Ambulatory blood pressure monitoring and microalbuminuria in normotensive subjects with insulin-dependent diabetes mellitus

OBJECTIVE: To assess the association between microalbuminuria with ambulatory blood pressure monitoring in normotensive individuals with insulin-dependent diabetes mellitus. METHODS: Thirty-seven patients underwent determination of the rate of urinary excretion of albumin through radioimmunoassay and ambulatory blood pressure monitoring. Their mean age was 26.5±6.7 years, and the mean duration of their disease was 8 (1-34) years. Microalbuminuria was defined as urinary excretion of albumin > or = 20 and <200µg/min in at least 2 out of 3 urine samples. RESULTS: Nine (24.3%) patients were microalbuminuric. Ambulatory blood pressure monitoring in the microalbuminuric patients had higher mean pressure values, mainly the systolic pressure, during sleep as compared with that in the normoalbuminuric patients (120.1±8.3 vs 110.8±7.1 mmHg; p=0.007). The pressure load was higher in the microalbuminuric individuals, mainly the systolic pressure load during wakefulness [6.3 (2.9-45.9) vs 1.6 (0-16%); p=0.001]. This was the variable that better correlated with the urinary excretion of albumin (rS=0.61; p<0.001). Systolic pressure load >50% and diastolic pressure load > 30% during sleep was associated with microalbuminuria (p=0.008). The pressure drop during sleep did not differ between the groups. CONCLUSION: Microalbuminuric normotensive insulin-dependent diabetic patients show greater mean pressure value and pressure load during ambulatory blood pressure monitoring, and these variables correlate with urinary excretion of albumin.

Final report detailed description - NET Station: shaping radio for web environment

In more scientific terms, NET Station contributed to: - discuss in theoretical terms the role radio still play in contemporary societies; - examine how audiences are using sound resources on the Web; - draw up a new theoretical framework for the study of the reconfiguration of radio language on the Internet;acknowledge that people are not abandoning radio as a medium; the survey applied by the team demonstrated that there is a complementariness between traditional radio and radio on the Internet; - understand that people expect more interactivity, more opportunities to participate in content production and more diversity of contents. These results were shared with editors responsible for Portuguese radio and might influence the offer made available by these radio corporations from now on; - demonstrate that the Internet is underexplored in terms of sound and acoustic communication; - promote the production of new sound narratives to be available on the Internet;

Avaliação da eficiência de projetos de reabilitação ambiental de áreas mineiras abandonadas: o caso da área mineira de Covas

Dissertação de mestrado em Geociências (área de especialização em Valorização de Recursos Geológicos)

BIOMedical search engine framework: lightweight and customized implementation of domain-specific biomedical search engines

The Smart Drug Search is publicly accessible at http://sing.ei.uvigo.es/sds/. The BIOMedical Search Engine Framework is freely available for non-commercial use at https://github.com/agjacome/biomsef

Ambulatory blood pressure monitoring of patients with heart failure: a new prognosis marker

OBJECTIVE: To evaluate the relationship between 24-hour ambulatory arterial blood pressure monitoring and the prognosis of patients with advanced congestive heart failure. METHODS: We studied 38 patients with NYHA functional class IV congestive heart failure, and analyzed left ventricular ejection fraction, diastolic diameter, and ambulatory blood pressure monitoring data. RESULTS: Twelve deaths occurred. Left ventricular ejection fraction (35.2±7.3%) and diastolic diameter (72.2±7.8mm) were not correlated with the survival. The mean 24-hour (SBP24), waking (SBPw), and sleeping (SBPs) systolic pressures of the living patients were higher than those of the deceased patients and were significant for predicting survival. Patients with mean SBP24, SBPv, and SBPs > or = 105mmHg had longer survival (p=0.002, p=0.01 and p=0.0007, respectively). Patients with diastolic blood pressure sleep decrements (dip) and patients with mean blood pressure dip <=6mmHg had longer survival (p=0.04 and p=0.01, respectively). In the multivariate analysis, SBPs was the only variable with an odds ratio of 7.61 (CI: 1.56; 3704) (p=0.01). Patients with mean SBP<105mmHg were 7.6 times more likely to die than those with SBP > or = 105 mmHg CONCLUSION: Ambulatory blood pressure monitoring appears to be a useful method for evaluating patients with congestive heart failure.

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.

Towards a pervasive data mining engine: architecture overview

Current data mining engines are difficult to use, requiring optimizations by data mining experts in order to provide optimal results. To solve this problem a new concept was devised, by maintaining the functionality of current data mining tools and adding pervasive characteristics such as invisibility and ubiquity which focus on their users, providing better ease of use and usefulness, by providing autonomous and intelligent data mining processes. This article introduces an architecture to implement a data mining engine, composed by four major components: database; Middleware (control); Middleware (processing); and interface. These components are interlinked but provide independent scaling, allowing for a system that adapts to the user’s needs. A prototype has been developed in order to test the architecture. The results are very promising and showed their functionality and the need for further improvements.

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.

Influence of Quality of Sleep on the Nocturnal Decline in Blood Pressure During Ambulatory Blood Pressure Monitoring

OBJECTIVE: To assess the influence of the quality of sleep on the nocturnal physiological drop in blood pressure during ambulatory blood pressure monitoring. METHODS: We consecutively assessed ambulatory blood pressure monitoring, the degree of tolerance for the examination, and the quality of sleep in 168 patients with hypertension or with the suspected "white-coat" effect. Blood pressure fall during sleep associated with a specific questionnaire and an analogical visual scale of tolerance for ambulatory blood pressure monitoring were used to assess usual sleep and sleep on the day of examination. Two specialists in sleep disturbances classified the patients into 2 groups: those with normal sleep and those with abnormal sleep. RESULTS: Fifty-nine (35 %) patients comprised the abnormal sleep group. Findings regarding the quality of sleep on the day of ambulatory blood pressure monitoring as compared with those regarding the quality of sleep on a usual day were different and were as follows, respectively: total duration of sleep (-12.4±4.7 versus -42.2±14.9 minutes, P=0.02), latency of sleep (0.4±2.7 versus 17±5.1 minutes, P<0.001), number of awakenings (0.1±0.1 versus 1.35±0.3 times, P<0.001), and tolerance for ambulatory blood pressure monitoring (8±0.2 versus 6.7±0.35, P=0.035). An abnormal drop in blood pressure during sleep occurred in 20 (18%) patients in the normal sleep group and in 14 (24%) patients in the abnormal sleep group, P=0.53. CONCLUSION: Ambulatory blood pressure monitoring causes sleep disturbances in some patients, and a positive association between quality of sleep and tolerance for the examination was observed.

Predicting pre-triage waiting time in a maternity emergency room through data mining

An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child’s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients’ waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.

Incorporation of hybrid phase change materials in plastering mortars for increased energy efficiency in buildings

Tese de Doutoramento em Engenharia Civil.