Psychometric qualities of the Brazilian versions of the Fagerstrom Test for Nicotine Dependence and the Heaviness of Smoking Index

This study examined the psychometric properties of the Brazilian versions of the Fagerstrom Test for Nicotine Dependence (FTND) and the Heaviness of Smoking Index (HSI). The test-retest reliability of the FTND was assessed in a sample of 61 smoking university students, with a 15-day interval between assessments. The interrater reliability was examined in 30 smoking patients of a psychosocial care center for alcohol and drug users (PCC-AD). The reliability coefficient was estimated by the kappa and intraclass correlation coefficients. The predictive validity, internal consistency, and factor structure of the FTND and the HSI were evaluated by factor analysis in 271 smokers treated at an emergency unit and at the PCC-AD. The gold standard was the nicotine dependence criteria of DSM-IV, as assessed by the Structured Clinical Interview for DSM-IV. The FTND showed high reliability, with correlation coefficients of .92 for test-retest reliability and .99 for interrater reliability. Both the FTND and the HSI presented high levels of sensitivity and specificity. The internal consistency evaluation yielded a Cronbach`s alpha coefficient of .83 for the FTND and of .56 for the HSI. An exploratory factor analysis found 2 factors in the FTND, which were validated by a confirmatory factor analysis. The results obtained in this study confirm the validity and reliability of the Brazilian versions of the FTND and the HSI.

Validation of the National Institutes of Health Stroke Scale, Modified Rankin Scale and Barthel Index in Brazil: The Role of Cultural Adaptation and Structured Interviewing

Background: We aimed to validate three widely used scales in stroke research in a multiethnic Brazilian population. Methods: The National Institutes of Health Stroke Scale (NIHSS), modified Rankin Scale (mRS) and Barthel Index (BI) were translated, culturally adapted and applied by two independent investigators. The mRS was applied with or without a previously validated structured interview. Interobserver agreement (kappa statistics) and intraclass correlation coefficients were calculated. Results: 84 patients underwent mRS (56 with and 28 without a structured interview), 57 BI and 62 NIHSS scoring. Intraclass correlation coefficient was 0.902 for NIHSS and 0.967 for BI. For BI, interobserver agreement was good (kappa = 0.70). For mRS, the structured interview improved interobserver agreement (kappa = 0.34 without a structured interview; 0.75 with a structured interview). Conclusion: The NIHSS, BI and mRS show good validity when translated and culturally adapted. Using a structured interview for the mRS improves interobserver concordance rates. Copyright (C) 2008 S. Karger AG, Basel

Asymmetric page split generalized index search trees for formal concept analysis

Formal Concept Analysis is an unsupervised machine learning technique that has successfully been applied to document organisation by considering documents as objects and keywords as attributes. The basic algorithms of Formal Concept Analysis then allow an intelligent information retrieval system to cluster documents according to keyword views. This paper investigates the scalability of this idea. In particular we present the results of applying spatial data structures to large datasets in formal concept analysis. Our experiments are motivated by the application of the Formal Concept Analysis idea of a virtual filesystem [11,17,15]. In particular the libferris [1] Semantic File System. This paper presents customizations to an RD-Tree Generalized Index Search Tree based index structure to better support the application of Formal Concept Analysis to large data sources.

Can the Insulin Sensitivity Index (ISI) in Association with Insulin-like Growth Factor Binding Protein-1 Identify Insulin Resistance Early in Overweight Children?

Association between insulin resistance (IR) and non-alcoholic fatty liver disease (NAFLD) has been reported. This prompted us to evaluate the power of the insulin sensitivity index (ISI) in association with IGFBP-1 to identify IR early in obese children/adolescents. OGTT was performed in 34 obese/overweight children/adolescents. Glucose, insulin and IGFBP-1 were measured in serum samples and ISI was calculated. Considering the presence of three or more risk factors for IR as a criterion for IR, ISI <4.6 showed 87.5% sensitivity and 94.5% specificity in diagnosing IR. IGFBP-1 was lower in the group with ISI <4.6 (p <0.01). In this group, three patients had higher than expected IGFBP-1, suggesting hepatic IR, while three patients with ISI >4.6 showed very low IGFBP-1 levels. Conclusion: ISI <4.6 is a good indicator of early peripheral IR and, associated with IGFBP-1, can identify increased risk of hepatic IR. Low IGFBP-1 levels among non-IR children may indicate increased portal insulin levels.

Plasma obestatin concentrations are negatively correlated with body mass index, insulin resistance index, and plasma leptin concentrations in obesity and anorexia nervosa

Background: Obestatin is a recently identified ghrelin gene product that was reported to inhibit appetite and gastric motility in contrast to ghrelin. We investigated fasting obestatin and ghrelin levels in patients with obesity and anorexia nervosa. Methods: Fasting plasma obestatin, acyl-ghrelin, desacyl-ghrelin, leptin, glucose serum adiponectin, and insulin were measured in 10 obese subjects, 11 restricting-type anorexics, and 11 control subjects. Results: Obese group had significantly lower levels of obestatin (p < .01), while anorexic group had significantly higher levels (p < .01). Obestatin was negatively correlated with body mass index (BMI) (r = -.74), glucose (r = -.56), insulin (r = -.55), leptin (r = -.66), and also with the homeostasis model assessment of insulin resistance (HOMA-R) (r = -.49) and was positively correlated with acyl-ghrelin (r = .65) and desacyl-ghrelin (r = .60). No correlation was seen between obestatin and adiponectin, but the latter was negatively correlated with both acyl-ghrelin and desacyl-ghrelin. Desacyl-ghrelin to acyl-ghrelin ratio was significantly different between anorexic and control groups (p < .05), while no difference was seen between obese and control groups. Conclusions: Both obestatin and ghrelin are increased in anorexic and decreased in obesity. We suggest that obestatin is a nutritional marker reflecting body adiposity and insulin resistance.