898 resultados para Autopsy diagnosis


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This thesis describes some aspects of a computer system for doing medical diagnosis in the specialized field of kidney disease. Because such a system faces the spectre of combinatorial explosion, this discussion concentrates on heuristics which control the number of concurrent hypotheses and efficient "compiled" representations of medical knowledge. In particular, the differential diagnosis of hematuria (blood in the urine) is discussed in detail. A protocol of a simulated doctor/patient interaction is presented and analyzed to determine the crucial structures and processes involved in the diagnosis procedure. The data structure proposed for representing medical information revolves around elementary hypotheses which are activated when certain disposing of findings, activating hypotheses, evaluating hypotheses locally and combining hypotheses globally is examined for its heuristic implications. The thesis attempts to fit the problem of medical diagnosis into the framework of other Artifcial Intelligence problems and paradigms and in particular explores the notions of pure search vs. heuristic methods, linearity and interaction, local vs. global knowledge and the structure of hypotheses within the world of kidney disease.

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Hardy, N. W., Barnes, D. P., Lee, L. H. (1989). Automatic diagnosis of task faults in flexible manufacturing systems. Robotica, 7 (1):25-35

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McArdle disease is a metabolic disorder caused by pathogenic mutations in the PYGM gene. Timely diagnosis can sometimes be difficult with direct genomic analysis, which requires additional studies of cDNA from muscle transcripts. Although the "nonsense-mediated mRNA decay" (NMD) eliminates tissue-specific aberrant transcripts, there is some residual transcription of tissue-specific genes in virtually all cells, such as peripheral blood mononuclear cells (PBMCs).We studied a subset of the main types of PYGM mutations (deletions, missense, nonsense, silent, or splicing mutations) in cDNA from easily accessible cells (PBMCs) in 12 McArdle patients.Analysis of cDNA from PBMCs allowed detection of all mutations. Importantly, the effects of mutations with unknown pathogenicity (silent and splicing mutations) were characterized in PBMCs. Because the NMD mechanism does not seem to operate in nonspecific cells, PBMCs were more suitable than muscle biopsies for detecting the pathogenicity of some PYGM mutations, notably the silent mutation c.645G>A (p.K215=), whose effect in the splicing of intron 6 was unnoticed in previous muscle transcriptomic studies.We propose considering the use of PBMCs for detecting mutations that are thought to cause McArdle disease, particularly for studying their actual pathogenicity.

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Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

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The recent implementation of Universal Neonatal Hearing Screening (UNHS) in all 19 maternity hospitals across Ireland has precipitated early identification of paediatric hearing loss in an Irish context. This qualitative, grounded theory study centres on the issue of parental coping as families receive and respond to (what is typically) an unexpected diagnosis of hearing loss in their newborn baby. Parental wellbeing is of particular concern as the diagnosis occurs in the context of recovery from birth and at a time when the parent-child relationship is being established. As the vast majority of children with a hearing loss are born into hearing families with no prior history of deafness, parents generally have had little exposure to childhood hearing loss and often experience acute emotional vulnerability as they respond to the diagnosis. The researcher conducted in-depth interviews primarily with parents (and to a lesser extent with professionals), as well as a follow-up postal questionnaire for parents. Through a grounded theory analysis of data, the researcher subsequently fashioned a four-stage model depicting the parental journey of receiving and coping with a diagnosis. The four stages (entitled Anticipating, Confirming, Adjusting and Normalising) are differentiated by the chronology of service intervention and defined by the overarching parental experience. Far from representing a homogenous trajectory, this four-stage model is multifaceted and captures a wide diversity of parental experiences ranging from acute distress to resilient hopefulness

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OBJECTIVE: To investigate the value of serum antitissue transglutaminase IgA antibodies (IgA-TTG) and IgA antiendomysial antibodies (IgA-EMA) in the diagnosis of coeliac disease in cohorts from different geographical areas in Europe. The setting allowed a further comparison between the antibody results and the conventional small-intestinal histology. METHODS: A total of 144 cases with coeliac disease [median age 19.5 years (range 0.9-81.4)], and 127 disease controls [median age 29.2 years (range 0.5-79.0)], were recruited, on the basis of biopsy, from 13 centres in nine countries. All biopsy specimens were re-evaluated and classified blindly a second time by two investigators. IgA-TTG were determined by ELISA with human recombinant antigen and IgA-EMA by an immunofluorescence test with human umbilical cord as antigen. RESULTS: The quality of the biopsy specimens was not acceptable in 29 (10.7%) of 271 cases and a reliable judgement could not be made, mainly due to poor orientation of the samples. The primary clinical diagnosis and the second classification of the biopsy specimens were divergent in nine cases, and one patient was initially enrolled in the wrong group. Thus, 126 coeliac patients and 106 controls, verified by biopsy, remained for final analysis. The sensitivity of IgA-TTG was 94% and IgA-EMA 89%, the specificity was 99% and 98%, respectively. CONCLUSIONS: Serum IgA-TTG measurement is effective and at least as good as IgA-EMA in the identification of coeliac disease. Due to a high percentage of poor histological specimens, the diagnosis of coeliac disease should not depend only on biopsy, but in addition the clinical picture and serology should be considered.

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Congrès du GIRSO, Lille, avril 2011

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BACKGROUND: The etiologic diagnosis of community-acquired pneumonia (CAP) remains challenging in children because blood cultures have low sensitivity. Novel approaches are needed to confirm the role of Streptococcus pneumoniae. METHODS: In this study, pneumococcal aetiology was determined by serology using a subset of blood samples collected during a prospective multicentre observational study of children <15 years of age hospitalised in Belgium with X-ray-confirmed CAP. Blood samples were collected at admission and 3-4 weeks later. Pneumococcal (P)-CAP was defined in the presence of a positive blood or pleural fluid culture. Serotyping of Streptococcus pneumoniae isolates was done with the Quellung reaction. Serological diagnosis was assessed for nine serotypes using World Health Organization validated IgG and IgA serotype-specific enzyme-linked immunosorbent assays (ELISAs). RESULTS: Paired admission/convalescent sera from 163 children were evaluated by ELISA (35 with proven P-CAP and 128 with non proven P-CAP). ELISA detected pneumococci in 82.8% of patients with proven P-CAP. The serotypes identified were the same as with the Quellung reaction in 82% and 59% of cases by IgG ELISA and IgA ELISA, respectively. Overall, ELISA identified a pneumococcal aetiology in 55% of patients with non-proven P-CAP. Serotypes 1 (51.6%), 7F (19%), and 5 (15.7%) were the most frequent according to IgG ELISA. CONCLUSIONS: In conclusion, the serological assay allows recognition of pneumococcal origin in 55% of CAP patients with negative culture. This assay should improve the diagnosis of P-CAP in children and could be a useful tool for future epidemiological studies on childhood CAP etiology.

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As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p < 0.02) and achieved AUC=0.85 +/- 0.01. The DF-P surpassed the other classifiers in terms of pAUC (p < 0.01) and reached pAUC=0.38 +/- 0.02. For the mass data set, DF-A outperformed both the ANN and the LDA (p < 0.04) and achieved AUC=0.94 +/- 0.01. Although for this data set there were no statistically significant differences among the classifiers' pAUC values (pAUC=0.57 +/- 0.07 to 0.67 +/- 0.05, p > 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p < 0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets.

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In the event of a terrorist-mediated attack in the United States using radiological or improvised nuclear weapons, it is expected that hundreds of thousands of people could be exposed to life-threatening levels of ionizing radiation. We have recently shown that genome-wide expression analysis of the peripheral blood (PB) can generate gene expression profiles that can predict radiation exposure and distinguish the dose level of exposure following total body irradiation (TBI). However, in the event a radiation-mass casualty scenario, many victims will have heterogeneous exposure due to partial shielding and it is unknown whether PB gene expression profiles would be useful in predicting the status of partially irradiated individuals. Here, we identified gene expression profiles in the PB that were characteristic of anterior hemibody-, posterior hemibody- and single limb-irradiation at 0.5 Gy, 2 Gy and 10 Gy in C57Bl6 mice. These PB signatures predicted the radiation status of partially irradiated mice with a high level of accuracy (range 79-100%) compared to non-irradiated mice. Interestingly, PB signatures of partial body irradiation were poorly predictive of radiation status by site of injury (range 16-43%), suggesting that the PB molecular response to partial body irradiation was anatomic site specific. Importantly, PB gene signatures generated from TBI-treated mice failed completely to predict the radiation status of partially irradiated animals or non-irradiated controls. These data demonstrate that partial body irradiation, even to a single limb, generates a characteristic PB signature of radiation injury and thus may necessitate the use of multiple signatures, both partial body and total body, to accurately assess the status of an individual exposed to radiation.

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Background:Diagnosis of childhood active tuberculosis (aTB) or latent Mycobacterium tuberculosis (Mtb) infection (LTBI) remains a challenge, and replacement of tuberculin skin tests (TST) by commercialized interferon-gamma release assays (IGRA) is not currently recommended.Methods:266 children between 1 month and 15 years of age, 214 being at risk of recent Mtb infection and 51 being included as controls, were prospectively enrolled. According results of clinical evaluation, TST, chest X-Ray and microbiology, children were classified as non-infected, LTBI or aTB. Long-incubation time PPD-, ESAT-6-, and CFP-10-IGRA were performed and evaluated for their accuracy to correctly classify the children.Results:Whereas both TST and PPD-IGRA were suboptimal to detect aTB, combining CFP-10-IGRA with TST or with PPD-IGRA allowed us to detect all the children with aTB, with 96% specificity for children who were positive for CFP-10-IGRA. Moreover, combination of CFP-10- and PPD-IGRA also detected 96% of children classified as LTBI, but a strong IFN-γ response to CFP-10 (>500 pg/ml) was highly suggestive of aTB at least among children less than 3 years old.Conclusions:Long-incubation time CFP-10- and PPD-IGRA should help the clinicians to identify quickly aTB or LTBI in young children.