosed depression or anxiety. The internalising scales were much more effective at identifying those with comorbid depression and anxiety, with Ors between 10.1 and 21.7 depending on the internalising scale used. Conclusion DSM-oriented scales perform no better than the standard internalising in identifying young adults with DSM-IV mood or anxiety disorder.

The ISR and ESR scales : measures of the project manager-stakeholder relationship

In this paper, we develop two stakeholder relationships scales. These scales assess project managers’ perceived competence in establishing and maintaining high quality, effective relationships with people internal to the project as well as those stakeholders who are external to the project. We developed the scales using an online survey study of three hundred and seventy three complex project managers from a sub-set of the Australian Defence Industry. Both the internal stakeholder relationships’ scale and the external stakeholder relationships’ scale demonstrated validity and reliability. This research has implications for the interpersonal work relationships’ literature and the stakeholder management literature. We recommend future research tests these scales with multiple samples, across different project types and project industries. The stakeholder relationships’ scales should be versatile enough to be applied to project management generally but are best suited to large-scale complex project environments.

A review of sedation scales for the cardiac catheterization laboratory

Sedation scales have the potential to facilitate effective procedural sedation and analgesia in the cardiac catheterization laboratory (CCL). For this potential to become realised, a scale that is suitable for use in the CCL either needs to be identified or developed. To identify sedation scales, a review of Medline and CINHAL was conducted. One sedation scale for the CCL, the NASPE SED, and 15 Intensive Care Unit (ICU) scales met the inclusion and exclusion criteria. Analysis of the scale’s item structures and psychometric properties was then performed. None of these scales were deemed suitable for use in the CCL. As such, further research is required to develop a new scale. The new scale should consist of more than one item because it will be the most effective for tracking the patient’s response to medications. Specific tests required to conduct a rigorous evaluation of the new scale’s psychometric properties are outlined in this paper.

The impact of spatial scales and spatial smoothing on the outcome of Bayesian spatial model

Discretization of a geographical region is quite common in spatial analysis. There have been few studies into the impact of different geographical scales on the outcome of spatial models for different spatial patterns. This study aims to investigate the impact of spatial scales and spatial smoothing on the outcomes of modelling spatial point-based data. Given a spatial point-based dataset (such as occurrence of a disease), we study the geographical variation of residual disease risk using regular grid cells. The individual disease risk is modelled using a logistic model with the inclusion of spatially unstructured and/or spatially structured random effects. Three spatial smoothness priors for the spatially structured component are employed in modelling, namely an intrinsic Gaussian Markov random field, a second-order random walk on a lattice, and a Gaussian field with Matern correlation function. We investigate how changes in grid cell size affect model outcomes under different spatial structures and different smoothness priors for the spatial component. A realistic example (the Humberside data) is analyzed and a simulation study is described. Bayesian computation is carried out using an integrated nested Laplace approximation. The results suggest that the performance and predictive capacity of the spatial models improve as the grid cell size decreases for certain spatial structures. It also appears that different spatial smoothness priors should be applied for different patterns of point data.

Towards bio-inspired place recognition over multiple spatial scales

This paper presents a new multi-scale place recognition system inspired by the recent discovery of overlapping, multi-scale spatial maps stored in the rodent brain. By training a set of Support Vector Machines to recognize places at varying levels of spatial specificity, we are able to validate spatially specific place recognition hypotheses against broader place recognition hypotheses without sacrificing localization accuracy. We evaluate the system in a range of experiments using cameras mounted on a motorbike and a human in two different environments. At 100% precision, the multiscale approach results in a 56% average improvement in recall rate across both datasets. We analyse the results and then discuss future work that may lead to improvements in both robotic mapping and our understanding of sensory processing and encoding in the mammalian brain.

Assessing the construct validity and reliability of the parental perception on antibiotics (PAPA) scales

Background: The overuse of antibiotics is becoming an increasing concern. Antibiotic resistance, which increases both the burden of disease, and the cost of health services, is perhaps the most profound impact of antibiotics overuse. Attempts have been made to develop instruments to measure the psychosocial constructs underlying antibiotics use, however, none of these instruments have undergone thorough psychometric validation. This study evaluates the psychometric properties of the Parental Perceptions on Antibiotics (PAPA) scales. The PAPA scales attempt to measure the factors influencing parental use of antibiotics in children. Methods: 1111 parents of children younger than 12 years old were recruited from primary schools’ parental meetings in the Eastern Province of Saudi Arabia from September 2012 to January 2013. The structure of the PAPA instrument was validated using Confirmatory Factor Analysis (CFA) with measurement model fit evaluated using the raw and scaled χ2, Goodness of Fit Index, and Root Mean Square Error of Approximation. Results: A five-factor model was confirmed with the model showing good fit. Constructs in the model include: Knowledge and Beliefs, Behaviors, Sources of information, Adherence, and Awareness about antibiotics resistance. The instrument was shown to have good internal consistency, and good discriminant and convergent validity. Conclusion: The availability of an instrument able to measure the psychosocial factors underlying antibiotics usage allows the risk factors underlying antibiotic use and overuse to now be investigated.

Feral pig populations are structured at fine spatial scales in tropical Queensland, Australia

Feral pigs occur throughout tropical far north Queensland, Australia and are a significant threat to biodiversity and World Heritage values, agriculture and are a vector of infectious diseases. One of the constraints on long-lasting, local eradication of feral pigs is the process of reinvasion into recently controlled areas. This study examined the population genetic structure of feral pigs in far north Queensland to identify the extent of movement and the scale at which demographically independent management units exist. Genetic analysis of 328 feral pigs from the Innisfail to Tully region of tropical Queensland was undertaken. Seven microsatellite loci were screened and Bayesian clustering methods used to infer population clusters. Sequence variation at the mitochondrial DNA control region was examined to identify pig breed. Significant population structure was identified in the study area at a scale of 25 to 35 km, corresponding to three demographically independent management units (MUs). Distinct natural or anthropogenic barriers were not found, but environmental features such as topography and land use appear to influence patterns of gene flow. Despite the strong, overall pattern of structure, some feral pigs clearly exhibited ancestry from a MU outside of that from which they were sampled indicating isolated long distance dispersal or translocation events. Furthermore, our results suggest that gene flow is restricted among pigs of domestic Asian and European origin and non-random mating influences management unit boundaries. We conclude that the three MUs identified in this study should be considered as operational units for feral pig control in far north Queensland. Within a MU, coordinated and simultaneous control is required across farms, rainforest areas and National Park Estates to prevent recolonisation from adjacent localities.

Mechanics of microfilaments networks : a cross-scales study

The mechanical properties of microfilament networks are systematically summarized at different special scales in this paper. We have presented the mechanical models of single microfilaments and microfilament networks at microscale. By adopting a coarse-grained simulation strategy, the mechanical stability of microfilaments related cellular structures are analysed. Structural analysis is conducted to microfilament networks to understand the stress relaxation under compression. The nanoscale molecular mechanisms of the microfilaments deformation is also summarized from the viewpoint of molecular dynamics simulation. This paper provides the fundaments of multiscale modelling framework for the mechanical behaviours simulation of hierarchical microfilament networks.

Estimating local stream fish assemblage attributes: Sampling effort and efficiency at two spatial scales

As part of a wider study to develop an ecosystem-health monitoring program for wadeable streams of south-eastern Queensland, Australia, comparisons were made regarding the accuracy, precision and relative efficiency of single-pass backpack electrofishing and multiple-pass electrofishing plus supplementary seine netting to quantify fish assemblage attributes at two spatial scales (within discrete mesohabitat units and within stream reaches consisting of multiple mesohabitat units). The results demonstrate that multiple-pass electrofishing plus seine netting provide more accurate and precise estimates of fish species richness, assemblage composition and species relative abundances in comparison to single-pass electrofishing alone, and that intensive sampling of three mesohabitat units (equivalent to a riffle-run-pool sequence) is a more efficient sampling strategy to estimate reach-scale assemblage attributes than less intensive sampling over larger spatial scales. This intensive sampling protocol was sufficiently sensitive that relatively small differences in assemblage attributes (<20%) could be detected with a high statistical power (1-β > 0.95) and that relatively few stream reaches (<4) need be sampled to accurately estimate assemblage attributes close to the true population means. The merits and potential drawbacks of the intensive sampling strategy are discussed, and it is deemed to be suitable for a range of monitoring and bioassessment objectives.

An investigation of the impact of various geographical scales for the specification of spatial dependence

Ecological studies are based on characteristics of groups of individuals, which are common in various disciplines including epidemiology. It is of great interest for epidemiologists to study the geographical variation of a disease by accounting for the positive spatial dependence between neighbouring areas. However, the choice of scale of the spatial correlation requires much attention. In view of a lack of studies in this area, this study aims to investigate the impact of differing definitions of geographical scales using a multilevel model. We propose a new approach -- the grid-based partitions and compare it with the popular census region approach. Unexplained geographical variation is accounted for via area-specific unstructured random effects and spatially structured random effects specified as an intrinsic conditional autoregressive process. Using grid-based modelling of random effects in contrast to the census region approach, we illustrate conditions where improvements are observed in the estimation of the linear predictor, random effects, parameters, and the identification of the distribution of residual risk and the aggregate risk in a study region. The study has found that grid-based modelling is a valuable approach for spatially sparse data while the SLA-based and grid-based approaches perform equally well for spatially dense data.