992 resultados para Abdomen diseases


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Contiene : T.I : Maladies de poitrine (VIII, 591 p.) -- T.II : Maladies de poitrine (635 p.) -- T.III : Maladies de l'abdomen (674 p.) -- T.IV : Maladies de l'abdomen (694 p.)

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Mode of access: Internet.

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Published also as part IV of the author's The clinique médicale; or, Reports of medical cases. London, 1836.

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Introduction Most underlying diseases for abdominal pain in children are not dangerous. However some require rapid diagnosis and treatment, such as acute ovarian torsion or appendicitis. Since reaching a diagnosis can be difficult, and delayed treatment of potentially dangerous diseases might have significant consequences, exploratory laparoscopy is a diagnostic and therapeutic option for patients who have unclear and potentially hazardous abdominal diseases. Here we describe a case where the anomaly could not be identified using a laparoscopy in an adolescent girl with acute abdomen. Case presentation A 13-year old postmenarchal caucasian female presented with an acute abdomen. Emergency sonography could not exclude ovarian torsion. Accurate diagnosis and treatment were achieved only after an initial laparoscopy followed by a laparotomy and after a magnetic resonance imaging scan a further laparotomy. The underlying disease was hematometra of the right uterine horn in a uterus didelphys in conjunction with an imperforate right cervix. Conclusion This report demonstrates that the usual approach for patients with acute abdominal pain may not be sufficient in emergency situations.

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Mode of access: Internet.

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Austin, R.B. Early Amer. medical imprints,

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Contains short bibliographies.

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Translation of Lehrbuch der klinischen Untersuchungs-Methoden für die Brust- und Unterleibs-Organe.

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Nontuberculous mycobacteria are ubiquitous environmental organisms that have been recognised as a cause of pulmonary infection for over 50 years. Traditionally patients have had underlying risk factors for development of disease; however the proportion of apparently immunocompetent patients involved appears to be rising. Not all patients culture-positive for mycobacteria will have progressive disease, making the diagnosis difficult, though criteria to aid in this process are available. The two main forms of disease are cavitary disease (usually involving the upper lobes) and fibronodular bronchiectasis (predominantly middle and lingular lobes). For patients with disease, combination antibiotic therapy for 12-24 months is generally required for successful treatment, and this may be accompanied by drug intolerances and side effects. Published success rates range from 30-82%. As the progression of disease is variable, for some patients, attention to pulmonary hygiene and underlying diseases without immediate antimycobacterial therapy may be more appropriate. Surgery can be a useful adjunct, though is associated with risks. Randomised controlled trials in well described patients would provide stronger evidence-based data to guide therapy of NTM lung diseases, and thus are much needed.

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Genetic research of complex diseases is a challenging, but exciting, area of research. The early development of the research was limited, however, until the completion of the Human Genome and HapMap projects, along with the reduction in the cost of genotyping, which paves the way for understanding the genetic composition of complex diseases. In this thesis, we focus on the statistical methods for two aspects of genetic research: phenotype definition for diseases with complex etiology and methods for identifying potentially associated Single Nucleotide Polymorphisms (SNPs) and SNP-SNP interactions. With regard to phenotype definition for diseases with complex etiology, we firstly investigated the effects of different statistical phenotyping approaches on the subsequent analysis. In light of the findings, and the difficulties in validating the estimated phenotype, we proposed two different methods for reconciling phenotypes of different models using Bayesian model averaging as a coherent mechanism for accounting for model uncertainty. In the second part of the thesis, the focus is turned to the methods for identifying associated SNPs and SNP interactions. We review the use of Bayesian logistic regression with variable selection for SNP identification and extended the model for detecting the interaction effects for population based case-control studies. In this part of study, we also develop a machine learning algorithm to cope with the large scale data analysis, namely modified Logic Regression with Genetic Program (MLR-GEP), which is then compared with the Bayesian model, Random Forests and other variants of logic regression.