Mother’s depression at childbirth does not contribute to the effects of antenatal depression on neonate’s behavioral development

Background: Maternal depression is a worldwide phenomenon that has been linked to adverse developmental outcomes in neonates. Aims: To study the effect of antenatal depression (during the third trimester of pregnancy) on neonate behavior, preference, and habituation to both the mother and a stranger’s face/voice. To analyze mother’s depression at childbirth as a potential mediator or moderator of the relationship between antenatal depression and neonate behavioral development. Method: A sample of 110 pregnant women was divided in 2 groups according to their scores on the Edinburgh Postnatal Depression Scale during pregnancy (EPDS; ≥10, depressed; <10, non-depressed). In the first 5 days after birth, neonatal performance on the Neonatal Behavioral Assessment Scale (NBAS) and in the ‘Preference and habituation to the mother’s face/voice versus stranger’ paradigm was assessed; each mother filled out an EPDS. Results: Neonates of depressed pregnant women, achieved lower scores on the NBASs (regulation of state, range of state, and habituation); did not show a visual/auditory preference for the mother’s face/voice; required more trials to become habituated to the mother’s face/voice; and showed a higher visual/auditory preference for the stranger’s face/voice after habituation compared to neonates of non-depressed pregnant women. Depression at childbirth does not contribute to the effect of antenatal depression on neonatal behavioral development. Conclusion: Depression even before childbirth compromises the neonatal behavioral development. Depression is a relevant issue and should be addressed as a routine part of prenatal health care.

Estudo de validação da versão portuguesa da Alarm Distress Baby Scale (ADBB)

Contexto. O comportamento de retraimento social prolongado da criança é um importante sinal de alarme, quer tenha origem orgânica, psicológica e/ou social. A. Guédeney construiu a Alarm Distress Baby Scale (ADBB), para identificar este comportamento no contexto da consulta pediátrica ou da observação psicológica. Objectivos. Validação da versão portuguesa da ADBB destinada a avaliar o comportamento de retraimento social de crianças com idades compreendidas entre 2 e 24 meses. Metodologia A ADBB e as Bayley Scales of Infant Development (BSID) foram administradas a uma amostra de 130 lactentes com 3 meses de idade, cujas mães preencheram a versão portuguesa da Edinburgh Postnatal Depression Scale (EPDS); 51 bebés foram novamente avaliados aos 12 meses de idade. Resultados. Os itens da ADBB organizam-se satisfatoriamente em duas sub-escalas. A consistência interna do instrumento é razoável (alpha de Cronbach = .587). A validade externa é elevada: a correlação entre os resultados na ADBB e nas BSID é muito significativa - os bebés que aos 3 meses apresentam um resultado igual ou superior a 5 na ADBB evidenciam menor desenvolvimento nas BSID. Os resultados testemunham ainda que bebés de mães deprimidas (EPDS ≥ 12) mostram mais sinais de retraimento social do que os bebés das mães não deprimidas. Conclusão. A escala permite detectar crianças a necessitar de ajuda no sentido de contrariar o retraimento social que encetaram em relação ao meio. Desenhada para sinalizar tão precocemente quanto possível o retraimento social do lactente, e na medida em que este é um comprovado sinal da perturbação do desenvolvimento, a ADBB pode estimular os clínicos na procura das suas causas e na intervenção junto das mesmas. Estudos em amostras de crianças com mais idade são necessários. No entanto, os resultados obtidos apontam que a Versão portuguesa da ADBB é robusta e válida.

Qualidade da vinculação e dos relacionamentos significativos na gravidez

O estudo apresentado neste artigo destinou-se a investigar a qualidade da vinculação e das relações significativas na gravidez. Mais precisamente, teve por objectivos (1) determinar as características sociais e demográficas e as condições anteriores de existência que se associam e permitem prever um estilo de vinculação (in)seguro e (2) estimar o impacto do estilo de vinculação na qualidade do relacionamento e do apoio por parte do companheiro e de uma outra pessoa significativa, na gravidez. Uma amostra de 130 grávidas (66 adolescentes e 64 adultas) foi avaliada no último trimestre de gestação quanto ao estilo de vinculação e à qualidade do relacionamento e do apoio por parte do companheiro e de uma outra pessoa significativa (com base na Attachment Style Interview, ASI; Bifulco, Figueiredo, Guedeney, Gorman, Hays et al., 2004; Bifulco, Moran, Ball & Bernazzani, 2002a; Bifulco, Moran, Ball & Lillie, 2002b). A amostra foi recolhida na Maternidade de Júlio Dinis (Porto) e é bastante heterogénea do ponto de vista social e demográfico, em características como: a idade, o nível educacional, o estado civil, o estatuto ocupacional e o tipo de agregado familiar, embora fundamentalmente constituída por grávidas primíparas. Os resultados mostram que um estilo inseguro de vinculação pode ser previsto na sequência de separação ou divórcio parental durante a infância ou adolescência e quando a grávida está desempregada, e que a gravidez na adolescência se associa ao estilo de vinculação desligado. Mostram ainda que um estilo inseguro de vinculação permite prever um pior relacionamento na gravidez, quer com o companheiro, quer com a outra pessoa significativa, principalmente a presença de relações discordantes com o companheiro e de relações apáticas com a outra pessoa significativa. As estratégias emaranhadas afectam a relação com o companheiro (em aspectos como menos confiança, menos suporte emocional e mais interacção negativa), mas não a relação com a outra pessoa significativa; enquanto as estratégias desligadas afectam a relação com a outra pessoa significativa (em aspectos como menos actividades partilhadas e menos interacção positiva), mas não a relação com o companheiro, e as estratégias amedrontadas afectam o relacionamento, tanto com o companheiro (em aspectos como menor sentimento de ligação) quanto com a outra pessoa significativa (em aspectos como menos confiança). De acordo com a Teoria da Vinculação, conclui-se que condições adversas de existência (anteriores e actuais) propiciam vinculação insegura e que o estilo de vinculação interfere na qualidade do relacionamento com o companheiro e com outras pessoas significativas, nomeadamente na capacidade da grávida recorrer a apoio.

Critical events in mechanically ventilated patients

Mechanical Ventilation is an artificial way to help a Patient to breathe. This procedure is used to support patients with respiratory diseases however in many cases it can provoke lung damages, Acute Respiratory Diseases or organ failure. With the goal to early detect possible patient breath problems a set of limit values was defined to some variables monitored by the ventilator (Average Ventilation Pressure, Compliance Dynamic, Flow, Peak, Plateau and Support Pressure, Positive end-expiratory pressure, Respiratory Rate) in order to create critical events. A critical event is verified when a patient has a value higher or lower than the normal range defined for a certain period of time. The values were defined after elaborate a literature review and meeting with physicians specialized in the area. This work uses data streaming and intelligent agents to process the values collected in real-time and classify them as critical or not. Real data provided by an Intensive Care Unit were used to design and test the solution. In this study it was possible to understand the importance of introduce critical events for Mechanically Ventilated Patients. In some cases a value is considered critical (can trigger an alarm) however it is a single event (instantaneous) and it has not a clinical significance for the patient. The introduction of critical events which crosses a range of values and a pre-defined duration contributes to improve the decision-making process by decreasing the number of false positives and having a better comprehension of the patient condition.

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.

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.

Step towards to improve the voluntary interruption of pregnancy by means of business intelligence

With the implementation of Information and Communication Technologies in the health sector, it became possible the existence of an electronic record of information for patients, enabling the storage and the availability of their information in databases. However, without the implementation of a Business Intelligence (BI) system, this information has no value. Thus, the major motivation of this paper is to create a decision support system that allows the transformation of information into knowledge, giving usability to the stored data. The particular case addressed in this chapter is the Centro Materno Infantil do Norte, in particular the Voluntary Interruption of Pregnancy unit. With the creation of a BI system for this module, it is possible to design an interoperable, pervasive and real-time platform to support the decision-making process of health professionals, based on cases that occurred. Furthermore, this platform enables the automation of the process for obtaining key performance indicators that are presented annually by this health institution. In this chapter, the BI system implemented in the VIP unity in CMIN, some of the KPIs evaluated as well as the benefits of this implementation are presented.

Determination of the importance of iron acquisition for Staphylococcus epidermidis biofilm survival in human blood

Dissertação de mestrado em Bioengenharia

Development of nanohydrogels as a vehicle for the release of bioactive compounds in food matrices

PhD in Chemical and Biological Engineering

Pre-clinical trials for Machado-Joseph Disease: Hypothesis-based and hypothesis-free therapeutic approaches

Tese de Doutoramento em Ciências da Saúde

A realização do sujeito em complementos infinitivos de verbos causativos e percetivos no português língua de herança

Dissertação de mestrado em Ciências da Linguagem

Electronic tongue: a versatile tool for mineral and fruit-flavored waters recognition

Natural mineral waters (still), effervescent natural mineral waters (sparkling) and aromatized waters with fruit-flavors (still or sparkling) are an emerging market. In this work, the capability of a potentiometric electronic tongue, comprised with lipid polymeric membranes, to quantitatively estimate routinely quality physicochemical parameters (pH and conductivity) as well as to qualitatively classify water samples according to the type of water was evaluated. The study showed that a linear discriminant model, based on 21 sensors selected by the simulated annealing algorithm, could correctly classify 100 % of the water samples (leave-one out cross-validation). This potential was further demonstrated by applying a repeated K-fold cross-validation (guaranteeing that at least 15 % of independent samples were only used for internal-validation) for which 96 % of correct classifications were attained. The satisfactory recognition performance of the E-tongue could be attributed to the pH, conductivity, sugars and organic acids contents of the studied waters, which turned out in significant differences of sweetness perception indexes and total acid flavor. Moreover, the E-tongue combined with multivariate linear regression models, based on sub-sets of sensors selected by the simulated annealing algorithm, could accurately estimate waters pH (25 sensors: R 2 equal to 0.99 and 0.97 for leave-one-out or repeated K-folds cross-validation) and conductivity (23 sensors: R 2 equal to 0.997 and 0.99 for leave-one-out or repeated K-folds cross-validation). So, the overall satisfactory results achieved, allow envisaging a potential future application of electronic tongue devices for bottled water analysis and classification.

Experimental validation of a proposed single-phase five-level active rectifier operating with model predictive current control

This paper presents a model predictive current control applied to a proposed single-phase five-level active rectifier (FLAR). This current control strategy uses the discrete-time nature of the active rectifier to define its state in each sampling interval. Although the switching frequency is not constant, this current control strategy allows to follow the reference with low total harmonic distortion (THDF). The implementation of the active rectifier that was used to obtain the experimental results is described in detail along the paper, presenting the circuit topology, the principle of operation, the power theory, and the current control strategy. The experimental results confirm the robustness and good performance (with low current THDF and controlled output voltage) of the proposed single-phase FLAR operating with model predictive current control.

Participação estudantil no Facebook: processos, modalidades e motivações

Tese de Doutoramento em Ciências da Comunicação.