Surgical treatment of endocrine exophthalmos by removal of orbital fat: clinical experience

PURPOSE: To report a series of 73 patients with endocrine exophthalmos treated by removal of orbital fat using the transpalpebral approach during the period 1989 to 1999. METHODS: The operation was performed according to the technique described by Olivari. Aesthetic analysis was done preoperatively and postoperatively (more than 6 months after surgery). The number of complications was also observed. RESULTS: The average volume of resected fat was approximately 7.6 mL per orbit. No major complication was observed. In 9 patients with epiphora, all improved. One patient developed postoperative diplopia and 5 complained of temporary diplopia. Appearance improved in 62 patients (85%). CONCLUSION: Surgical removal of orbital fat associated with endocrine exophthalmos provides consistent improvement in appearance with a low rate of complications. Additional procedures may be indicated to improve the cosmetic outcome.

Gastric myoelectrical activity in neonates of different gestational ages by means of electrogastrography

PURPOSE: to describe the patterns of the gastric myoelectrical activity, pre-and postprandially, in clinically stable neonates of different gestational ages, during their first two weeks of life by means of Electrogastrography. PATIENTS AND METHODS: Electrogastrography was recorded in forty-five clinically stable neonates of different gestational ages (group I: 15 neonates of > 37 weeks, group II: 15 premature neonates of 32-37 weeks; Group III: 15 premature neonates of 28-31 weeks) receiving intermittent enteral feedings during their first two weeks of life. Electrogastrography recordings were performed for 1 hour pre-and postprandially. The Electrogastrography signal was recorded using the portable MicroDigitrapper Electrogastrography recording device and after motion artifacts were deleted, the remaining Electrogastrography data were submitted to quantitative analysis based on the "Running Spectrum Analysis". RESULTS: The percentages of normogastria, pre-and postprandially were greater than the percentages of gastric dysrythmias in all three studied groups. Furthermore, all neonates had the mean values of the Electrogastrography dominant frequency predominantly within the normogastria range, in both periods analyzed. There were no significant differences in the relative change of the Electrogastrography dominant power among the groups. CONCLUSION: This study demonstrates that the Electrogastrography patterns are similar between premature and full term neonates during the pre-and postprandial periods. The results of this study also indicate that the gastric myoelectrical activity in premature and full term neonates is immature, as compared to that described for older neonates, children and adults.

DISTINGUISHING Campa guianensis Aubl. FROM Campa procera D.C. (MELIACEAE) BY MORPHOLOGY OF YOUNG SEEDLINGS

Seedling morphology was studied in Campa guianensisAubl. and Carapa proceraD. C. from germination to 90 days age. In both species germination is hypogeal and cryptocotylar. Both have rare albino seedlings. Though both species have compound leaves when adult, C, proceraputs out an average total of six simple leaves at germination, while leaves of C. guianensisare compound at all stages. This is the best diagnostic character for separation of the two species at the young seedling stage. Not diagnostic, but none the less useful, is the fact, that polyembryonic seeds are often found in C. procera,but not observed in C guianensis.

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.

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.

Quantitative determination by HPLC of iridoids in the bark and latex of himatanthus sucuuba

The main iridoids from the bark and latex of Himatanthus sucuuba were isolated and characterised by spectroscopic methods. HPLC was used for the quantitative analyses of these iridoids and the chromatograms of bark and latex showed a similar iridoid composition. Both parts of the plant are used in folk medicine for the treatment of various ailments.

Predicting SO2 pollution incidents by means of additive models with optimum variable selection

The aim of this paper is to predict time series of SO2 concentrations emitted by coal-fired power stations in order to estimate in advance emission episodes and analyze the influence of some meteorological variables in the prediction. An emission episode is said to occur when the series of bi-hourly means of SO2 is greater than a specific level. For coal-fired power stations it is essential to predict emission epi- sodes sufficiently in advance so appropriate preventive measures can be taken. We proposed a meth- odology to predict SO2 emission episodes based on using an additive model and an algorithm for variable selection. The methodology was applied to the estimation of SO2 emissions registered in sampling lo- cations near a coal-fired power station located in Northern Spain. The results obtained indicate a good performance of the model considering only two terms of the time series and that the inclusion of the meteorological variables in the model is not significant.

By-products of beer fermentation

Among the most important factors influencing beer quality is the presence of well-adjusted amounts of higher alcohols and esters; as well as the successful reduction of undesirable by-products such as diacetyl. While higher alcohols and esters contribute rather positively to the beer aroma, diacetyl is mostly unwelcome for beer types with lighter taste. Thus, the complex metabolic pathways in yeast responsible for the synthesis of both pleasant and unpleasant by-products of fermentation were given special attention in this last chapter.

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.

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.

Step towards to improve the voluntary interruption of pregnancy by means of business intelligence

With the implementation of Information and Communication Technologies in the health sector, it became possible the existence of an electronic record of information for patients, enabling the storage and the availability of their information in databases. However, without the implementation of a Business Intelligence (BI) system, this information has no value. Thus, the major motivation of this paper is to create a decision support system that allows the transformation of information into knowledge, giving usability to the stored data. The particular case addressed in this chapter is the Centro Materno Infantil do Norte, in particular the Voluntary Interruption of Pregnancy unit. With the creation of a BI system for this module, it is possible to design an interoperable, pervasive and real-time platform to support the decision-making process of health professionals, based on cases that occurred. Furthermore, this platform enables the automation of the process for obtaining key performance indicators that are presented annually by this health institution. In this chapter, the BI system implemented in the VIP unity in CMIN, some of the KPIs evaluated as well as the benefits of this implementation are presented.

Repair of an Atherosclerotic Coronary Artery Aneurysm by Implantation of a Coronary Covered Stent

An atherosclerotic aneurysm of the right coronary artery complicated by a recent myocardial infarction was successfully treated with coronary artery stenting, using a device consisting of 2 stents with a layer of expandable polytetrafluorethylene (PTFE) placed between them. A follow-up angiograph 5 months after the procedure showed sustained initial results.

Flora boreali-americana, or, the botany of the northern parts of British America : compiled principally from the plants collected by Dr. Richardson & Mr. Drummond on the late northern expeditions, under command of Captain Sir John Franklin, R.N. To which are added (by permission of the Horticultural society of London,) those of Mr. Douglas, from north-west America, and of other naturalists /

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Flora boreali-americana, or, the botany of the northern parts of British America : compiled principally from the plants collected by Dr. Richardson & Mr. Drummond on the late northern expeditions, under command of Captain Sir John Franklin, R.N. To which are added (by permission of the Horticultural society of London,) those of Mr. Douglas, from north-west America, and of other naturalists /

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