O hospital da misericórdia de Penafiel (1600-1850)

Tese de Doutoramento em História - Especialidade de Idade Moderna

Adhesive bioactive coatings inspired by sea life

Inspired by nature, in particular by the marine mussels adhesive proteins (MAPs) and by the tough brick-and-mortar nacre-like structure, novel multilayered films are prepared in the present work. Organic-inorganic multilayered films, with an architecture similar to nacre based on bioactive glass nanoparticles (BG), chitosan and hyaluronic acid modified with catechol groups, which are the main responsible for the outstanding adhesion in MAPs, are developed for the first time. The biomimetic conjugate is prepared by carbodiimide chemistry and analyzed by ultraviolet-visible spectrophotometry. The build-up of the multilayered films is monitored with a quartz crystal microbalance with dissipation monitoring and their topography is characterized by atomic force microscopy. The mechanical properties reveal that the films containing catechol groups and BG present an enhanced adhesion. Moreover, the bioactivity of the films upon immersion in a simulated body fluid solution for 7 days is evaluated by scanning electron microscopy coupled with energy dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy and X-ray diffraction. It was found that the constructed films promote the formation of bone-like apatite in vitro. Such multifunctional mussel inspired LbL films, which combine enhanced adhesion and bioactivity, could be potentially used as coatings of a variety of implants for orthopedic applications.

Intervenção precoce na perturbação do espetro do autismo: preocupações e apoios das famílias

Dissertação de mestrado em Educação Especial (área de especialização em Intervenção Precoce)

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.

Postpartum Depression: Is it a condition affecting the mother-infant interaction and the development of the child across the first year of life?

Noting that maternal depression is common during a baby's first year, this study examined the interaction of depressed and non-depressed mother-child dyads. A sample of 26 first-time mothers with postpartum depression at the third month after birth and their 3-month-old infants was compared to a sample of 25 first-time mothers with no postpartum depression at the third month after birth and their 3-month-old infants. The observations were repeated at 6 months and again at 12 months postpartum. The samples were compared for differences in mother interaction behavior, mother's infant care, mother's concern with the baby, infant behavioral difficulties, infant mental and motor development, and infant behavior with the observer. Among the findings are the following: (1) depressed mothers' interaction behavior and care of their infants are less adequate than the non-depressed mothers' interaction behavior and care of their infants at 3, 6, and 12 months postpartum; (2) infants' interaction behaviors during feeding and face-to-face interaction with depressed mothers are less adequate than infants' interactions with non-depressed mothers at 3, 6, and 12 months postpartum; (3) mother-infant interactions are less adequate in the depressed mother dyads than the non-depressed dyads at 3, 6, and 12 months postpartum; (4) depressed mothers are less concerned about their infants than non-depressed mothers at 3, 6, and 12 months postpartum; (5) infants of depressed mothers have more behavioral difficulties at 3, 6, and 12 months postpartum than infants of non-depressed mothers; (6) infants of depressed mothers had lower mental and motor development rates at 6 and 12 months postpartum than infants of non-depressed mothers; and (7) infants of non-depressed mothers behaved in a more positive way with the observer than the infants of depressed mothers. (AS)

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.

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.

A clinical recommendation system to maternity care

Nowadays in healthcare, the Clinical Decision Support Systems are used in order to help health professionals to take an evidence-based decision. An example is the Clinical Recommendation Systems. In this sense, it was developed and implemented in Centro Hospitalar do Porto a pre-triage system in order to group the patients on two levels (urgent or outpatient). However, although this system is calibrated and specific to the urgency of obstetrics and gynaecology, it does not meet all clinical requirements by the general department of the Portuguese HealthCare (Direção Geral de Saúde). The main requirement is the need of having priority triage system characterized by five levels. Thus some studies have been conducted with the aim of presenting a methodology able to evolve the pre-triage system on a Clinical Recommendation System with five levels. After some tests (using data mining and simulation techniques), it has been validated the possibility of transformation the pre-triage system in a Clinical Recommendation System in the obstetric context. This paper presents an overview of the Clinical Recommendation System for obstetric triage, the model developed and the main results achieved.

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.