Child abuse monitor system model: a health care critical knowledge monitor system

The Childhood protection is a subject with high value for the society, but, the Child Abuse cases are difficult to identify. The process from suspicious to accusation is very difficult to achieve. It must configure very strong evidences. Typically, Health Care services deal with these cases from the beginning where there are evidences based on the diagnosis, but they aren’t enough to promote the accusation. Besides that, this subject it’s highly sensitive because there are legal aspects to deal with such as: the patient privacy, paternity issues, medical confidentiality, among others. We propose a Child Abuses critical knowledge monitor system model that addresses this problem. This decision support system is implemented with a multiple scientific domains: to capture of tokens from clinical documents from multiple sources; a topic model approach to identify the topics of the documents; knowledge management through the use of ontologies to support the critical knowledge sensibility concepts and relations such as: symptoms, behaviors, among other evidences in order to match with the topics inferred from the clinical documents and then alert and log when clinical evidences are present. Based on these alerts clinical personnel could analyze the situation and take the appropriate procedures.

Avaliação do desempenho de indicadores com base na metodologia ROC (Receiver Operating Characteristic)

Dissertação de mestrado em Bioinformática

Clustering-based approach for categorizing pregnant women in obstetrics and maternity care

When a pregnant woman is guided to a hospital for obstetrics purposes, many outcomes are possible, depending on her current conditions. An improved understanding of these conditions could provide a more direct medical approach by categorizing the different types of patients, enabling a faster response to risk situations, and therefore increasing the quality of services. In this case study, the characteristics of the patients admitted in the maternity care unit of Centro Hospitalar of Porto are acknowledged, allowing categorizing the patient women through clustering techniques. The main goal is to predict the patients’ route through the maternity care, adapting the services according to their conditions, providing the best clinical decisions and a cost-effective treatment to patients. The models developed presented very interesting results, being the best clustering evaluation index: 0.65. The evaluation of the clustering algorithms proved the viability of using clustering based data mining models to characterize pregnant patients, identifying which conditions can be used as an alert to prevent the occurrence of medical complications.

Predicting plateau pressure in intensive medicine for ventilated patients

Barotrauma is identified as one of the leading diseases in Ventilated Patients. This type of problem is most common in the Intensive Care Units. In order to prevent this problem the use of Data Mining (DM) can be useful for predicting their occurrence. The main goal is to predict the occurence of Barotrauma in order to support the health professionals taking necessary precautions. In a first step intensivists identified the Plateau Pressure values as a possible cause of Barotrauma. Through this study DM models (classification) where induced for predicting the Plateau Pressure class (>=30 cm

Predicting preterm birth in maternity care by means of data mining

Worldwide, around 9% of the children are born with less than 37 weeks of labour, causing risk to the premature child, whom it is not prepared to develop a number of basic functions that begin soon after the birth. In order to ensure that those risk pregnancies are being properly monitored by the obstetricians in time to avoid those problems, Data Mining (DM) models were induced in this study to predict preterm births in a real environment using data from 3376 patients (women) admitted in the maternal and perinatal care unit of Centro Hospitalar of Oporto. A sensitive metric to predict preterm deliveries was developed, assisting physicians in the decision-making process regarding the patients’ observation. It was possible to obtain promising results, achieving sensitivity and specificity values of 96% and 98%, respectively.

Step towards multiplatform framework for supporting pediatric and neonatology care unit decision process

Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.

Step towards a patient timeline in intensive care units

In Intensive Medicine, the presentation of medical information is done in many ways, depending on the type of data collected and stored. The way in which the information is presented can make it difficult for intensivists to quickly understand the patient's condition. When there is the need to cross between several types of clinical data sources the situation is even worse. This research seeks to explore a new way of presenting information about patients, based on the timeframe in which events occur. By developing an interactive Patient Timeline, intensivists will have access to a new environment in real-time where they can consult the patient clinical history and the data collected until the moment. The medical history will be available from the moment in which patients is admitted in the ICU until discharge, allowing intensivist to examine data regarding vital signs, medication, exams, among others. This timeline also intends to, through the use of information and models produced by the INTCare system, combine several clinical data in order to help diagnose the future patients’ conditions. This platform will help intensivists to make more accurate decision. This paper presents the first approach of the solution designed

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Extending the reservoir of bla IMP-5: the emerging pathogen Acinetobacter bereziniae

Acinetobacter bereziniae clinical relevance is starting to be recognized; however, very few descriptions of its carbapenem resistance currently exist. Here we characterize two carbapenem-resistant A. bereziniae isolates. Materials & methods: Isolates were obtained from environmental and clinical samples. Carbapenemases were searched by phenotypic, biochemical and PCR assays. Clonality was studied by ApaI-PFGE and genetic location for carbapenemase genes were assessed by I-CeuI and S1 hybridizations. Results: Isolates were not clonally related but both produced the exclusively Portuguese IMP-5, with the clinical isolate also producing an OXA-58. The carbapenemase genes were plasmid located. Conclusion: Our results emphasize the role of non-baumannii Acinetobacter species as important reservoirs of clinically relevant resistance genes that could also contribute to their emergence as nosocomial pathogens

Spousal support and satisfaction with healthcare services as moderators between psychological morbidity and adherence to diet in Type 2 Diabetes patients

Objectives: This study analyzed the moderating role of partners’ support and satisfaction with healthcare services in the relationship between psychological morbidity and adherence to diet in patients with type 2 diabetes (T2DM). Methods: Participants were 387 recently diagnosed T2DM patients that answered the following instruments: Revised Summary of Diabetes Self- Care Activities Measure, Hospital Anxiety and Depression Scales, Multidimensional Diabetes Questionnaire and Patient Satisfaction Questionnaire. Results: Partners’ positive and negative support moderated the relationship between psychological morbidity and adherence to diet. Satisfaction with healthcare services also moderated the relationship between psychological morbidity and adherence to diet. Conclusions: Intervention programs to promote adherence to diet in patients with type 2 diabetes should focus on partners’ support and patient satisfaction with healthcare services.

Assistive locomotion strategies for active lower limb devices

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)

Alcohol-dependent patients receiving specialised outpatient care: an overview of gender issues

OBJECTIVE: The objective of the present study, with focus on gender, was aimed at evaluating alcohol-dependent individual in terms of socio-demographic variables related to alcohol consumption and therapeutic interventions. METHODS: This is a retrospective cross-sectional study of 1,051 patients (833 men and 218 women), with diagnosis of alcohol dependence syndrome, according to ICD-10 criteria, who had sought treatment for the first time at a specialised health centre between 2000 and 2006. RESULTS: The results showed that women, compared to men, are more likely to be unemployed and without partner, in addition to having higher educational level, latter age of alcohol initiation, needing less outpatient alcohol detoxification program, consuming more fermented beverage, presenting less psychiatric comorbidities, and using less coadjutant medications during treatment. CONCLUSION: We can state that some peculiarities exist permeating both gender and alcohol consumption. A further focus on the characteristics of each population is needed to facilitate the adequate use of therapeutic interventions according to gender specificities.

Quality of life assessment of patients with schizophrenic spectrum disorders from Psychosocial Care Centers

OBJECTIVE: Assessing the quality of life and the clinical and social-demographic factors associated in schizophrenic spectrum patients (ICD-10 F20-F29) attending CAPS at the programmatic area 3.0. METHODS: A cross-sectional study was carried out in a sample of schizophrenic spectrum patients who have been enrolled in 2008 in CAPS in programmatic area (AP) 3 at Rio de Janeiro city, using MINIPLUS to assess schizophrenia spectrum disorder and use of psychoactive substances, Positive and Negative Symptoms Scale (PANSS) to assess psychiatric symptoms and Quality of Life Scale (QLS-BR) to assess the quality of life. RESULTS: Seventy nine patients were included, of whom 74 (93.7%) presented some impairment in quality of life. The most frequently affected area was occupational performance. Variables that showed a significant association with severe impairment of quality of life were: marital status, race, occupation, who patients lived with, homelessness, having children, previous psychiatric hospitalization, negative symptoms and symptoms designated as not applicable (being characterized by a lack of typical positive and negative symptoms). CONCLUSION: The knowledge of these factors should be crucial to implement health policies and psychosocial rehabilitation programs focused on improving the quality of life of these patients.

Aplicação da metodologia ROC na avaliação de desempenho de índices de gravidade clínica em unidades de neonatologia de Portugal

Tese de Doutoramento em Engenharia Industrial e de Sistemas

Psychiatric morbidity and quality of life of primary care attenders in two cities in Brazil

Objective: To identify the associations among quality of life (QoL), social determinants and psychological distress in primary care in two cities in Brazil. Methods: A cross-sectional study with 1,466 patients from 2009 to 2010. The statistical analysis used the t-test to compare the variables of interest to the study. Results: The prevalence of Common Mental Disorders (CMD3), severe forms of Common Mental Disorders (CMD5), anxiety and depression were 20.5%, 32%, 37% and 25.1% respectively. Thes presence of psychological distress is associated with worse QoL among the patients studied, especially those older than 40 years of age. In cases of CMD3, those with higher income and educational levels presented higher QoL in the psychical and psychological domains. For the cases of probable anxiety, those with higher educational levels presented lower scores on the physical and social relationship scores. Conclusion: Psychological distress can be associated with a worse QoL among those studied and can be influenced by socioeconomic conditions. Therefore, it is important to structure patient-centered help, which should also include patients’ social contexts.