11 research outputs found

    Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

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    Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

    Monitoring vegetation state in the central Iraq using Landsat-8 satellite data

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    Tokareva, O. S., Pasko, O. A., Majid, S. M., & Cabral, P. (2020). МОНИТОРИНГ СОСТОЯНИЯ РАСТИТЕЛЬНОГО ПОКРОВА ТЕРРИТОРИИ ЦЕНТРАЛЬНОГО ИРАКА С ИСПОЛЬЗОВАНИЕМ СПУТНИКОВЫХ ДАННЫХ LANDSAT-8. [ Monitoring vegetation state in the central Iraq using Landsat-8 satellite data ]. Bulletin of the Tomsk Polytechnic University, Geo Assets Engineering, 331(6), 19-31. https://doi.org/10.18799/24131830/2020/6/2671The relevance of the research is caused by the need to obtain objective information about the patterns of territorial and temporal variability of vegetation state and the factors that determine it for the most effective use of lands in extreme natural and socio-economic conditions in the Republic of Iraq. The aim of the research is to analyze the dynamics of vegetation of territories of the four provinces in Central Iraq using the normalized difference vegetation index NDVI in the period from 2014 to 2017. The objects of the research are territories of Central Iraq: Babil, Baghdad, Wasit and Diyala. The subject of the study is temporal-territorial variability of vegetation state. Methods: remote sensing, thematic mapping, image processing, spatial data analysis, statistical analysis. Results. Patterns of temporarily-territorial dynamics of vegetation state in Central Iraq were revealed using vegetation index NDVI calculated with remote sensing data obtained by Landsat-8. Regional features of the vegetation structure and the rate of its state change were established. The maximum areas of non-vegetated territories were found in Baghdad and Wasit; covered by vegetation of most classes – also in Wasit; covered by dense vegetation – in Diyala, marked as well by minimum of barren areas. Babil is characterized by minimum area covered by vegetation. Baghdad in the studied indicators is intermediate. These patterns are poorly consistent with the absolute values of the province areas. They are caused by the prevailing economic conditions and are manifested in the qualitative and quantitative heterogeneity of the distribution of vegetation in the provinces. During the active stage of vegetation, from February to March, the variations in areas of non-vegetated territories, occupied by moderate and dense vegetation, are stable. At the same time, the variability of areas of territories with very dense vegetation is growing, with weak vegetation and vegetation of maximum density decreases. A correlation analysis between NDVI values and weather conditions did not reveal any significant relationships.publishersversionpublishe

    Assessment of state of cedar forests in Tomsk region using remote sensing data of the earth

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    Pasko, O. A., Tokareva, O. S., Alshaibi, A. J. A., Chernikova, T. Y., & Cabral, P. (2019). Оценка состояния припоселковых кедровников томской области с использованием данных дистанционного зондирования земли. [Assessment of state of cedar forests in Tomsk region using remote sensing data of the earth]. Bulletin of the Tomsk Polytechnic University, Geo Assets Engineering, 330(1), 98-109. https://doi.org/10.18799/24131830/2019/1/54The relevance of the research is caused by the necessity to obtain objective information on the condition of forests for their protection from fires, diseases and pests, as well as for forestry and logging production. The aim of the research is the quantitative and qualitative assessment of changes in the condition of cedar forests on the example of the Tomsk region using ground survey methods and Earth remote sensing data. The objects of the research are the 13 cedar forests located on forest lands and belonging to the forestry branch of institution «Tomsk forest management» in Tomsk region. Methods: thematic mapping of the territory; calculation of the indicator of the number of photosynthetically active biomass NDVI (Nor' malize Difference Vegetation Index) on space images of medium spatial resolution (30 m) from the satellites Landsat 5 (camera TM), 7 (camera ETM+) and 8 (camera OLI), obtained in the period from 2002 to 2015 from the archive of the US Geological Survey using the Internet service Earth Explorer; spatial analysis of data using geographic information technologies; statistical processing of the obtained results by correlation and regression analysis. Result. A comprehensive assessment of 13 cedar forests was given; the dynamics of NDVI values in the period from 2002 to 2017 was analyzed; the main reason (illegal logging, windfalls, fires and spread of pests) were determined; the cedar forests were grouped accor' ding to their status; the maximum values of NDVI were set for the Bogashovskiy and Belousovskiy cedar forests, the minimum values of NDVI were set for Aksenovskiy, Protopopovskiy, Plotnikovskiy cedar forests; positive correlations between NDVI values and tree state were shown: high correlation – with the vital index, and the average correlation – with the weighted average tree state category in the forest; reliable correlation of NDVI values of cedar trees with the amount of precipitation and the amount of temperatures have not been found (except for the Aksenovskiy cedar forest, characterized as «severely weakened»); the proposed approaches are applicable to the evaluation of any cedar forests.publishersversionpublishe

    Программное обеспечение для оценки динамики состояния растительного покрова с использованием данных спутникового мониторинга Земли

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    The article presents the results of software development for predictive maps modeling of the earth’s surface processes based on time-varying satellite data using the probabilistic and spatial characteristics of various types of the earth’s surface in the image. The analysis of existing methods for the assessment and modeling of the state of landscapes of various territories using satellite Earth monitoring data is presented. The review of existing systems of the earth’s surface dynamics analysis and their main advantages and disadvantages is given. The cellular automata method was used to implement the forecast. This method allows complex systems modeling using a simple set of rules and is the most convenient and accurate method for working with a space images. Algorithms and basic modeling parameters for using this method are described. The developed software makes it possible to forecast the state of the surface of the territories under consideration based on a series of time-varying data, and also to specify various modeling parameters in order to improve the accuracy of forecast maps. The results of the developed software testing with MODIS and Landsat data are presented, the accuracy of the forecast and the influence of simulation parameters on the result were estimatedВ статье изложены результаты разработки программного обеспечения для построения прогнозных карт развития процессов на земной поверхности на основе разновременных данных спутникового мониторинга с использованием вероятностных и пространственных характеристик различных типов земной поверхности на изображении. Представлен анализ существующих методов для оценки и моделирования состояния ландшафтов различных территорий с использованием данных спутникового мониторинга Земли. Приведен обзор существующих систем анализа динамики земной поверхности, их основных достоинств и недостатков. Для разработки использован метод клеточных автоматов, который позволяет моделировать сложные системы с помощью простого набора правил и является наиболее удобным и точным методом для работы с аэрокосмоснимками. Описаны алгоритмы и основные параметры моделирования, необходимые для использования данного метода. Разработанное программное обеспечение позволяет производить прогноз состояния поверхности рассматриваемых территорий на основе серии разновременных данных, а также задавать различные параметры моделирования с целью повышения точности прогнозных карт. Приведены результаты тестирования разработанного программного обеспечения на данных MODIS и Landsat, произведена оценка точности прогноза, влияния параметров моделирования на полученный результа

    Metal artifact reduction on MRI images

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    This article examines the method of image reconstruction, which aims to restore the exposed areas on MRI images. The algorithm is based on a geometric model for patch synthesis. The lost pixels are recovered by copying pixel values from the source using a similarity criterion. We used a trained neural network to choose the “best similar” patch. Experimental results show that the proposed method outperforms widely used state-of-the-art methods

    Metal artifact reduction on MRI images

    No full text
    This article examines the method of image reconstruction, which aims to restore the exposed areas on MRI images. The algorithm is based on a geometric model for patch synthesis. The lost pixels are recovered by copying pixel values from the source using a similarity criterion. We used a trained neural network to choose the “best similar” patch. Experimental results show that the proposed method outperforms widely used state-of-the-art methods
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