Female gender but not season of birth is associated with mood seasonality in a near-equatorial Brazilian city

OBJECTIVE: Studies conducted mainly in countries located in the Northern Hemisphere have shown that season of birth influences mood seasonality. Greater mood seasonality has been observed for individuals born during spring/summer months than those born during autumn/winter months. Expanding past research to the Southern Hemisphere, in this study we examine the influence of season of birth on mood seasonality in a sample of 1,247 healthy young Brazilians. METHOD: The Seasonal Pattern Assessment Questionnaire was used to compute a global seasonality score as a measure of mood seasonality in a cross-sectional study. RESULTS: Analysis of covariance was conducted to examine the effects of month of birth and gender on mood seasonality, with age entered as a covariate. A main effect of gender was observed, F (1, 1197) = 17.86, p < .01; partial Eta-squared = .02, with mood seasonality being higher for females (M = 8) than for males (M = 7). Contradicting previous findings, no significant main effect for month of birth was observed, F (1, 1197) = 0.65, p > .05. CONCLUSION: The unexpected finding is tentatively explained by differences in geographic location and weather fluctuations between the sampling location in Brazil and other countries where season of birth has been found to influence mood seasonality. Additional studies with larger samples from the Southern Hemisphere are necessary to shed additional light on the possible significant influence of season of birth on mood.

Benzodiazepine use and associated factors in elderly in the city of Dourados, MS, Brazil

ABSTRACT Objective The use of benzodiazepines (BZD) and associated factors in the elderly of Dourados, MS, Brazil was investigated. Methods This is a cross-sectional population-based study using a multistage sampling design. Participants were 1,022 individuals aged ≥ 60 years. Measurements socioeconomic status, schooling, demographic aspects, marital status, physical activity, hospitalizations, self-rated health, use of alcohol beverages and smoking were assessed by standard questionnaire. The drugs used were obtained by checking the prescription or package and classified according to the Anatomical Therapeutic Chemical Index. Chi-square test, Chi-square for linear tendency, Fisher's exact test and Poisson regression were used to assess association between variables. Results The prevalence of use of BZD was 6.5% (CI95%: 5.1-8.2%). The oldest group (PR: 1.60 for 70-79 years and PR: 1.79 for ≥ 80 years), non-use of alcohol (PR: 4.14) and use of antidepressants (PR: 8.73) were the statistically associated characteristics. Conclusions The prevalence of use of BZD in the study population was low, similar to findings of more recent Brazilian studies and lower than those obtained in international studies. The prevalence of use of BZD increased with aging and use of antidepressants.

Prevalence of depressive and anxiety symptoms in medical students in the city of Santos

ABSTRACT Objective Ascertain the prevalence of depressive and anxiety symptoms in medical students, considering data in the literature that indicate higher vulnerability to emotional disorders in this population. Methods A descriptive cross-sectional study with a sample of 657 (98%) students. The instruments used were: questionnaire of socioeconomic-demographic characteristics, Beck Depression Inventory and Beck Anxiety Inventory. Results Predominance of the female gender (61%), aged between 17 and 30 years (98%), Catholic religion (64.2%) from the city of São Paulo (40.7%) and other cities in the state (35.7%); 30% presented depressive symptoms and 21% anxiety symptoms. Female students had higher scores both for depression (34.8%) and for anxiety (26.8%). As regards the course year, the highest rates were found in the 5th year (40.7%) for depression and in the 2nd year for anxiety (28.8%). Conclusion The data obtained in this study (30%) agreed with the literature regarding the prevalence of depressive symptoms in medical students, but this index was higher compared to the population in general (15.1% to 16.8%), and related to people in São Paulo city (18.5%). Concerning anxiety the rates found were slightly lower than those in specific literature but higher than those in literature for the population in general (8% to 18%) and in city São Paulo (16.8%). These indices indicate that the school of medicine may play a role as a predisposing and/or triggering factor in some students. The results suggest that more attention should be directed to 5th year students, who are beginning the internship period.

Estimativa dos parâmetros de compactação de solos usando técnicas de data mining

Dissertação de mestrado integrado em Engenharia Civil

Plataforma de apoio à decisão nos cuidados de ginecologia e obstetrícia

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

Risk factors for atherosclerosis in an elderly out patient population in the City of São Paulo

OBJECTIVE: To analyze in out clinic elderly patients of both sexes for the prevalence of risk factors for atherosclerosis and study their association with the complications of atherosclerosis. METHODS: Five hundred and sixteen outpatients, 152 men and 364 women, 60 years or older, were studied. The prevalences of hypertension, dyslipidemia, diabetes mellitus, cigarette smoking and obesity were determined in both sexes and compared using the chi-square test. The association between these factors and the presence of atherosclerotic complications was analyzed by logistic regression. RESULTS: The comparative analysis of the factors in both sexes showed that hypertension, total cholesterol > or = 240mg/dL, LDL-cholesterol > or = 160mg/dL, and body mass index >27.5 were more frequent among women, but HDL-cholesterol <35mg/dL and cigarette smoking were more frequent among men, and no difference occurred between sexes in relation to the frequency of triglycerides > or = 250mg/dL and diabetes mellitus. After adjustment of the variables in the regression model, we observed that in the total of elderly patients, risk factors for complications of atherosclerosis were: triglycerides > or = 250mg/dL, hypertension, and male sex. Among men, the risk factors were: LDL-cholesterol > or = 160mg/dL, diabetes mellitus, HDL-cholesterol <35mg/dL and hypertension. Among women, the risk factors were: tryglicerides > or = 250mg/dL and hypertension. CONCLUSION: The results showed that, in the elderly, the risk factors for atherosclerosis persist, but with different behaviors between men and women. The study suggests that the relative importance of the risk factors can change with the aging process.

Characterization of late antique and early medieval pottery production of the city of Braga and its territory

The fundamental goal we set ourselves when developing this study is to try to characterize, both technically and formally, ceramics made in the city of Braga and its territory from the initial moments of the Late Antiquity to the Middle Ages. Thus, we will focus on analyzing some own productions that appear attached to the phases of late antique occupation —ceramics of red engobes and late gray—, as well as in the early medieval containers identified in different archaeological interventions practiced in the Braga environment. Concretely, we will analyze the material from various excavations conducted recently at the Theatre in the solar number 20/28 and 36/56 from the Afonso Henriques Street and the former District Hostel as well as the church of São Martinho de Dume.

Increase in mortality due to myocardial infarction in the Brazilian city of São Paulo during winter

OBJECTIVE: To study the seasonal variation in mortality due to myocardial infarction in the city of São Paulo. METHODS: We analyzed the database of PROAIM (Programa de Aprimoramento de Informações de Mortalidade) containing the registrations of the certificates of deaths due to myocardial infarction (International Classification of Diseases, 10th edition, classification I21) of the residents of the municipality of São Paulo during 12 months (from December 1996 to November 1997). The number of deaths was corrected for a standard period of 90 days and then it was divided by the corresponding population to obtain the event rate per 10 thousand inhabitants. The magnitude of the seasonal variation, which was defined by the difference of the relative risks between the seasons with higher and lower mortality, was estimated. RESULTS: A total of 5,615 deaths due to myocardial infarction were included in the study. Sixty-one per cent occurred in the male sex, and the mean age was 68 years. The mortality rate during winter was always higher and that during summer was lower than that during the other seasons (P<0.01), independent from age and sex. Seasonal variations in deaths due to myocardial infarction was 30% in the general group, being 23% in individuals who died younger than 75 years, and 44% in the older ones. CONCLUSION: A marked seasonal variation in mortality due to myocardial infarction was observed in the city of São Paulo, with a significant increase in its magnitude and age distribution during the winter, similar to those reported in regions of North America and Europe with temperate climates.

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.

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.

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%.

Electrocardiographic Alterations in Patients Hospitalized with Leptospirosis in the Brazilian City of Salvador

OBJECTIVE: To report the frequency and types of electrocardiographic alterations in patients with leptospirosis in the first 24 hours of hospitalization. METHODS: We analyzed the electrocardiograms of 157 patients admitted to the Hospital Couto Maia in the city of Salvador, in the State of Bahia, Brazil, from March 1998 to June 1999. The electrocardiograms were performed in the first 24 hours after hospital admission, independent of the clinical manifestations of the patients. RESULTS: The mean ± SD for patients' age was 35.5± 13.7 (median = 32) years, and jaundice was present in 95.5% of them. Alterations in the electrocardiogram were detected in 68.2% (107/157) of the patients (95% confidence interval = 60.6% - 75.1%). Atrial fibrillation was the most frequent arrhythmia, occurring in 10.8% (17/157) of the patients. Other frequent findings were alterations in ventricular repolarization detected in 38.9% (61/157) of patients and first-degree atrioventricular block in 10.2% (16/157). The patients with atrial fibrillation were older and had higher levels of creatinine and aminotransferases. CONCLUSION: In this sample, approximately 2/3 of the patients had electrocardiographic alterations after hospital admission. Of the major arrhythmias, atrial fibrillation was the most frequent, and the patients with this arrhythmia had evidence of more severe disease. The relation between the presence and type of electrocardiographic alteration and the prognosis of leptospirosis is yet to be assessed.

Noise mapping for an urban area: study case: old city of Damascus, Syria

Dissertação de mestrado em Engenharia Urbana