376 resultados para Diseases without mortality
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A Delay Tolerant Network (DTN) is one where nodes can be highly mobile, with long message delay times forming dynamic and fragmented networks. Traditional centralised network security is difficult to implement in such a network, therefore distributed security solutions are more desirable in DTN implementations. Establishing effective trust in distributed systems with no centralised Public Key Infrastructure (PKI) such as the Pretty Good Privacy (PGP) scheme usually requires human intervention. Our aim is to build and compare different de- centralised trust systems for implementation in autonomous DTN systems. In this paper, we utilise a key distribution model based on the Web of Trust principle, and employ a simple leverage of common friends trust system to establish initial trust in autonomous DTN’s. We compare this system with two other methods of autonomously establishing initial trust by introducing a malicious node and measuring the distribution of malicious and fake keys. Our results show that the new trust system not only mitigates the distribution of fake malicious keys by 40% at the end of the simulation, but it also improved key distribution between nodes. This paper contributes a comparison of three de-centralised trust systems that can be employed in autonomous DTN systems.
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Background & aims The Australasian Nutrition Care Day Survey (ANCDS) ascertained if malnutrition and poor food intake are independent risk factors for health-related outcomes in Australian and New Zealand hospital patients. Methods Phase 1 recorded nutritional status (Subjective Global Assessment) and 24-h food intake (0, 25, 50, 75, 100% intake). Outcomes data (Phase 2) were collected 90-days post-Phase 1 and included length of hospital stay (LOS), readmissions and in-hospital mortality. Results Of 3122 participants (47% females, 65 ± 18 years) from 56 hospitals, 32% were malnourished and 23% consumed ≤ 25% of the offered food. Malnourished patients had greater median LOS (15 days vs. 10 days, p < 0.0001) and readmissions rates (36% vs. 30%, p = 0.001). Median LOS for patients consuming ≤ 25% of the food was higher than those consuming ≤ 50% (13 vs. 11 days, p < 0.0001). The odds of 90-day in-hospital mortality were twice greater for malnourished patients (CI: 1.09–3.34, p = 0.023) and those consuming ≤ 25% of the offered food (CI: 1.13–3.51, p = 0.017), respectively. Conclusion The ANCDS establishes that malnutrition and poor food intake are independently associated with in-hospital mortality in the Australian and New Zealand acute care setting.
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Rationale: The Australasian Nutrition Care Day Survey (ANCDS) evaluated if malnutrition and decreased food intake are independent risk factors for negative outcomes in hospitalised patients. Methods: A multicentre (56 hospitals) cross-sectional survey was conducted in two phases. Phase 1 evaluated nutritional status (defined by Subjective Global Assessment) and 24-hour food intake recorded as 0, 25, 50, 75, and 100% intake. Phase 2 data, which included length of stay (LOS), readmissions and mortality, were collected 90 days post-Phase 1. Logistic regression was used to control for confounders: age, gender, disease type and severity (using Patient Clinical Complexity Level scores). Results: Of 3122 participants (53% males, mean age: 65±18 years) 32% were malnourished and 23% consumed�25% of the offered food. Median LOS for malnourished (MN) patients was higher than well-nourished (WN) patients (15 vs. 10 days, p<0.0001). Median LOS for patients consuming �25% of the food was higher than those consuming �50% (13 vs. 11 days, p<0.0001). MN patients had higher readmission rates (36% vs. 30%, p = 0.001). The odds ratios of 90-day in-hospital mortality were 1.8 times greater for MN patients (CI: 1.03 3.22, p = 0.04) and 2.7 times greater for those consuming �25% of the offered food (CI: 1.54 4.68, p = 0.001). Conclusion: The ANCDS demonstrates that malnutrition and/or decreased food intake are associated with longer LOS and readmissions. The survey also establishes that malnutrition and decreased food intake are independent risk factors for in-hospital mortality in acute care patients; and highlights the need for appropriate nutritional screening and support during hospitalisation. Disclosure of Interest: None Declared.
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BACKGROUND: Studies have shown that nurse staffing levels, among many other factors in the hospital setting, contribute to adverse patient outcomes. Concerns about patient safety and quality of care have resulted in numerous studies being conducted to examine the relationship between nurse staffing levels and the incidence of adverse patient events in both general wards and intensive care units. AIM: The aim of this paper is to review literature published in the previous 10 years which examines the relationship between nurse staffing levels and the incidence of mortality and morbidity in adult intensive care unit patients. METHODS: A literature search from 2002 to 2011 using the MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, and Australian digital thesis databases was undertaken. The keywords used were: intensive care; critical care; staffing; nurse staffing; understaffing; nurse-patient ratios; adverse outcomes; mortality; ventilator-associated pneumonia; ventilator-acquired pneumonia; infection; length of stay; pressure ulcer/injury; unplanned extubation; medication error; readmission; myocardial infarction; and renal failure. A total of 19 articles were included in the review. Outcomes of interest are patient mortality and morbidity, particularly infection and pressure ulcers. RESULTS: Most of the studies were observational in nature with variables obtained retrospectively from large hospital databases. Nurse staffing measures and patient outcomes varied widely across the studies. While an overall statistical association between increased nurse staffing levels and decreased adverse patient outcomes was not found in this review, most studies concluded that a trend exists between increased nurse staffing levels and decreased adverse events. CONCLUSION: While an overall statistical association between increased nurse staffing levels and decreased adverse patient outcomes was not found in this review, most studies demonstrated a trend between increased nurse staffing levels and decreased adverse patient outcomes in the intensive care unit which is consistent with previous literature. While further more robust research methodologies need to be tested in order to more confidently demonstrate this association and decrease the influence of the many other confounders to patient outcomes; this would be difficult to achieve in this field of research.
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Purpose: To determine whether neuroretinal function differs in healthy persons with and without common risk gene variants for age- related macular degeneration (AMD) and no ophthalmoscopic signs of AMD, and to compare those findings in persons with manifest early AMD. Methods and Participants: Neuroretinal function was assessed with the multifocal electroretinogram (mfERG) (VERIS, Redwood City, CA,) in 32 participants (22 healthy persons with no clinical signs of AMD and 10 early AMD patients). The 22 healthy participants with no AMD were risk genotypes for either the CFH (rs380390) and/or ARMS2 (rs10490920). We used a slow flash mfERG paradigm (3 inserted frames) and a 103 hexagon stimulus array. Recordings were made with DTL electrodes; fixation and eye movements were monitored online. Trough N1 to peak P1 (N1P1) response densities and P1-implicit times (IT) were analysed in 5 concentric rings. Results: N1P1 response densities (mean ± SD) for concentric rings 1-3 were on average significantly higher in at-risk genotypes (ring 1: 17.97 nV/deg2 ± 1.9, ring 2: 11.7 nV/deg2 ±1.3, ring 3: 8.7 nV/deg2 ± 0.7) compared to those without risk (ring 1: 13.7 nV/deg2 ± 1.9, ring 2: 9.2 nV/deg2 ±0.8, ring 3: 7.3 nV/deg2 ± 1.1) and compared to persons with early AMD (ring 1: 15.3 nV/deg2 ± 4.8, ring 2: 9.1 nV/deg2 ±2.3, ring 3 nV/deg2: 7.3± 1.3) (p<0.5). The group implicit times, P1-ITs for ring 1 were on average delayed in the early AMD patients (36.4 ms ± 1.0) compared to healthy participants with (35.1 ms ± 1.1) or without risk genotypes (34.8 ms ±1.3), although these differences were not significant. Conclusion: Neuroretinal function in persons with normal fundi can be differentiated into subgroups based on their genetics. Increased neuroretinal activity in persons who carry AMD risk genotypes may be due to genetically determined subclinical inflammatory and/or histological changes in the retina. Assessment of neuroretinal function in healthy persons genetically susceptible to AMD may be a useful early biomarker before there is clinical manifestation of AMD.
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Deterioration of air quality in Indian megacities (Delhi, Mumbai or Kolkata) is much more significant than that observed in the megacities of developed countries. Densely packed high-rise buildings restrict the self-cleaning capabilities of Indian megacities. Also, the ever growing number of on-road vehicles, resuspension of the dust, and anthropogenic activities exacerbate the levels of ambient air pollution, which is in turn breathed by urban dwellers. Pollution levels exceeding the standards on a regular basis often result in a notable increase in morbidity and mortality. This article discusses the challenges faced by Indian megacities in their quest for sustainable growth, without compromising the air quality and urban way of life.
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The ageing population is increasing worldwide, as are a range of chronic diseases, conditions, and physical and cognitive disabilities associated with later life. The older population is also neurologically diverse, with unique and specific challenges around mobility and engagement with the urban environment. Older people tend to interact less with cities and neighbourhoods, putting them at risk of further illnesses and co-morbidities associated with being less physically and socially active. Empirical evidence has shown that reduced access to healthcare services, health-related resources and social interaction opportunities is associated with increases in morbidity and premature mortality. While it is crucial to respond to the needs of this ageing population, there is insufficient evidence for interventions regarding their experiences of public space from the vantage point of neurodiversity. This paper provides a conceptual and methodological framework to investigate relationships between the sensory and cognitive abilities of older people, and their use and negotiation of the urban environment. The paper will refer to a case example of the city of Logan, an urban area in Queensland, Australia, where current urban development provides opportunities for the design of spaces that take experiences of neurodiversity into account. The framework will inform the development of principles for urban design for increasingly neurologically diverse populations.
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Nanotechnology is a vigorous research area and one of its important applications is in biomedical sciences. Among biomedical applications, targeted drug delivery is one of the most extensively studied subjects. Nanostructured particles and scaffolds have been widely studied for increasing treatment efficacy and specificity of present treatment approaches. Similarly, this technique has been used for treating bone diseases including bone regeneration. In this review, we have summarized and highlighted the recent advancement of nanostructured particles and scaffolds for the treatment of cancer bone metastasis, osteosarcoma, bone infections and inflammatory diseases, osteoarthritis, as well as for bone regeneration. Nanoparticles used to deliver deoxyribonucleic acid and ribonucleic acid molecules to specific bone sites for gene therapies are also included. The investigation of the implications of nanoparticles in bone diseases have just begun, and has already shown some promising potential. Further studies have to be conducted, aimed specifically at assessing targeted delivery and bioactive scaffolds to further improve their efficacy before they can be used clinically
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Background: Ureaplasma species are the most prevalent isolates from women who deliver preterm. The MBA, a surface exposed lipoprotein, is a key virulence factor of ureaplasmas. We investigated MBA variation after chronic and acute intra-amniotic (IA) ureaplasma infections. Method: U. parvum serovar 3 (2x104 colony-forming-units) was injected IA into pregnant ewes at: 55 days gestation (d, term = 145d) (n=8); 117d (n=8) and 121d (n=8). Fetuses were delivered surgically (124d) and ureaplasmas cultured from amniotic fluid (AF), chorioamnion, fetal lung (FL) and umbilical cord were tested by western blot and PCR assays to demonstrate MBA and mba gene variation respectively. Tissue sections were sectioned and stained by haemotoxylin and eosin and inflammatory cell counts and pathology were reported (blinded to outcome). Results: Numerous MBA/mba variants were generated in vivo after chronic exposure to ureaplasma infection but after acute infection no variants (3d) or very few variants (7d) were generated. Identical MBA variants were detected within the AF and FL but different ureaplasma variants were detected within chorioamnion specimens. The severity of inflammation within chronically infected tissues varied between animals ranging from no inflammation to severe inflammation with/without fibrosis. Chorioamnion, FL and cord from the same animal demonstrated the same degree of inflammation. Conclusions: MBA/mba variation in vivo occurred after the initiation of the host immune response and we propose that ureaplasmas vary the MBA antigen to evade the host immune response. In some animals there was no inflammation despite colonisation with high numbers of ureaplasmas.
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Most existing research on maintenance optimisation for multi-component systems only considers the lifetime distribution of the components. When the condition-based maintenance (CBM) strategy is adopted for multi-component systems, the strategy structure becomes complex due to the large number of component states and their combinations. Consequently, some predetermined maintenance strategy structures are often assumed before the maintenance optimisation of a multi-component system in a CBM context. Developing these predetermined strategy structure needs expert experience and the optimality of these strategies is often not proofed. This paper proposed a maintenance optimisation method that does not require any predetermined strategy structure for a two-component series system. The proposed method is developed based on the semi-Markov decision process (SMDP). A simulation study shows that the proposed method can identify the optimal maintenance strategy adaptively for different maintenance costs and parameters of degradation processes. The optimal maintenance strategy structure is also investigated in the simulation study, which provides reference for further research in maintenance optimisation of multi-component systems.
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Background Individual exposure to ultraviolet radiation (UVR) is challenging to measure, particularly for diseases with substantial latency periods between first exposure and diagnosis of outcome, such as cancer. To guide the choice of surrogates for long-term UVR exposure in epidemiologic studies, we assessed how well stable sun-related individual characteristics and environmental/meteorological factors predicted daily personal UVR exposure measurements. Methods We evaluated 123 United States Radiologic Technologists subjects who wore personal UVR dosimeters for 8 hours daily for up to 7 days (N = 837 days). Potential predictors of personal UVR derived from a self-administered questionnaire, and public databases that provided daily estimates of ambient UVR and weather conditions. Factors potentially related to personal UVR exposure were tested individually and in a model including all significant variables. Results The strongest predictors of daily personal UVR exposure in the full model were ambient UVR, latitude, daily rainfall, and skin reaction to prolonged sunlight (R2 = 0.30). In a model containing only environmental and meteorological variables, ambient UVR, latitude, and daily rainfall were the strongest predictors of daily personal UVR exposure (R2 = 0.25). Conclusions In the absence of feasible measures of individual longitudinal sun exposure history, stable personal characteristics, ambient UVR, and weather parameters may help estimate long-term personal UVR exposure.
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Dear Editor We thank Dr Klek for his interest in our article and giving us the opportunity to clarify our study and share our thoughts. Our study looks at the prevalence of malnutrition in an acute tertiary hospital and tracked the outcomes prospectively.1 There are a number of reasons why we chose Subjective Global Assessment (SGA) to determine the nutritional status of patients. Firstly, we took the view that nutrition assessment tools should be used to determine nutrition status and diagnose presence and severity of malnutrition; whereas the purpose of nutrition screening tools are to identify individuals who are at risk of malnutrition. Nutritional assessment rather than screening should be used as the basis for planning and evaluating nutrition interventions for those diagnosed with malnutrition. Secondly, Subjective Global Assessment (SGA) has been well accepted and validated as an assessment tool to diagnose the presence and severity of malnutrition in clinical practice.2, 3 It has been used in many studies as a valid prognostic indicator of a range of nutritional and clinical outcomes.4, 5, 6 On the other hand, Malnutrition Universal Screening Tool (MUST)7 and Nutrition Risk Screening 2002 (NRS 2002)8 have been established as screening rather than assessment tools.
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The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.
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Objective: To examine the effects of extremely cold and hot temperatures on ischaemic heart disease (IHD) mortality in five cities (Beijing, Tianjin, Shanghai, Wuhan and Guangzhou) in China; and to examine the time relationships between cold and hot temperatures and IHD mortality for each city. Design: A negative binomial regression model combined with a distributed lag non-linear model was used to examine city-specific temperature effects on IHD mortality up to 20 lag days. A meta-analysis was used to pool the cold effects and hot effects across the five cities. Patients: 16 559 IHD deaths were monitored by a sentinel surveillance system in five cities during 2004–2008. Results: The relationships between temperature and IHD mortality were non-linear in all five cities. The minimum-mortality temperatures in northern cities were lower than in southern cities. In Beijing, Tianjin and Guangzhou, the effects of extremely cold temperatures were delayed, while Shanghai and Wuhan had immediate cold effects. The effects of extremely hot temperatures appeared immediately in all the cities except Wuhan. Meta-analysis showed that IHD mortality increased 48% at the 1st percentile of temperature (extremely cold temperature) compared with the 10th percentile, while IHD mortality increased 18% at the 99th percentile of temperature (extremely hot temperature) compared with the 90th percentile. Conclusions: Results indicate that both extremely cold and hot temperatures increase IHD mortality in China. Each city has its characteristics of heat effects on IHD mortality. The policy for response to climate change should consider local climate–IHD mortality relationships.
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Mortality and cost outcomes of elderly intensive care unit (ICU) trauma patients were characterised in a retrospective cohort study from an Australian tertiary ICU. Trauma patients admitted between January 2000 and December 2005 were grouped into three major age categories: aged ≥65 years admitted into ICU (n=272); aged ≥65 years admitted into general ward (n=610) and aged <65 years admitted into ICU (n=1617). Hospital mortality predictors were characterised as odds ratios (OR) using logistic regression. The impact of predictor variables on (log) total hospital-stay costs was determined using least squares regression. An alternate treatment-effects regression model estimated the mortality cost-effect as an endogenous variable. Mortality predictors (P ≤0.0001, comparator: ICU ≥65 years, ventilated) were: ICU <65 not-ventilated (OR 0.014); ICU <65 ventilated (OR 0.090); ICU age ≥65 not-ventilated (OR 0.061) and ward ≥65 (OR 0.086); increasing injury severity score and increased Charlson comorbidity index of 1 and 2, compared with zero (OR 2.21 [1.40 to 3.48] and OR 2.57 [1.45 to 4.55]). The raw mean daily ICU and hospital costs in A$ 2005 (US$) for age <65 and ≥65 to ICU, and ≥65 to the ward were; for year 2000: ICU, $2717 (1462) and $2777 (1494); hospital, $1837 (988) and $1590 (855); ward $933 (502); for year 2005: ICU, $3202 (2393) and $3086 (2307); hospital, $1938 (1449) and $1914 (1431); ward $1180 (882). Cost increments were predicted by age ≥65 and ICU admission, increasing injury severity score, mechanical ventilation, Charlson comorbidity index increments and hospital survival. Mortalitycost-effect was estimated at -63% by least squares regression and -82% by treatment-effects regression model. Patient demographic factors, injury severity and its consequences predict both cost and survival in trauma. The cost mortality effect was biased upwards by conventional least squares regression estimation.