Innocent heart murmurs

Innocent heart murmur is a frequent auscultatory finding in children. The diagnosis is essentially clinical, without need for further investigation. However, excluding heart disease can be a difficult task. This review article describes some features of medical history and physical examination that help in this differentiation. The role of diagnostic tests is also examined

Risk of low energy availability among female and male elite runners competing at the 26th European cross-country championships

Low energy availability (LEA) causes impaired physiological functioning. Cross-country running is a weight-sensitive sport, making athletes more prone to LEA. We aimed to estimate the prevalence of elite European cross-country athletes at risk of LEA using the LEA in Females Questionnaire (LEAF-Q) and to analyze demographic and physical characteristics that are associated with LEA. Athletes ≥ 18 years competing at the 26th European Cross-Country Championships (n = 602) were invited to complete a questionnaire (sociodemographic, training, anthropometric characteristics, and LEAF-Q). A total of 207 valid surveys were collected (83 females, 22.1 (4.0) years, and 124 males, 22.3 (4.1) years), and 16 surveys were excluded. A high prevalence of athletes at risk of LEA (64.3%) was observed, being higher in females than in males (79.5 and 54.0% respectively, p < 0.001). More than half of athletes (54.1%, n = 112) reported bowel movements once a week or more rarely, while 33 female athletes (41.3%) did not report normal menstruation. Overall, cross-country athletes are at high risk of LEA. Moreover, a high prevalence of gastrointestinal and menstrual impairments was reported. Hence, athletes should be followed by multidisciplinary teams to inform, prevent, and treat LEA and its effects.publishersversionpublishe

Displasia Torácica

Os autores descrevem um caso clínico referente a uma criança que apresentava ao nascer uma marcada desproporção toraco-abdominal,por diminuição do diâmetro torácico. O Recém-nascido (RN) fez um Síndrome de Dificuldade Respiratória (SDR) precoce com necessidade de ventilação mecânica, tendo-se verificado dificuldade na entubação traqueal. Após a extubação manteve crises frequentes de polipneia e cianose. Na sequência da investigação etiológica, verificou-se que tinha uma estenose sub glótica importante. Associando os achados clínicos verificamos tratar-se de um síndrome de Barnes, forma rara de displasia torácica

Deep Learning for Identification of Acute Illness and Facial Cues of Illness

Background: The inclusion of facial and bodily cues (clinical gestalt) in machine learning (ML) models improves the assessment of patients' health status, as shown in genetic syndromes and acute coronary syndrome. It is unknown if the inclusion of clinical gestalt improves ML-based classification of acutely ill patients. As in previous research in ML analysis of medical images, simulated or augmented data may be used to assess the usability of clinical gestalt. Objective: To assess whether a deep learning algorithm trained on a dataset of simulated and augmented facial photographs reflecting acutely ill patients can distinguish between healthy and LPS-infused, acutely ill individuals. Methods: Photographs from twenty-six volunteers whose facial features were manipulated to resemble a state of acute illness were used to extract features of illness and generate a synthetic dataset of acutely ill photographs, using a neural transfer convolutional neural network (NT-CNN) for data augmentation. Then, four distinct CNNs were trained on different parts of the facial photographs and concatenated into one final, stacked CNN which classified individuals as healthy or acutely ill. Finally, the stacked CNN was validated in an external dataset of volunteers injected with lipopolysaccharide (LPS). Results: In the external validation set, the four individual feature models distinguished acutely ill patients with sensitivities ranging from 10.5% (95% CI, 1.3–33.1% for the skin model) to 89.4% (66.9–98.7%, for the nose model). Specificity ranged from 42.1% (20.3–66.5%) for the nose model and 94.7% (73.9–99.9%) for skin. The stacked model combining all four facial features achieved an area under the receiver characteristic operating curve (AUROC) of 0.67 (0.62–0.71) and distinguished acutely ill patients with a sensitivity of 100% (82.35–100.00%) and specificity of 42.11% (20.25–66.50%). Conclusion: A deep learning algorithm trained on a synthetic, augmented dataset of facial photographs distinguished between healthy and simulated acutely ill individuals, demonstrating that synthetically generated data can be used to develop algorithms for health conditions in which large datasets are difficult to obtain. These results support the potential of facial feature analysis algorithms to support the diagnosis of acute illness

A introdução de competências de gestão na formação médica: uma avaliação multidimensional das expectativas

In the last decades, the organizational dynamics has shown the imperative need to rule the management competences mainly relevant in the health sector. Has this reality been perceived and included in the medical curriculum? Once there is a reformist impulse in the way how the health units are managed, why haven’t most of the Medicine Faculties integrated this domain in their curricular reforms? Hence, there seems to be a strong search for these additional competences, only in a post-graduate phase, above all justified by a better qualification in the medical praxis, in which the doctors are called to decide in scenarios with limited resources and budget constraints. With this work we wish to research the perceptions and eventual motivations of the students in the Medicine Faculties of Portugal to introduce management competences in the ir medical pre-graduate curriculum. Focusing on the medicine students and on the change occurred in the doctors’ behaviour, before and after contacting with this new competence, we aspired to qualify and understand the future graduates’ expectations in what regards this objective. Thus, the use of the Non Linear Canonical Correlation Analysis has allowed not only the multidimensional description of topologies and /or typologies of individuals, but it has also analysed the relations among the various answers, arranged in optimal scales, thus determining similarities / dissimilarities among the shown opinions along the medical training process. From the results it was concluded that there isn’t a majority group expressing a tendency clearly, but rather a distribution of the respondents in the various typologies in every sample, which indicates to the decision-makers a perspective of the curriculum flexible approach, in a different model from the one predominating in the present Medical Education institutions, that still don’t work with the concept of curricular attractors.A dinâmica organizacional que se tem manifestado nas últimas décadas tornou imperativo o domínio de competências de gestão, particularmente relevantes no sector da saúde. Terá sido esta realidade percepcionada e incluída no currículo médico? Existindo um impulso reformista na forma de encarar a gestão de unidades de saúde, por que razão a maioria das Faculdades de Medicina não integrou este domínio nas suas reformas curriculares? Não obstante, parece existir uma forte procura na aquisição destas competências complementares, apenas numa fase pós-graduada, fundamentalmente justificada por uma melhor qualificação na prática médica, na qual os médicos são chamados a decidir em cenários com recursos limitados e constrangimentos orçamentais. Pretendemos com este trabalho, investigar as motivações das Faculdades de Medicina em Portugal para a introdução de competências de gestão no currículo pré e pós-graduado médico. Centrando-nos nos alunos de medicina e na mudança operada no comportamento dos médicos, antes e após contacto com esta nova competência, aspirámos qualificar e entender as expectativas dos futuros licenciados em relação a este objectivo. Assim, o recurso à Análise de Correlações Canónicas Não Lineares permitiu, não só uma descrição multidimensional de topologias e/ou tipologias de indivíduos, como também analisou as relações entre as várias respostas, acomodadas em escalas óptimas, determinando, deste modo, similitudes/dissimilitudes entre as opiniões manifestadas, no decurso do processo de formação médica

Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device

Microwave Imaging (MWI) is an emerging medical imaging technique, which has been studied to aid breast cancer diagnosis in the frequency range from 0.5 to 30 GHz. The information about the dielectric properties of each tissue is essential to assess the viability of this type of systems. However, accurate measurements of heterogeneous tissues can be very challenging, and the current available information is still very limited. In this paper, we present a methodology for extracting dielectric properties to create anatomical models of the axillary region. These models will be used in a MWI device to aid breast cancer diagnosis through the detection of metastasised axillary lymph nodes. We apply segmentation tools to Magnetic Resonance Images (MRI) of the breast and assign dielectric properties to each tissue, extracting preliminary information about the properties of axillary lymph nodes. This study may open a way to more quickly extract dielectric properties of tissues and/or validate measurements, accelerating the development of microwave-based medical devices.The authors would like to acknowledge the study with ref. CES/44/2019/ME in Hospital da Luz Lisboa (19/09/2019).info:eu-repo/semantics/publishedVersio