918 resultados para Fragmento TrkB-ICD


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Tese de mestrado, Neurociências, Faculdade de Medicina, Universidade de Lisboa, 2016

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Tese de doutoramento, Ciências Biomédicas (Neurociências), Universidade de Lisboa, Faculdade de Medicina, 2014

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Tese de mestrado, Neurociências, Faculdade de Medicina, Universidade de Lisboa, 2016

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Objective: The objectives of this article are to explore the extent to which the International Statistical Classification of Diseases and Related Health Problems (ICD) has been used in child abuse research, to describe how the ICD system has been applied and to assess factors affecting the reliability of ICD coded data in child abuse research.----- Methods: PubMed, CINAHL, PsychInfo and Google Scholar were searched for peer reviewed articles written since 1989 that used ICD as the classification system to identify cases and research child abuse using health databases. Snowballing strategies were also employed by searching the bibliographies of retrieved references to identify relevant associated articles. The papers identified through the search were independently screened by two authors for inclusion, resulting in 47 studies selected for the review. Due to heterogeneity of studies metaanalysis was not performed.----- Results: This paper highlights both utility and limitations of ICD coded data. ICD codes have been widely used to conduct research into child maltreatment in health data systems. The codes appear to be used primarily to determine child maltreatment patterns within identified diagnoses or to identify child maltreatment cases for research.----- Conclusions: A significant impediment to the use of ICD codes in child maltreatment research is the under-ascertainment of child maltreatment by using coded data alone. This is most clearly identified and, to some degree, quantified, in research where data linkage is used. Practice Implications: The importance of improved child maltreatment identification will assist in identifying risk factors and creating programs that can prevent and treat child maltreatment and assist in meeting reporting obligations under the CRC.

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Background: The systematic collection of high-quality mortality data is a prerequisite in designing relevant drowning prevention programmes. This descriptive study aimed to assess the quality (i.e., level of specificity) of cause-of-death reporting using ICD-10 drowning codes across 69 countries.---------- Methods: World Health Organization (WHO) mortality data were extracted for analysis. The proportion of unintentional drowning deaths coded as unspecified at the 3-character level (ICD-10 code W74) and for which the place of occurrence was unspecified at the 4th character (.9) were calculated for each country as indicators of the quality of cause-of-death reporting.---------- Results: In 32 of the 69 countries studied, the percentage of cases of unintentional drowning coded as unspecified at the 3-character level exceeded 50%, and in 19 countries, this percentage exceeded 80%; in contrast, the percentage was lower than 10% in only 10 countries. In 21 of the 56 countries that report 4-character codes, the percentage of unintentional drowning deaths for which the place of occurrence was unspecified at the 4th character exceeded 50%, and in 15 countries, exceeded 90%; in only 14 countries was this percentage lower than 10%.---------- Conclusion: Despite the introduction of more specific subcategories for drowning in the ICD-10, many countries were found to be failing to report sufficiently specific codes in drowning mortality data submitted to the WHO.

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As the development of ICD-11 progresses, the Australian Bureau of Statistics is beginning to consider what will be required to successfully implement the new version of the classification. This paper will present early thoughts on the following: building understanding amongst the user community of upcoming changes and the implications of those changes; the need for training of coders and data users; development of analytical methods and conduct of comparability studies; processes to test, accept and implement new or updated coding software; assessment of coding quality; changes to data analyses and reporting processes; updates to regular publications; and assessing the resources required for successful implementation.

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The National Centre for Health Information Research & Training (formerly NCCH Brisbane) has been conducting an annual introductory ICD-10 coding program in Brisbane for seven years. In 2008, the Centre introduced a new initiative, inviting potential trainers to participate in a one week train the trainer workshop prior to the regular coder training. The new trainers are provided with the opportunity to practice their new skills with the support and assistance of the NCHIRT trainers during the subsequent introductory program. This paper will report on the results of a survey of participants of these programs about their experiences conducting training courses in their own countries. The train the trainer program as a means to create a cadre of trainers to support the implementation of ICD-11 will be explored.

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Background The implementation of the Australian Consumer Law in 2011 highlighted the need for better use of injury data to improve the effectiveness and responsiveness of product safety (PS) initiatives. In the PS system, resources are allocated to different priority issues using risk assessment tools. The rapid exchange of information (RAPEX) tool to prioritise hazards, developed by the European Commission, is currently being adopted in Australia. Injury data is required as a basic input to the RAPEX tool in the risk assessment process. One of the challenges in utilising injury data in the PS system is the complexity of translating detailed clinical coded data into broad categories such as those used in the RAPEX tool. Aims This study aims to translate hospital burns data into a simplified format by mapping the International Statistical Classification of Disease and Related Health Problems (Tenth Revision) Australian Modification (ICD-10-AM) burn codes into RAPEX severity rankings, using these rankings to identify priority areas in childhood product-related burns data. Methods ICD-10-AM burn codes were mapped into four levels of severity using the RAPEX guide table by assigning rankings from 1-4, in order of increasing severity. RAPEX rankings were determined by the thickness and surface area of the burn (BSA) with information extracted from the fourth character of T20-T30 codes for burn thickness, and the fourth and fifth characters of T31 codes for the BSA. Following the mapping process, secondary data analysis of 2008-2010 Queensland Hospital Admitted Patient Data Collection (QHAPDC) paediatric data was conducted to identify priority areas in product-related burns. Results The application of RAPEX rankings in QHAPDC burn data showed approximately 70% of paediatric burns in Queensland hospitals were categorised under RAPEX levels 1 and 2, 25% under RAPEX 3 and 4, with the remaining 5% unclassifiable. In the PS system, prioritisations are made to issues categorised under RAPEX levels 3 and 4. Analysis of external cause codes within these levels showed that flammable materials (for children aged 10-15yo) and hot substances (for children aged <2yo) were the most frequently identified products. Discussion and conclusions The mapping of ICD-10-AM burn codes into RAPEX rankings showed a favourable degree of compatibility between both classification systems, suggesting that ICD-10-AM coded burn data can be simplified to more effectively support PS initiatives. Additionally, the secondary data analysis showed that only 25% of all admitted burn cases in Queensland were severe enough to trigger a PS response.

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Background The implementation of the Australian Consumer Law in 2011 highlighted the need for better use of injury data to improve the effectiveness and responsiveness of product safety (PS) initiatives. In the PS system, resources are allocated to different priority issues using risk assessment tools. The rapid exchange of information (RAPEX) tool to prioritise hazards, developed by the European Commission, is currently being adopted in Australia. Injury data is required as a basic input to the RAPEX tool in the risk assessment process. One of the challenges in utilising injury data in the PS system is the complexity of translating detailed clinical coded data into broad categories such as those used in the RAPEX tool. Aims This study aims to translate hospital burns data into a simplified format by mapping the International Statistical Classification of Disease and Related Health Problems (Tenth Revision) Australian Modification (ICD-10-AM) burn codes into RAPEX severity rankings, using these rankings to identify priority areas in childhood product-related burns data. Methods ICD-10-AM burn codes were mapped into four levels of severity using the RAPEX guide table by assigning rankings from 1-4, in order of increasing severity. RAPEX rankings were determined by the thickness and surface area of the burn (BSA) with information extracted from the fourth character of T20-T30 codes for burn thickness, and the fourth and fifth characters of T31 codes for the BSA. Following the mapping process, secondary data analysis of 2008-2010 Queensland Hospital Admitted Patient Data Collection (QHAPDC) paediatric data was conducted to identify priority areas in product-related burns. Results The application of RAPEX rankings in QHAPDC burn data showed approximately 70% of paediatric burns in Queensland hospitals were categorised under RAPEX levels 1 and 2, 25% under RAPEX 3 and 4, with the remaining 5% unclassifiable. In the PS system, prioritisations are made to issues categorised under RAPEX levels 3 and 4. Analysis of external cause codes within these levels showed that flammable materials (for children aged 10-15yo) and hot substances (for children aged <2yo) were the most frequently identified products. Discussion and conclusions The mapping of ICD-10-AM burn codes into RAPEX rankings showed a favourable degree of compatibility between both classification systems, suggesting that ICD-10-AM coded burn data can be simplified to more effectively support PS initiatives. Additionally, the secondary data analysis showed that only 25% of all admitted burn cases in Queensland were severe enough to trigger a PS response.

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This paper describes the limitations of using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) to characterise patient harm in hospitals. Limitations were identified during a project to use diagnoses flagged by Victorian coders as hospital-acquired to devise a classification of 144 categories of hospital acquired diagnoses (the Classification of Hospital Acquired Diagnoses or CHADx). CHADx is a comprehensive data monitoring system designed to allow hospitals to monitor their complication rates month-to-month using a standard method. Difficulties in identifying a single event from linear sequences of codes due to the absence of code linkage were the major obstacles to developing the classification. Obstetric and perinatal episodes also presented challenges in distinguishing condition onset, that is, whether conditions were present on admission or arose after formal admission to hospital. Used in the appropriate way, the CHADx allows hospitals to identify areas for future patient safety and quality initiatives. The value of timing information and code linkage should be recognised in the planning stages of any future electronic systems.

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Objective Death certificates provide an invaluable source for cancer mortality statistics; however, this value can only be realised if accurate, quantitative data can be extracted from certificates – an aim hampered by both the volume and variable nature of certificates written in natural language. This paper proposes an automatic classification system for identifying cancer related causes of death from death certificates. Methods Detailed features, including terms, n-grams and SNOMED CT concepts were extracted from a collection of 447,336 death certificates. These features were used to train Support Vector Machine classifiers (one classifier for each cancer type). The classifiers were deployed in a cascaded architecture: the first level identified the presence of cancer (i.e., binary cancer/nocancer) and the second level identified the type of cancer (according to the ICD-10 classification system). A held-out test set was used to evaluate the effectiveness of the classifiers according to precision, recall and F-measure. In addition, detailed feature analysis was performed to reveal the characteristics of a successful cancer classification model. Results The system was highly effective at identifying cancer as the underlying cause of death (F-measure 0.94). The system was also effective at determining the type of cancer for common cancers (F-measure 0.7). Rare cancers, for which there was little training data, were difficult to classify accurately (F-measure 0.12). Factors influencing performance were the amount of training data and certain ambiguous cancers (e.g., those in the stomach region). The feature analysis revealed a combination of features were important for cancer type classification, with SNOMED CT concept and oncology specific morphology features proving the most valuable. Conclusion The system proposed in this study provides automatic identification and characterisation of cancers from large collections of free-text death certificates. This allows organisations such as Cancer Registries to monitor and report on cancer mortality in a timely and accurate manner. In addition, the methods and findings are generally applicable beyond cancer classification and to other sources of medical text besides death certificates.

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Homenaje a Ignacio Barandiarán Maestu / coord. por Javier Fernández Eraso, Juan Santos Yanguas.

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[EN] This article consists of a study (provenance, date of the manuscript, sources of the glossary, etc.) and an edition of the fragment of an epitome of the «Liber Glossarum» which is contained in a ms. about the year 1000 A.D. From the "Spanish symptoms" which one can track in the present copy, the ms. El Escorial L.I.15, from the 16th-17th century, the author infers that his model, now perished, was written in Spain and in wisigothic script about the year 1000. On the other side, on the basis of the copy the author reconstructs the primitive glossary text of the 10th-11th century model in a critical edition accompanied by a critical apparat and sources.

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La colicinas son bacteriocinas producidas por cepas de Escherichia coli y letales para otras cepas relacionadas. Este trabajo está enfocado a la interacción proteína-proteína del complejo funcional caa-cai. Las interacciones proteína-proteína dentro de la membrana han sido tradicionalmente muy difíciles de cuantificar. Sin embargo, publicaciones anteriores han demostrado que el sistema caa-cai representa un complejo eficaz a la hora de inhibir la actividad tóxica de caa. Además, este complejo posee dos ventajas principales que facilitan su estudio: la interacción debe tener una alta afinidad y se debe poder medir in vivo de forma indirecta. El objetivo principal de esta memoria reside en la optimización de las condiciones de sobreexpresión del complejo funcional caa-cai. La formación del complejo en el sistema natural implica el acceso de ambas proteínas desde lados opuestos de la IM de la bacteria. Con el fin de mimetizar este escenario es necesario inducir la exportación del fragmento pf-caa al periplasma celular tras su sobreexpresión.