973 resultados para PRESENTING CLINICAL-FEATURE


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Background: Primary hyperparathyroidism occurs in only 10%-30% of patients with multiple endocrine neoplasia type 2A (MEN2A), rarely as the sole clinical manifestation, and is usually diagnosed after the third decade of life. Summary: A5-year-old girl was referred for prophylactic thyroidectomy as she carried the p.C634R RET mutation. She was clinically asymptomatic, with a normally palpable thyroid and with the cervical region free of lymphadenopathy or other nodules. Preoperative tests revealed hypercalcemia associated with elevation of parathyroid hormone (PTH) (calcium = 11.2mg/dL, calcium ion = 1.48mmol/L, phosphorus = 4.0 mg/dL, alkaline phosphatase = 625U/L, parathyroid hormone (PTH) PTH = 998 pg/mL). A thyroid ultrasound was normal and parathyroid scintigraphy with (99m)Tc-Sestamibi revealed an area of radioconcentration in the upper half of the left thyroid lobe suggesting hyperfunctioning parathyroid tissue. She underwent total thyroidectomy and parathyroidectomy and developed hypocalcemia. The anatomopathological examination showed no histopathological changes in the thyroid tissue and an adenoma of the parathyroid gland, confirming the diagnosis of hyperparathyroidism. Conclusions: Primary hyperparathyroidism can be a precocious manifestation of MEN2A. This case report highlights that asymptomatic hypercalcemia should be scrutinized in children related to patients with MEN2A who carry a mutation in the RET proto-oncogene, especially mutations in the codon 634, before the currently recommended age of 8 years.

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Background: Cancer stem cell (CSC) hypothesis postulates that tumors are maintained by a self-renewing CSC population that is also capable of differentiating into non-self-renewing cell populations that constitute the bulk of tumor. Stem cells renewal and differentiation can be directly influenced by the oxygen levels of determined tissues, probably by the reduction of oxidative DNA damage in hypoxic regions, thus leading to a friendlier microenvironment, regarding to clonal expansion and for resistance to chemotherapeutic regimens. Furthermore, there have been strong data indicating a pivotal role of hypoxic niche in cancer stem cells development. There are evidence that hypoxia could drive the maintenance of CSC, via HIF-1 alpha expression, but it still to be determined whether hypoxia markers are expressed in breast tumors presenting CD44(+)CD24(-/low) immunophenotype. Methods: Immunohistochemical analysis of CD44(+)CD24(-/low) expression and its relationship with hypoxia markers and clinical outcome were evaluated in 253 samples of breast ductal carcinomas. Double-immunolabeling was performed using EnVision Doublestain System (Dako, Carpinteria, CA, USA). Slides were then scanned into high-resolution images using Aperio ScanScope XT and then, visualized in the software Image Scope (Aperio, Vista, CA, USA). Results: In univariate analysis, CD44(+)CD24(-/low) expression showed association with death due to breast cancer (p = 0.035). Breast tumors expressing CD44(+)CD24(-/low) immunophenotype showed relationship with HIF-1 alpha (p = 0.039) and negativity for HER-2 (p = 0.013). Conclusion: Considering that there are strong evidences that the fraction of a tumour considered to be cancer stem cells is plastic depending upon microenvironmental signals, our findings provide further evidence that hypoxia might be related to the worse prognosis found in CD44(+)CD24(-/low) positive breast tumors.

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Purpose: The purpose of this work was to evaluate the potential of substituting autogenous bone (AB) by bone marrow aspirate concentrate (BMAC). Both AB and BMAC were tested in combination with a bovine bone mineral (BBM) for their ability of new bone formation (NBF) in a multicentric, randomized, controlled, clinical and histological noninferiority trial. Materials and Methods: Forty-five severely atrophied maxillary sinus from 26 patients were evaluated in a partial cross-over design. As test arm, 34 sinus of 25 patients were augmented with BBM and BMAC containing mesenchymal stem cells. Eleven control sinus from 11 patients were augmented with a mixture of 70% BBM and 30% AB. Biopsies were obtained after a 3-4-month healing period at time of implant placement and histomorphometrically analyzed for NBF. Results: NBF was 14.3%+/- 1.8% for the control and nonsignificantly lower (12.6%+/- 1.7%) for the test (90% confidence interval: -4.6 to 1.2). Values for BBM (31.3%+/- 2.7%) were significantly higher for the test compared with control (19.3%+/- 2.5%) (p < 0.0001). Nonmineralized tissue was lower by 3.3% in the test compared with control (57.6%; p = 0.137). Conclusions: NBF after 3-4 months is equivalent in sinus, augmented with BMAC and BBM or a mixture of AB and BBM. This technique could be an alternative for using autografts to stimulate bone formation.

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Objective To examine the ability of the criteria proposed by the WHO to identify pneumonia among cases presenting with wheezing and the extent to which adding fever to the criteria alters their performance. Design Prospective classification of 390 children aged 2-59 months with lower respiratory tract disease into five diagnostic categories, including pneumonia. WHO criteria for the identification of pneumonia and a set of such criteria modified by adding fever were compared with radio-graphically diagnosed pneumonia as the gold standard. Results The sensitivity of the WHO criteria was 94% for children aged <24 months and 62% for those aged >= 24 months. The corresponding specificities were 20% and 16%. Adding fever to the WHO criteria improved specificity substantially (to 44% and 50%, respectively). The specificity of the WHO criteria was poor for children with wheezing (12%). Adding fever improved this substantially (to 42%). The addition of fever to the criteria apparently reduced their sensitivity only marginally (to 92% and 57%, respectively, in the two age groups). Conclusion The authors' results reaffirm that the current WHO criteria can detect pneumonia with high sensitivity, particularly among younger children. They present evidence that the ability of these criteria to distinguish between children with pneumonia and those with wheezing diseases might be greatly enhanced by the addition of fever.

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The most relevant clinical trials, assessing the role of glycemic control in reducing cardiovascular risk, are examined. The UKPDS was the first to address this issue. More recent trials (ACCORD, ADVANCE and VADT) are controversial and evidences did not support that strict glycemic control (reflected by normal glycated hemoglobin) exclusively is sufficient to reduce cardiovascular risk in complicated individuals with long-term type 2 diabetes mellitus. Some possible reasons for controversies are included.

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Background: Despite governmental and private efforts on providing malaria control, this disease continues to be a major health threat. Thus, innovative strategies are needed to reduce disease burden. The malaria vectors, through the injection of saliva into the host skin, play important role on disease transmission and may influence malaria morbidity. This study describes the humoral immune response against Anopheles (An.) darlingi saliva in volunteers from the Brazilian Amazon and addresses the association between levels of specific antibodies and clinical presentation of Plasmodium (P.) vivax infection. Methods: Adult volunteers from communities in the Rondonia State, Brazil, were screened in order to assess the presence of P. vivax infection by light microscopy and nested PCR. Non-infected volunteers and individuals with symptomatic or symptomless infection were randomly selected and plasma collected. An. darlingi salivary gland sonicates (SGS) were prepared and used to measure anti-saliva antibody levels. Plasma interleukin (IL)-10 and interferon (IFN)-gamma levels were also estimated and correlated to anti-SGS levels. Results: Individuals infected with P. vivax presented higher levels of anti-SGS than non-infected individuals and antibody levels could discriminate infection. Furthermore, anti-saliva antibody measurement was also useful to distinguish asymptomatic infection from non-infection, with a high likelihood ratio. Interestingly, individuals with asymptomatic parasitaemia presented higher titers of anti-SGS and lower IFN-gamma/IL-10 ratio than symptomatic ones. In P. vivax-infected asymptomatic individuals, the IFN-gamma/IL-10 ratio was inversely correlated to anti-SGS titers, although not for while in symptomatic volunteers. Conclusion: The estimation of anti-An. darlingi antibody levels can indicate the probable P. vivax infection status and also could serve as a marker of disease severity in this region of Brazilian Amazon.

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Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

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Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.

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Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

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Background: Continuing education courses related to critical thinking and clinical reasoning are needed to improve the accuracy of diagnosis. Method: This study evaluated a 4-day, 16-hour continuing education course conducted in Brazil. Thirty-nine nurses completed a pretest and a posttest consisting of two written case studies designed to measure the accuracy of nurses` diagnoses. Results: There were significant differences in accuracy from pretest to posttest for case 1 (p = .008) and case 2 (p = .042) and overall (p = .001). Conclusion: Continuing education courses should be implemented to improve the accuracy of nurses` diagnoses. J Contin Educ Nurs 2009;40(3):121-127.

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Introduction: The purpose of this study was to compare the frequency and severity of perineal trauma during spontaneous birth with or without perineal injections of hyaluronidase (HAase). Methods: A randomized, placebo-controlled, double-blind clinical trial was conducted in a midwife-led, in-hospital birth center in Sao Paulo, Brazil. Primiparous women (N = 160) were randomly assigned to an experimental (n = 80) or control (n = 80) group. During the second stage of labor, women in the experimental group received an injection of 20.000 turbidity-reducing units of HAase in the posterior region of the perineum, and those in the control group received a placebo injection. The assessment of perineal outcome was performed by 2 independent nurse-midwives. A 1-tailed Fisher exact test was performed, and a P value < .025 was considered statistically significant. Results: Perineal integrity occurred in 34.2% of the experimental group and in 32.5% of the control group, which was not a statistically significant difference (P = .477). First-degree laceration was the most common trauma in the posterior region of the perineum in women in both groups (experimental = 56%, control = 42.6%). Severe perineal trauma occurred in 28.9% of the experimental group and 38.8% of the control group, which also was not a statistically significant difference (P =. 131). The depth of second-degree perineal lacerations in the experimental and control groups, measured by the Peri-Rule, was 1.9 cm and 2.3 cm, respectively. An episiotomy was performed in 11 women (experimental group = 3, control group = 8), and 4 (all in control group) had third-degree lacerations. Discussion: The use of injectable HAase did not increase the proportion of intact perineum and did not reduce the proportion of severe perineal trauma in our sample. J Midwifery Womens Health 2011; 56: 436-445 (C) 2011 by the American College of Nurse-Midwives.

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Objectives: Main Objective: to identify ethical problems in primary care according to nurses` and doctors` perceptions. Secondary Objective: to know ethical issues of patient-professional relationships in primary care. Design: Synthesis to integrate and reinterpret primary results of qualitative studies. Setting: Primary healthcare centers, Sao Paulo, SP, Brazil. Participants and/or context: Incidental sample of 34 nurses and 36 medical doctors working in primary healthcare centers selected by convenience. Methods: Individual, semi-structured interviews to identity situations considered as sources of ethical problems. The sample is socially representative of primary care health centers and professionals. Data collection assured discourse saturation. Hermeneutic-dialectical discourse analysis was used to study the results. Results: Patient-professional relationships and team work were the main sources of ethical problems. The most important problems were patient information, privacy, confidentiality, interpersonal relationship, linkage and patient autonomy. These issues reflect the recent changes in clinical relation ships and show the peculiarities of primary care with its continuous care which lasts a long time. Healthcare involves multiprofessional team work in the midst of the patient claims for autonomy. Good care of patients needs requires a relationship based on communication and cooperation, and includes feelings and values, with communication skills. Conclusions: Ethical problems in primary care are common situations. For quality and humane primary care the relationship should consist of dialogue, trust and cooperation. (C) 2009 Elsevier Espana, S.L. All rights reserved.

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Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.

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Of the various genetic homologues to Duchenne Muscular Dystrophy (DMD), the Golden Retriever Muscular Dystrophy (GRMD) dog, which presents a variable but usually severe and progressive muscle weakness, has the closest relevance to DMD in both clinical severity and histopathological change. Among 77 GRMD dogs born in our colony in Brazil, we have identified a very mildly affected dog, Ringo, born July 2003. Among his descendants, at least one male, Suflair, is also showing a mild course. In an attempt to better characterize these two dogs, we studied the pattern of muscle proteins expression in Ringo and Suflair, as compared to severely affected and normal control dogs. Dystrophin was absent in both and utrophin was overexpressed in a pattern similar to the observed in severely affected dogs. Understanding the mechanism that is protecting Ringo and Suflair from the deleterious effect of the dystrophin gene mutation is of utmost interest, In addition it points out that the clinical impact of therapeutic trials should be interpreted with caution. (C) 2009 Elsevier B.V. All rights reserved.

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Creatine (CR) supplementation is commonly used by athletes. However, its effects on renal function remain controversial. The aim of this study was to evaluate the effects of creatine supplementation on renal function in healthy sedentary males (18-35 years old) submitted to exercise training. A randomized, double-blind, placebo-controlled trial was performed. Subjects (n = 18) were randomly allocated to receive treatment with either creatine (CR) (similar to 10 g day(-1) over 3 months) or placebo (PL) (dextrose). All subjects undertook moderate intensity aerobic training, in three 40-min sessions per week, during 3 months. Serum creatinine, serum and urinary sodium and potassium were determined at baseline and at the end of the study. Cystatin C was assessed prior to training (PRE), after 4 (POST 4) and 12 weeks (POST 12). Cystatin C levels (mg L-1) (PRE CR: 0.82 +/- 0.09; PL: 0.88 +/- 0.07 vs. POST 12 CR: 0.71 +/- 0.06; PL: 0.75 +/- 0.09, P = 0.0001) were decreased over time, suggesting an increase in glomerular filtration rate. Serum creatinine decreased with training in PL but was unchanged with training in CR. No significant differences were observed within or between groups in other parameters investigated. The decrease in cystatin C indicates that high-dose creatine supplementation over 3 months does not provoke any renal dysfunction in healthy males undergoing aerobic training. In addition, the results suggest that moderate aerobic training per se may improve renal function.