Mother-to-infant emotional involvement at birth

Objectives. To study mother-to-infant emotional involvement at birth, namely factors (socio-demographics, previous life events, type of delivery, pain at childbirth, support from partner, infant characteristics, early experiences with the newborn, and mother’s mood) that interfere with the mother’s positive, negative and not clear emotions toward the newborn. Methods. The Bonding Scale (an extended Portuguese version of the ‘New Mother-to-Infant Bonding Scale’) and the Edinburgh Postnatal Depression Scale were administrated during the first after delivery days to 315 mothers recruited at Ju´lio Dinis Maternity Hospital (MJD, Porto, Portugal). Results. A worse emotional involvement with the newborn was observed when the mother was unemployed, unmarried, had less than grade 9, previous obstetrical/psychological problems or was depressed, as well as when the infant was female, had neonatal problems or was admitted in the intensive care unit. Lower total bonding results were significantly predicted when the mother was depressed and had a lower educational level; being depressed, unemployed and single predicted more negative emotions toward the infant as well. No significant differences in the mother-to-infant emotional involvement were obtained for events related to childbirth, such as type of delivery, pain and partner support, or early experiences with the newborn; these events do not predict mother’s bonding results either. Conclusion. The study results support the need for screening and supporting depressed, unemployed and single mothers, in order to prevent bonding difficulties with the newborn at birth.

Utentes da Consulta Externa de Ginecologia/Obstetrícia da Maternidade Júlio Dinis

Com o objectivo de fazer a caracterização da situação social e demográfica e das condições de saúde médica e psicológica das utentes da Consulta Externa de Ginecologia/Obstretícia da Maternidade Júlio Dinis e de seus companheiros, duzentas mulheres e cento e setenta e cinco homens (N=375) foram entrevistados com base num questionário desenhado para o efeito, durante o primeiro trimestre de gestação. Observamos o desfavorecimento social e económico da amostra, particularmente no grupo das mulheres. Constatamos que a situação matrimonial e familiar é estável; no entanto, muitos agregados familiares são recentes, incluem outros familiares e este é um primeiro filho do casal. A rede de apoio social e emocional da amostra é geralmente constituída por familiares, estando mais presente para as mulheres do que para os homens e muitas vezes o companheiro não é referido como confidente, sobretudo pelas mulheres. A gestação não é geralmente de risco; não obstante, a presença frequente de problemas psicológicos uma pior aceitação inicial da gravidez no caso das mulheres. Os hábitos de vida tornam-se mais saudáveis com a gestação; no entanto, é ainda elevado o consumo de substâncias, como o tabaco, pela grávida. Problemas ginecológicos e obstétricos foram referidos, assim como a presença de adversidades na história psicológica e desenvolvimental dos participantes. Concluímos que as utentes da Consulta Externa de Ginecologia/Obstetrícia da Maternidade Júlio Dinis e seus companheiros apresentam indicadores relevantes de risco médico, psicológico e social que devem ser considerados na prestação de melhores cuidados de saúde.

Pervasive patient timeline for intensive care units

This research work explores a new way of presenting and representing information about patients in critical care, which is the use of a timeline to display information. This is accomplished with the development of an interactive Pervasive Patient Timeline able to give to the intensivists an access in real-time to an environment containing patients clinical information from the moment in which the patients are admitted in the Intensive Care Unit (ICU) until their discharge This solution allows the intensivists to analyse data regarding vital signs, medication, exams, data mining predictions, among others. Due to the pervasive features, intensivists can have access to the timeline anywhere and anytime, allowing them to make decisions when they need to be made. This platform is patient-centred and is prepared to support the decision process allowing the intensivists to provide better care to patients due the inclusion of clinical forecasts.

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.