Web-application for gathering, analyzing, and processing health information about allergy data

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Participatory mapping in the design process of a spatial data infrastructure SDI: a case study in the Biosphere Reserve Rio Platano (Honduras)

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Spatial Patterns and Irregularities of the electoral data: general elections in Canada

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Collecting data for indoor mapping of the university of Münster via a location based game

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Nosocomial infections in a Brazilian neonatal intensive care unit: a 4-year surveillance study

INTRODUCTION: Report the incidence of nosocomial infections, causative microorganisms, risk factors associated with and antimicrobial susceptibility pattern in the NICU of the Uberlândia University Hospital. METHODS: Data were collected through the National Healthcare Safety Network surveillance from January 2006 to December 2009. The patients were followed five times/week from their birth to their discharge or death. RESULTS: The study included 1,443 patients, 209 of these developed NIs, totaling 293 NI episodes, principally bloodstream infections (203; 69.3%) and conjunctivitis (52; 17.7%). Device-associated infection rates were as follows: 17.3 primary bloodstream infections per 1,000 central line-days and 3.2 pneumonias per 1000 ventilator-days. The mortality rate in neonates with NI was 11.9%. Mechanical ventilation, total parenteral nutrition, orogastric tube, previous antibiotic therapy, use of CVC and birth weight of 751-1,000g appeared to be associated with a significantly higher risk of NI (p < 0.05). In multiple logistic regression analysis for NI, mechanical ventilation and the use of CVC were independent risk factors (p < 0.05). Coagulase- negative Staphylococcus (CoNS) (36.5%) and Staphylococcus aureus (23.6%) were the most common etiologic agents isolated from cultures. The incidences of oxacillin-resistant CoNS and S. aureus were 81.8% and 25.3%, respectively. CONCLUSIONS: Frequent surveillance was very important to evaluate the association of these well-known risk factors with NIs and causative organisms, assisting in drawing the attention of health care professionals to this potent cause of morbidity.

How effective is dog culling in controlling zoonotic visceral leishmaniasis? a critical evaluation of the science, politics and ethics behind this public health policy

INTRODUCTION: Zoonotic kala-azar, a lethal disease caused by protozoa of the genus Leishmania is considered out of control in parts of the world, particularly in Brazil, where transmission has spread to cities throughout most of the territory and mortality presents an increasing trend. Although a highly debatable measure, the Brazilian government regularly culls seropositive dogs to control the disease. Since control is failing, critical analysis concerning the actions focused on the canine reservoir was conducted. METHODS: In a review of the literature, a historical perspective focusing mainly on comparisons between the successful Chinese and Soviet strategies and the Brazilian approach is presented. In addition, analyses of the principal studies regarding the role of dogs as risk factors to humans and of the main intervention studies regarding the efficacy of the dog killing strategy were undertaken. Brazilian political reaction to a recently published systematic review that concluded that the dog culling program lacked efficiency and its effect on public policy were also reviewed. RESULTS: No firm evidence of the risk conferred by the presence of dogs to humans was verified; on the contrary, a lack of scientific support for the policy of killing dogs was confirmed. A bias for distorting scientific data towards maintaining the policy of culling animals was observed. CONCLUSIONS: Since there is no evidence that dog culling diminishes visceral leishmaniasis transmission, it should be abandoned as a control measure. Ethical considerations have been raised regarding distorting scientific results and the killing of animals despite minimal or absent scientific evidence

Antimicrobial use, incidence, etiology and resistance patterns in bacteria causing ventilator-associated pneumonia in a clinical-surgical intensive care unit

INTRODUCTION : Antimicrobial resistance is an increasing threat in hospitalized patients, and inappropriate empirical antimicrobial therapy is known to adversely affect outcomes in ventilator-associated pneumonia (VAP). The aim of this study was to evaluate antimicrobial usage, incidence, etiology, and antimicrobial resistance trends for prominent nosocomial pathogens causing ventilator-associated pneumonia in a clinical-surgical intensive care unit (ICU). METHODS : Gram-negative bacilli and Staphylococcus aureus causing VAP, as well as their antimicrobial resistance patterns and data on consumption (defined daily dose [DDD] per 1,000 patient days) of glycopeptides, extended-spectrum cephalosporins, and carbapenems in the unit were evaluated in two different periods (A and B). RESULTS: Antimicrobial use was high, mainly of broad-spectrum cephalosporins, with a significant increase in the consumption of glycopeptides (p < 0.0001) and carbapenems (p < 0.007) in period B. For Acinetobacter baumannii and members of the Enterobacteriaceae family, 5.27- and 3.06-fold increases in VAPs, respectively, were noted, and a significant increase in resistance rates was found for imipenem-resistant A. baumannii (p = 0.003) and third-generation cephalosporins-resistant Enterobacteriaceae (p = 0.01) isolates in this same period. CONCLUSIONS: Our results suggest that there is a link between antibiotics usage at institutional levels and resistant bacteria. The use of carbapenems was related to the high rate of resistance in A. baumannii and therefore a high consumption of imipenem/meropenem could play a major role in selective pressure exerted by antibiotics in A. baumannii strains.

Characterization of newborns with nonimmune hydrops fetalis admitted to a neonatal intensive care unit

PURPOSE: To determine the incidence and characteristics of nonimmune hydrops fetalis in the newborn population. METHOD: A retrospective study of the period between 1996 and 2000, including all newborns with a prenatal or early neonatal diagnosis of nonimmune hydrops fetalis, based on clinical history, physical examination, and laboratory evaluation. The following were analyzed: prenatal follow-up, delivery type, gender, birth weight, gestational age, presence of perinatal asphyxia, nutritional classification, etiopathic diagnosis, length of hospital stay, mortality, and age at death. RESULTS: A total of 47 newborns with hydrops fetalis (0.42% of live births), 18 (38.3%) with the immune form and 29 (61.7%) with the nonimmune form, were selected for study. The incidence of nonimmune hydrops fetalis was 1 per 414 neonates. Data was obtained from 21 newborns, with the following characteristics: 19 (90.5%) were suspected from prenatal diagnosis, 18 (85.7%) were born by cesarean delivery, 15 (71.4%) were female, and 10 (47.6%) were asphyxiated. The average weight was 2665.9 g, and the average gestational age was 35 3/7 weeks; 14 (66.6%) were preterm; 18 (85.0 %) appropriate delivery time; and 3 (14.3%) were large for gestational age. The etiopathic diagnosis was determined for 62%, which included cardiovascular (19.0%), infectious (9.5%), placental (4.8%), hematologic (4.7%), genitourinary (4.8%), and tumoral causes (4.8%), and there was a combination of causes in 9.5%. The etiology was classified as idiopathic in 38%. The length of hospital stay was 26.6 ± 23.6 days, and the mortality rate was 52.4%. CONCLUSIONS: The establishment of a suitable etiopathic diagnosis associated with prenatal detection of nonimmune hydrops fetalis can be an important step in reducing the neonatal mortality rate from this condition.

Ethical aspects in the management of the terminally ill patient in the pediatric intensive care unit

OBJECTIVE: To identify the prevalence of management plans and decision-making processes for terminal care patients in pediatric intensive care units. METHODOLOGY: Evidence-based medicine was done by a systematic review using an electronic data base (LILACS, 1982 through 2000) and (MEDLINE, 1966 through 2000). The key words used are listed and age limits (0 to 18 years) were used. RESULTS: One hundred and eighty two articles were found and after selection according to the exclusion/inclusion criteria and objectives 17 relevant papers were identified. The most common decisions found were do-not-resuscitation orders and withdrawal or withholding life support care. The justifications for these were "imminent death" and "unsatisfatory quality of life". CONCLUSION: Care management was based on ethical principles aiming at improving benefits, avoiding harm, and when possible, respecting the autonomy of the terminally ill patient.

Contributions towards smart cities : exploring block level census data for the characterization of change in Lisbon

The interest in using information to improve the quality of living in large urban areas and its governance efficiency has been around for decades. Nevertheless, the improvements in Information and Communications Technology has sparked a new dynamic in academic research, usually under the umbrella term of Smart Cities. This concept of Smart City can probably be translated, in a simplified version, into cities that are lived, managed and developed in an information-saturated environment. While it makes perfect sense and we can easily foresee the benefits of such a concept, presently there are still several significant challenges that need to be tackled before we can materialize this vision. In this work we aim at providing a small contribution in this direction, which maximizes the relevancy of the available information resources. One of the most detailed and geographically relevant information resource available, for the study of cities, is the census, more specifically the data available at block level (Subsecção Estatística). In this work, we use Self-Organizing Maps (SOM) and the variant Geo-SOM to explore the block level data from the Portuguese census of Lisbon city, for the years of 2001 and 2011. We focus on gauging change, proposing ways that allow the comparison of the two time periods, which have two different underlying geographical bases. We proceed with the analysis of the data using different SOM variants, aiming at producing a two-fold portrait: one, of the evolution of Lisbon during the first decade of the XXI century, another, of how the census dataset and SOM’s can be used to produce an informational framework for the study of cities.

A data-driven analytics approach in the study of pneumonia’s fatalities

As huge amounts of data become available in organizations and society, specific data analytics skills and techniques are needed to explore this data and extract from it useful patterns, tendencies, models or other useful knowledge, which could be used to support the decision-making process, to define new strategies or to understand what is happening in a specific field. Only with a deep understanding of a phenomenon it is possible to fight it. In this paper, a data-driven analytics approach is used for the analysis of the increasing incidence of fatalities by pneumonia in the Portuguese population, characterizing the disease and its incidence in terms of fatalities, knowledge that can be used to define appropriate strategies that can aim to reduce this phenomenon, which has increased more than 65% in a decade.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

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

Predicting type of delivery by identification of obstetric risk factors through data mining

In Maternity Care, a quick decision has to be made about the most suitable delivery type for the current patient. Guidelines are followed by physicians to support that decision; however, those practice recommendations are limited and underused. In the last years, caesarean delivery has been pursued in over 28% of pregnancies, and other operative techniques regarding specific problems have also been excessively employed. This study identifies obstetric and pregnancy factors that can be used to predict the most appropriate delivery technique, through the induction of data mining models using real data gathered in the perinatal and maternal care unit of Centro Hospitalar of Oporto (CHP). Predicting the type of birth envisions high-quality services, increased safety and effectiveness of specific practices to help guide maternity care decisions and facilitate optimal outcomes in mother and child. In this work was possible to acquire good results, achieving sensitivity and specificity values of 90.11% and 80.05%, respectively, providing the CHP with a model capable of correctly identify caesarean sections and vaginal deliveries.