Metabolic syndrome and dietary components are associated with coronary artery disease risk score in free-living adults: a cross-sectional study

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The evaluation of an instrument for pediatric oncology patient classification

The objectives of this study were to assess the interrater reproducibility of the instrument to classify pediatric patients with cancer; verify the adequacy of the patient classification instrument for pediatric patients with cancer; and make a proposal for changing the instrument, thus allowing for the necessary adjustments for pediatric oncology patients. A total of 34 pediatric inpatients of a Cancer Hospital were evaluated by the teams of physicians, nurses and nursing technicians. The Kappa coefficient was used to rate the agreement between the scores, which revealed a moderate to high value in the objective classifications, and a low value in the subjective. In conclusion, the instrument is reliable and reproducible, however, it is suggested that to classify pediatric oncology patients, some items should be complemented in order to reach an outcome that is more compatible with the reality of this specific population.

Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients

Background: Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods: Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results: We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. Conclusions: The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.

Gender classification in large databases

[EN]In this paper, we address the challenge of gender classi - cation using large databases of images with two goals. The rst objective is to evaluate whether the error rate decreases compared to smaller databases. The second goal is to determine if the classi er that provides the best classi cation rate for one database, improves the classi cation results for other databases, that is, the cross-database performance.

Development of a new galaxy classification technique and its application to the zCOSMOS survey

The purpose of this Thesis is to develop a robust and powerful method to classify galaxies from large surveys, in order to establish and confirm the connections between the principal observational parameters of the galaxies (spectral features, colours, morphological indices), and help unveil the evolution of these parameters from $z \sim 1$ to the local Universe. Within the framework of zCOSMOS-bright survey, and making use of its large database of objects ($\sim 10\,000$ galaxies in the redshift range $0 < z \lesssim 1.2$) and its great reliability in redshift and spectral properties determinations, first we adopt and extend the \emph{classification cube method}, as developed by Mignoli et al. (2009), to exploit the bimodal properties of galaxies (spectral, photometric and morphologic) separately, and then combining together these three subclassifications. We use this classification method as a test for a newly devised statistical classification, based on Principal Component Analysis and Unsupervised Fuzzy Partition clustering method (PCA+UFP), which is able to define the galaxy population exploiting their natural global bimodality, considering simultaneously up to 8 different properties. The PCA+UFP analysis is a very powerful and robust tool to probe the nature and the evolution of galaxies in a survey. It allows to define with less uncertainties the classification of galaxies, adding the flexibility to be adapted to different parameters: being a fuzzy classification it avoids the problems due to a hard classification, such as the classification cube presented in the first part of the article. The PCA+UFP method can be easily applied to different datasets: it does not rely on the nature of the data and for this reason it can be successfully employed with others observables (magnitudes, colours) or derived properties (masses, luminosities, SFRs, etc.). The agreement between the two classification cluster definitions is very high. ``Early'' and ``late'' type galaxies are well defined by the spectral, photometric and morphological properties, both considering them in a separate way and then combining the classifications (classification cube) and treating them as a whole (PCA+UFP cluster analysis). Differences arise in the definition of outliers: the classification cube is much more sensitive to single measurement errors or misclassifications in one property than the PCA+UFP cluster analysis, in which errors are ``averaged out'' during the process. This method allowed us to behold the \emph{downsizing} effect taking place in the PC spaces: the migration between the blue cloud towards the red clump happens at higher redshifts for galaxies of larger mass. The determination of $M_{\mathrm{cross}}$ the transition mass is in significant agreement with others values in literature.

Learning Methods and Algorithms for Semantic Text Classification across Multiple Domains

Information is nowadays a key resource: machine learning and data mining techniques have been developed to extract high-level information from great amounts of data. As most data comes in form of unstructured text in natural languages, research on text mining is currently very active and dealing with practical problems. Among these, text categorization deals with the automatic organization of large quantities of documents in priorly defined taxonomies of topic categories, possibly arranged in large hierarchies. In commonly proposed machine learning approaches, classifiers are automatically trained from pre-labeled documents: they can perform very accurate classification, but often require a consistent training set and notable computational effort. Methods for cross-domain text categorization have been proposed, allowing to leverage a set of labeled documents of one domain to classify those of another one. Most methods use advanced statistical techniques, usually involving tuning of parameters. A first contribution presented here is a method based on nearest centroid classification, where profiles of categories are generated from the known domain and then iteratively adapted to the unknown one. Despite being conceptually simple and having easily tuned parameters, this method achieves state-of-the-art accuracy in most benchmark datasets with fast running times. A second, deeper contribution involves the design of a domain-independent model to distinguish the degree and type of relatedness between arbitrary documents and topics, inferred from the different types of semantic relationships between respective representative words, identified by specific search algorithms. The application of this model is tested on both flat and hierarchical text categorization, where it potentially allows the efficient addition of new categories during classification. Results show that classification accuracy still requires improvements, but models generated from one domain are shown to be effectively able to be reused in a different one.

A cross cultural study of vaginal practices and sexuality: Implications for sexual health

Between 2005 and 2006, we investigated vaginal practices in Yogyakarta, Indonesia; Tete, Mozambique; KwaZulu-Natal, South Africa; and Bangkok and Chonburi, Thailand. We sought to understand women's practices, their motivations for use and the role vaginal practices play in women's health, sexuality and sense of wellbeing. The study was carried out among adult women and men who were identified as using, having knowledge or being involved in trade in products. Further contacts were made using snowball sampling. Across the sites, individual interviews were conducted with 229 people and 265 others participated in focus group discussions. We found that women in all four countries have a variety of reasons for carrying out vaginal practices whose aim is to not simply 'dry' the vagina but rather decrease moisture that may have other associated meanings, and that they are exclusively "intravaginal" in operation. Practices, products and frequency vary. Motivations generally relate to personal hygiene, genital health or sexuality. Hygiene practices involve external washing and intravaginal cleansing or douching and ingestion of substances. Health practices include intravaginal cleansing, traditional cutting, insertion of herbal preparations, and application of substances to soothe irritated vaginal tissue. Practices related to sexuality can involve any of these practices with specific products that warm, dry, and/or tighten the vagina to increase pleasure for the man and sometimes for the woman. Hygiene and health are expressions of femininity connected to sexuality even if not always explicitly expressed as such. We found their effects may have unexpected and even undesired consequences. This study demonstrates that women in the four countries actively use a variety of practices to achieve a desired vaginal state. The results provide the basis for a classification framework that can be used for future study of this complex topic.

Informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry (GCxGC-HRMS)

This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods. The approach developed here analyzes GCxGC-HRMS data from multiple samples to extract a feature template that comprehensively captures the pattern of peaks detected in the retention-times plane. Then, for each sample chromatogram, the template is geometrically transformed to align with the detected peak pattern and generate a set of feature measurements for cross-sample analyses such as sample classification and biomarker discovery. The approach avoids the intractable problem of comprehensive peak matching by using a few reliable peaks for alignment and peak-based retention-plane windows to define comprehensive features that can be reliably matched for cross-sample analysis. The informatics are demonstrated with a set of 18 samples from breast-cancer tumors, each from different individuals, six each for Grades 1-3. The features allow classification that matches grading by a cancer pathologist with 78% success in leave-one-out cross-validation experiments. The HRMS signatures of the features of interest can be examined for determining elemental compositions and identifying compounds.

Identification of problems in functioning of people with sleep disorders in a clinical setting using the International Classification of Functioning Disability and Health (ICF) Checklist

We conducted an explorative, cross-sectional, multi-centre study in order to identify the most common problems of people with any kind of (primary) sleep disorder in a clinical setting using the International Classification of Functioning, Disability and Health (ICF) as a frame of reference. Data were collected from patients using a structured face-to-face interview of 45-60 min duration. A case record form for health professionals containing the extended ICF Checklist, sociodemographic variables and disease-specific variables was used. The study centres collected data of 99 individuals with sleep disorders. The identified categories include 48 (32%) for body functions, 13 (9%) body structures, 55 (37%) activities and participation and 32 (22%) for environmental factors. 'Sleep functions' (100%) and 'energy and drive functions', respectively, (85%) were the most severely impaired second-level categories of body functions followed by 'attention functions' (78%) and 'temperament and personality functions' (77%). With regard to the component activities and participation, patients felt most restricted in the categories of 'watching' (e.g. TV) (82%), 'recreation and leisure' (75%) and 'carrying out daily routine' (74%). Within the component environmental factors the categories 'support of immediate family', 'health services, systems and policies' and 'products or substances for personal consumption [medication]' were the most important facilitators; 'time-related changes', 'light' and 'climate' were the most important barriers. The study identified a large variety of functional problems reflecting the complexity of sleep disorders. The ICF has the potential to provide a comprehensive framework for the description of functional health in individuals with sleep disorders in a clinical setting.

Chlamydia infection, pelvic inflammatory disease, ectopic pregnancy and infertility: cross-national study

Objectives To describe, using routine data in selected countries, chlamydia control activities and rates of chlamydia infection, pelvic inflammatory disease (PID), ectopic pregnancy and infertility and to compare trends in chlamydia positivity with rates of PID and ectopic pregnancy. Methods Cross-national comparison including national data from Australia, Denmark, the Netherlands, New Zealand, Sweden and Switzerland. Routine data sources about chlamydia diagnosis and testing and International Classification of Disease-10 coded diagnoses of PID, ectopic pregnancy and infertility in women aged 15–39 years from 1999 to 2008 were described. Trends over time and relevant associations were examined using Poisson regression. Results Opportunistic chlamydia testing was recommended in all countries except Switzerland, but target groups differed. Rates of chlamydia testing were highest in New Zealand. Chlamydia positivity was similar in all countries with available data (Denmark, New Zealand and Sweden) and increased over time. Increasing chlamydia positivity rates were associated with decreasing PID rates in Denmark and Sweden and with decreasing ectopic pregnancy rates in Denmark, New Zealand and Sweden. Ectopic pregnancy rates appeared to increase over time in 15–19-year-olds in several countries. Trends in infertility diagnoses were very variable. Conclusions The intensity of recommendations about chlamydia control varied between countries but was not consistently related to levels of chlamydia diagnosis or testing. Relationships between levels of chlamydia infection and complication rates between or within countries over time were not straightforward. Development and validation of indicators of chlamydia-related morbidity that can be compared across countries and over time should be pursued.

Chlamydia control activities in Europe: cross-sectional survey

Background: Chlamydia is the most commonly reported bacterial sexually transmitted infection in Europe. The objective of the Screening for Chlamydia in Europe (SCREen) project was to describe current and planned chlamydia control activities in Europe. Methods: The authors sent a questionnaire asking about different aspects of chlamydia epidemiology and control to public health and clinical experts in each country in 2007. The principles of sexually transmitted infection control were used to develop a typology comprising five categories of chlamydia control activities. Each country was assigned to a category, based on responses to the questionnaire. Results: Experts in 29 of 33 (88%) invited countries responded. Thirteen of 29 countries (45%) had no current chlamydia control activities. Six countries in this group stated that there were plans to introduce chlamydia screening programmes. There were five countries (17%) with case management guidelines only. Three countries (10%) also recommended case finding amongst partners of diagnosed chlamydia cases or people with another sexually transmitted infection. Six countries (21%) further specified groups of asymptomatic people eligible for opportunistic chlamydia testing. Two countries (7%) reported a chlamydia screening programme. There was no consistent association between the per capita gross domestic product of a country and the intensity of chlamydia control activities (P = 0.816). Conclusion: A newly developed classification system allowed the breadth of ongoing national chlamydia control activities to be described and categorized. Chlamydia control strategies should ensure that clinical guidelines to optimize chlamydia diagnosis and case management have been implemented before considering the appropriateness of screening programmes.

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.

Classification Using Generalized Partial Least Squares

The advances in computational biology have made simultaneous monitoring of thousands of features possible. The high throughput technologies not only bring about a much richer information context in which to study various aspects of gene functions but they also present challenge of analyzing data with large number of covariates and few samples. As an integral part of machine learning, classification of samples into two or more categories is almost always of interest to scientists. In this paper, we address the question of classification in this setting by extending partial least squares (PLS), a popular dimension reduction tool in chemometrics, in the context of generalized linear regression based on a previous approach, Iteratively ReWeighted Partial Least Squares, i.e. IRWPLS (Marx, 1996). We compare our results with two-stage PLS (Nguyen and Rocke, 2002A; Nguyen and Rocke, 2002B) and other classifiers. We show that by phrasing the problem in a generalized linear model setting and by applying bias correction to the likelihood to avoid (quasi)separation, we often get lower classification error rates.

Developing ICF Core Sets for persons with sleep disorders based on the International Classification of Functioning, Disability and Health

BACKGROUND: With the International Classification of Functioning, Disability and Health (ICF), we can now rely on a globally agreed-upon framework and system for classifying the typical spectrum of problems in the functioning of persons given the environmental context in which they live. ICF Core Sets are subgroups of ICF items selected to capture those aspects of functioning that are most likely to be affected by sleep disorders. OBJECTIVE: The objective of this paper is to outline the developmental process for the ICF Core Sets for Sleep. METHODS: The ICF Core Sets for Sleep will be defined at an ICF Core Sets Consensus Conference, which will integrate evidence from preliminary studies, namely (a) a systematic literature review regarding the outcomes used in clinical trials and observational studies, (b) focus groups with people in different regions of the world who have sleep disorders, (c) an expert survey with the involvement of international clinical experts, and (d) a cross-sectional study of people with sleep disorders in different regions of the world. CONCLUSION: The ICF Core Sets for Sleep are being designed with the goal of providing useful standards for research, clinical practice and teaching. It is hypothesized that the ICF Core Sets for Sleep will stimulate research that leads to an improved understanding of functioning, disability, and health in sleep medicine. It is of further hope that such research will lead to interventions and accommodations that improve the restoration and maintenance of functioning and minimize disability among people with sleep disorders throughout the world.

Screening for anemia in Red Cross blood donor clinics

Accurate screening for anemia at Red Cross blood donor clinics is essential to maintain a safe national blood supply. Despite the importance of identifying anemia correctly by measurement of hemoglobin or hematocrit (hemoglobin/hematocrit) there is no consensus regarding the efficacy of the current two stage screening method which uses the Readacrit$\sp{\rm tm}$ microhematocrit in conjunction with copper sulfate.^ A cross-sectional study was implemented in which hemoglobin/hematocrit was measured, with the present method and four new devices, on 504 prospective blood donors at a Canadian Red Cross permanent blood donor clinic in London, Canada. Concurrently gathered, venous and capillary blood samples were tested by each device and compared to Coulter S IV$\sp{\rm tm}$ determined venous standard readings. Instrument hemoglobin/hematocrit means were statistically calibrated to the standard ones in order to appraise systematic deviations from the standard. Classification analysis was employed to assess concordance between each instrument and the standard when classifying prospective donors as anemic or non-anemic. This was done both when each instrument was used alone (single stage) and when copper sulfate was used as a preliminary screen (two stage) and simulated over a range of anemia prevalences. The Hemoximeter$\sp{\rm tm}$ and Compur M1000$\sp{\rm tm}$ devices had the highest correlations of hemoglobin measurements with the standard ones for both capillary (n.s.) and venous blood (p $<$.05). Analysis of variance (anova) also showed them to be the most accurate (p $<$.05), as did both single and two stage classification analysis, therefore, they are both recommended. There was a smaller difference between instruments for two stage than for single stage screening; therefore instrument choice is less crucial for the former. The present method was adequate for two stage screening as tested but simulations showed that it would discriminate poorly in populations with a higher prevalence of anemia. The Stat-crit and Readacrit, which measure hematocrit, became less accurate at crucial low hematocrit levels. In light of this finding and the introduction of new, effective and easy to use hemoglobin measuring instruments, the continued use of hematocrit as a surrogate for hemoglobin, is not recommended. ^