Escore CRIB, peso ao nascer e idade gestacional na avaliação do risco de mortalidade neonatal

OBJETIVO: Avaliar a mortalidade dos recém-nascidos de muito baixo peso em uma UTI neonatal conforme as variações do escore CRIB (Clinical Risk Index for Babies), do peso de nascimento e da idade gestacional em determinado período. MÉTODOS: O escore CRIB foi aplicado seqüencial e prospectivamente em todos os recém-nascidos com peso de nascimento <1.500 g e/ou idade gestacional <31 semanas, em maternidade de um hospital universitário de Londrina, no período de janeiro de 1997 a dezembro de 2000. Os critérios de exclusão foram: óbitos antes de 12 horas de vida, os recém- nascidos com malformações congênitas incompatíveis com a sobrevida e os recém- nascidos encaminhados de outros serviços. RESULTADOS: Foram incluídos no estudo 284 recém-nascidos. O peso médio de nascimento foi de 1.148±248 g (mediana =1.180 g); a idade gestacional média foi de 30,2±2,4 semanas (mediana =30,0) e o CRIB médio foi de 3,8±4,4 (mediana =2,0). A mortalidade neonatal foi de 23,2% diferindo conforme peso <750 g (72,7%), IG<29 semanas (57,1%) e CRIB>10 (79,4%). A curva ROC (Receiver Operator Characteristic) para os valores de CRIB, peso de nascimento e idade gestacional gerou áreas sob a curva de 0,88, 0,76 e 0,81, respectivamente. Na análise bivariada, o CRIB, peso e idade gestacional mostraram-se preditores de mortalidade, sendo o escore CRIB>4 o de melhor resultado com sensibilidade de 75,8%, especificidade de 86,7%, valor preditivo positivo de 63,3% e valor preditivo negativo de 92,2%. CONCLUSÕES: Os recém-nascidos com peso de nascimento <750 g, idade gestacional <29 semanas e escore CRIB>10 tiveram maiores taxas de mortalidade, sendo o escore CRIB>4 o que representou melhor poder preditivo quando comparado com peso ao nascer e idade gestacional.

Usefulness of corneal esthesiometry for screening diabetic retinopathy

OBJECTIVE: To assess the usefulness of corneal esthesiometry for screening diabetic retinopathy. METHODS: A cross-sectional study was carried out comprising 575 patients attending a diabetic retinopathy-screening program in the city of São Paulo. Corneal esthesiometry was assessed with the Cochet-Bonnet esthesiometer. The presence of diabetic retinopathy was detected with indirect fundoscopy. The validity of corneal esthesiometry in identifying diabetic retinopathy was evaluated by the Receiver Operating Characteristic (ROC) curve. RESULTS: Sensitivity and specificity analyses of the corneal esthesiometry for detecting the stages of diabetic retinopathy using different cut-offs showed values less than 80%. The best indices (72.2% sensitivity and 57.4% specificity) were obtained for the identification of patients with proliferative diabetic retinopathy. CONCLUSIONS: In the study series, corneal esthesiometry was not a good indicator of diabetic retinopathy.

Estimativa de validade de um novo método de isolamento de vírus rábico

OBJETIVOS: Nenhum estudo de base populacional foi realizado para mostrar o uso potencial de diagnóstico virológico do vírus rábico. O estudo realizado teve por objetivo estimar parâmetros de acurácia para o isolamento de vírus rábico em célula McCoy, como um método alternativo, e comparar com o uso da célula N2A, considerada método de referência. MÉTODOS: Foi realizado um inquérito em 120 morcegos coletados aleatoriamente, na Mata Atlântica, no Estado de São Paulo. Utilizou-se a reação de imunofluorescência para a detecção do vírus rábico isolado no cérebro desses morcegos, avaliado nos dois sistemas de cultivos celulares. Dois bancos de dados foram formados com os resultados. A análise foi feita com o programa Computer Methods for Diagnosis Tests (CMDT), utilizando a técnica de two-graph-receiver operating characteristic (TG-ROC) para obter os parâmetros de sensibilidade e especificidade, além de outros indicadores, tais como eficácia, valor preditivo positivo, valor preditivo negativo e razão de verossimilhança. RESULTADOS: A célula N2A apresentou 90% de sensibilidade e especificidade, enquanto que a célula McCoy obteve 95% para os mesmos parâmetros. Os valores foram baseados em pontos de cortes otimizados para cada uma das células. CONCLUSÕES: Observou-se que a célula McCoy permite obter estimativas de acurácia superiores aos resultados observados com a célula de N2A, representando um método alternativo eficaz no isolamento do vírus rábico.

Neonatal mortality in intensive care units of Central Brazil

OBJECTIVE: To identify potential prognostic factors for neonatal mortality among newborns referred to intensive care units. METHODS: A live-birth cohort study was carried out in Goiânia, Central Brazil, from November 1999 to October 2000. Linked birth and infant death certificates were used to ascertain the cohort of live born infants. An additional active surveillance system of neonatal-based mortality was implemented. Exposure variables were collected from birth and death certificates. The outcome was survivors (n=713) and deaths (n=162) in all intensive care units in the study period. Cox's proportional hazards model was applied and a Receiver Operating Characteristic curve was used to compare the performance of statistically significant variables in the multivariable model. Adjusted mortality rates by birth weight and 5-min Apgar score were calculated for each intensive care unit. RESULTS: Low birth weight and 5-min Apgar score remained independently associated to death. Birth weight equal to 2,500g had 0.71 accuracy (95% CI: 0.65-0.77) for predicting neonatal death (sensitivity =72.2%). A wide variation in the mortality rates was found among intensive care units (9.5-48.1%) and two of them remained with significant high mortality rates even after adjusting for birth weight and 5-min Apgar score. CONCLUSIONS: This study corroborates birth weight as a sensitive screening variable in surveillance programs for neonatal death and also to target intensive care units with high mortality rates for implementing preventive actions and interventions during the delivery period.

Arrow Plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on samples subgroups

Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

Validação da escala de depressão geriátrica em um ambulatório geral

OBJETIVO: A Escala de Depressão Geriátrica, utilizada para o rastreamento de sintomas depressivos em idosos, ainda não teve suas características de medida avaliadas em ambulatórios gerais no Brasil. O objetivo foi estudar a validade da Escala, com 15 itens (EDG-15), na identificação de episódio de Depressão Maior ou Distimia em idosos atendidos em ambulatório geral. MÉTODOS: A Escala foi aplicada em 302 indivíduos com 65 anos ou mais, que em seguida foram examinados, de maneira independente, por um geriatra que não tinha conhecimento dos resultados da Escala. Os diagnósticos de Depressão Maior ou Distimia foram feitos utilizando-se os critérios do Diagnostic and Statistical Manual of Mental Disorders-IV. A sensibilidade e a especificidade nos vários pontos de corte foram expressas pela curva Receiver Operating Characteristic. RESULTADOS: O ponto de corte de melhor equilíbrio foi 5/6, obteve sensibilidade de 81% e especificidade de 71%; e o valor da área sob a curva Receiver Operating Characteristic foi de 0,85 (IC 95%: 0,79-0,91). CONCLUSÕES: A Escala de Depressão Geriátrica pode ser utilizada para o rastreamento de sintomas depressivos na população geriátrica ambulatorial brasileira. O ponto de corte 5/6, sugerido inicialmente por outros autores, mostrou-se adequado.

Modelling the distribution of cetaceans using opportunistic presence-only data in S. Miguel Island (Azores)

25th Annual Conference of the European Cetacean Society, Cadiz, Spain 21-23 March 2011.

Avaliação da tonopaquimetria como exame de rastreio de glaucoma primário de ângulo aberto

Mestrado em Gestão e Avaliação de Tecnologias em Saúde

A 5GHz/1.8V CMOS Active Balun Integrated with LNA

The development of high performance monolithic RF front-ends requires innovative RF circuit design to make the best of a good technology. A fully differential approach is usually preferred, due to its well-known properties. Although the differential approach must be preserved inside the chip, there are cases where the input signal is single-ended such as RF image filters and IF filters in a RF receiver. In these situations, a stage able to convert single-ended into differential signals (balun) is needed. The most cited topology, which is capable of providing high gain, consists on a differential stage with one of the two inputs grounded. Unfortunately, this solution has some drawbacks when implemented monolithically. This work presents the design and simulated results of an innovative high-performance monolithic single to differential converter, which overcomes the limitations of the circuits.The integration of the monolithic active balun circuit with an LNA on a 0.18μm CMOS process is also reported. The circuits presented here are aimed at 802.11a. Section 2 describes the balun circuit and section 3 presents its performance when it is connected to a conventional single-ended LNA. Section 4 shows the simulated performance results focused at phase/amplitude balance and noise figure. Finally, the last section draws conclusions and future work.

A 5GHz1.8V Low Power CMOS Low-Noise Amplifier

Wireless local-area networks (WLANs) have been deployed as office and home communications infrastructures worldwide. The diversification of the standards, such as IEEE 802.11 series demands the design of RF front-ends. Low power consumption is one of the most important design concerns in the application of those technologies. To maintain competitive hardware costs, CMOS has been used since it is the best solution for low cost and high integration processing, allowing analog circuits to be mixed with digital ones. In the receiver chain, the low noise amplifier (LNA) is one of the most critical blocks in a transceiver design. The sensitivity is mainly determined by the LNA noise figure and gain. It interfaces with the pre-select filter and the mixer. Furthermore, since it is the first gain stage, care must be taken to provide accurate input match, low-noise figure, good linearity and a sufficient gain over a wide band of operation. Several CMOS LNAs have been reported during the last decade, showing that the most research has been done at 802.11/b and GSM standards (900-2400MHz spectrum) and more recently at 802.11/a (5GHz band). One of the more significant disadvantages of 802.11/b is that the frequency band is crowded and subject to interference from other technologies, as is 2.4GHz cordless phones and Bluetooth. As the demand for radio-frequency integrated circuits, operating at higher frequency bands, increases, the IEEE 802.11/a standard becomes a very attractive option to wireless communication system developers. This paper presents the design and implementation of a low power, low noise amplifier aimed at IEEE 802.11a for WLAN applications. It was designed to be integrated with an active balun and mixer, representing the first step toward a fully integrated monolithic WLAN receiver. All the required circuits are integrated at the same die and are powered by 1.8V supply source. Preliminary experimental results (S-parameters) are shown and promise excellent results. The LNA circuit design details are illustrated in Section 2. Spectre simulation results focused at gain, noise figure (NF) and input/output matching are presented in Section 3. Finally, conclusions and comparison with other recently reported LNAs are made in Section 4, followed by future work.

Machine Learning Algorithms at Myocardial Perfusion Imaging - a Preliminary Study

Introduction: A major focus of data mining process - especially machine learning researches - is to automatically learn to recognize complex patterns and help to take the adequate decisions strictly based on the acquired data. Since imaging techniques like MPI – Myocardial Perfusion Imaging on Nuclear Cardiology, can implicate a huge part of the daily workflow and generate gigabytes of data, there could be advantages on Computerized Analysis of data over Human Analysis: shorter time, homogeneity and consistency, automatic recording of analysis results, relatively inexpensive, etc.Objectives: The aim of this study relates with the evaluation of the efficacy of this methodology on the evaluation of MPI Stress studies and the process of decision taking concerning the continuation – or not – of the evaluation of each patient. It has been pursued has an objective to automatically classify a patient test in one of three groups: “Positive”, “Negative” and “Indeterminate”. “Positive” would directly follow to the Rest test part of the exam, the “Negative” would be directly exempted from continuation and only the “Indeterminate” group would deserve the clinician analysis, so allowing economy of clinician’s effort, increasing workflow fluidity at the technologist’s level and probably sparing time to patients. Methods: WEKA v3.6.2 open source software was used to make a comparative analysis of three WEKA algorithms (“OneR”, “J48” and “Naïve Bayes”) - on a retrospective study using the comparison with correspondent clinical results as reference, signed by nuclear cardiologist experts - on “SPECT Heart Dataset”, available on University of California – Irvine, at the Machine Learning Repository. For evaluation purposes, criteria as “Precision”, “Incorrectly Classified Instances” and “Receiver Operating Characteristics (ROC) Areas” were considered. Results: The interpretation of the data suggests that the Naïve Bayes algorithm has the best performance among the three previously selected algorithms. Conclusions: It is believed - and apparently supported by the findings - that machine learning algorithms could significantly assist, at an intermediary level, on the analysis of scintigraphic data obtained on MPI, namely after Stress acquisition, so eventually increasing efficiency of the entire system and potentially easing both roles of Technologists and Nuclear Cardiologists. In the actual continuation of this study, it is planned to use more patient information and significantly increase the population under study, in order to allow improving system accuracy.

Modelação do transporte e dispersão atmosférica de poluentes produzidos por uma refinaria: estudo de caso

Mestrado em Engenharia Química.Ramo Tecnologias de Protecção Ambiental

Sistema de localização de um veículo autónomo terrestre

Mestrado em Engenharia Electrotécnica e de Computadores.

Comorbidity adjustment index for the international classification of diseases, 10

OBJECTIVE: To develop a Charlson-like comorbidity index based on clinical conditions and weights of the original Charlson comorbidity index. METHODS: Clinical conditions and weights were adapted from the International Classification of Diseases, 10th revision and applied to a single hospital admission diagnosis. The study included 3,733 patients over 18 years of age who were admitted to a public general hospital in the city of Rio de Janeiro, southeast Brazil, between Jan 2001 and Jan 2003. The index distribution was analyzed by gender, type of admission, blood transfusion, intensive care unit admission, age and length of hospital stay. Two logistic regression models were developed to predict in-hospital mortality including: a) the aforementioned variables and the risk-adjustment index (full model); and b) the risk-adjustment index and patient's age (reduced model). RESULTS: Of all patients analyzed, 22.3% had risk scores >1, and their mortality rate was 4.5% (66.0% of them had scores >1). Except for gender and type of admission, all variables were retained in the logistic regression. The models including the developed risk index had an area under the receiver operating characteristic curve of 0.86 (full model), and 0.76 (reduced model). Each unit increase in the risk score was associated with nearly 50% increase in the odds of in-hospital death. CONCLUSIONS: The risk index developed was able to effectively discriminate the odds of in-hospital death which can be useful when limited information is available from hospital databases.

A biosignal embedded system for physiological computing

Thesis submitted in the fulfilment of the requirements for the Degree of Master in Electronic and Telecomunications Engineering