Body mass index values for newborns according to gestational age

Objective: The combination of twho anthropometric parameters has been more appropriate to assess body composition and proportions in children, with special attention to the Body Mass Index (BMI), as it relates weight and length. However the BMI values for the neonatal period have not been determined yet. This study shows the BMI for newborns at different gestational ages represented in a normal smoothed percentile curve. Methods: Retrospective study including 2,406 appropriate for gestational age newborns following the Alexander et al curve (1996) from 29 to 42 weeks of gestational age. Weight and lenght were measured following standard procedures. For the construction aof a normal smoothed percentile curve, the 3(rd) 5(th), 10(th), 25(th), 5(th), 75(th), 90(th) and 95(th) percentiles were determined and a statistical procedure based on the mathematical model ""sinosuoidal fit"" was applied to establish a curve that estimates biological growth parameters. Results: The Body Mass Index values for gestational age in all percentiles shows a steady increase up to 38 weeks, levels off up to the 40(th) week, followed by a slight decrease to the 42(nd) week in both genders. Conclusion: The results show a direct correlation between gestational age and Body Mass Index for both genders in the nine percentiles, and can provide a useful reference to assess intra-uterine proportional growth.

Peak expiratory flow values are higher in older and taller healthy male children: An observational study

Purpose: Peak expiratory flow (PEF) was measured in healthy children aged five to ten years in order to provide baseline values and to determine correlations between PEF and factors such as gender, age and type of school. Methods: After the Ethical Committee of Research in Human of the School of Medicine of ABC - FMABC approval, PEF and height were measured in 1942 children between five and ten years old from nine public schools and nine private schools throughout Sao Bernardo do Campo City. PEF was measured using the Mini-Wright Peak Flow Meter (Clement Clarke International Ltd.) and. height was measured using a Sanny professional stadiometer. Results: Significant differences were found in values for PEF: higher values were seen in older students in comparison with younger students, in males in comparison with females and in students from private schools in comparison with public schools, with average values ranging from 206 L/min to 248 L/min,. Linear correlations were seen for PEF values with both height and age (Spearman Coefficient). Conclusions: Differences were seen for PEF between genders and between types of school, and a linear correlation was seen for PEF with both age and height in healthy children from five to ten years old.

Comparison of signal-to-cutoff values in first, second, and third generation enzyme immunoassays for the diagnosis of HTLV-1/2 infection in ""at-risk"" individuals from Sao Paulo, Brazil

Data obtained during routine diagnosis of human T-cell lymphotropic virus type 1 (HTLV-1) and 2 (HTLV-2) in ""at-risk"" individuals from Sao Paulo, Brazil using signal-to-cutoff (S/C) values obtained by first, second, and third generation enzyme immunoassay (EIA) kits, were compared. The highest S/C values were obtained with third generation EIA kits, but no correlation was detected between these values and specific antibody reactivity to HTLV-1, HTLV-2, or untyped HTLV (p = 0.302). In addition, use of these third generation kits resulted in HTLV-1/2 false-positive samples. In contrast, first and second generation EIA kits showed high specificity, and the second generation EIA kits showed the highest efficiency, despite lower S/C values. Using first and second generation EIA kits, significant differences in specific antibody detection of HTLV-1, relative to HTLV-2 (p = 0.019 for first generation and p < 0.001 for second generation EIA kits) and relative to untyped HTLV (p = 0.025 for first generation EIA kits), were observed. These results were explained by the composition and format of the assays. In addition, using receiver operating characteristics (ROC) analysis, a slight adjustment in cutoff values for third generation EIA kits improved their specificities and should be used when HTLV ""at-risk"" populations from this geographic area are to be evaluated. (C) 2009 Elsevier B.V. All rights reserved.

Evolutionary tuning of SVM parameter values in multiclass problems

Support vector machines (SVMs) were originally formulated for the solution of binary classification problems. In multiclass problems, a decomposition approach is often employed, in which the multiclass problem is divided into multiple binary subproblems, whose results are combined. Generally, the performance of SVM classifiers is affected by the selection of values for their parameters. This paper investigates the use of genetic algorithms (GAs) to tune the parameters of the binary SVMs in common multiclass decompositions. The developed GA may search for a set of parameter values common to all binary classifiers or for differentiated values for each binary classifier. (C) 2008 Elsevier B.V. All rights reserved.

Performance of balanced two-stage empirical predictors of realized cluster latent values from finite populations: A simulation study

Predictors of random effects are usually based on the popular mixed effects (ME) model developed under the assumption that the sample is obtained from a conceptual infinite population; such predictors are employed even when the actual population is finite. Two alternatives that incorporate the finite nature of the population are obtained from the superpopulation model proposed by Scott and Smith (1969. Estimation in multi-stage surveys. J. Amer. Statist. Assoc. 64, 830-840) or from the finite population mixed model recently proposed by Stanek and Singer (2004. Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 1119-1130). Predictors derived under the latter model with the additional assumptions that all variance components are known and that within-cluster variances are equal have smaller mean squared error (MSE) than the competitors based on either the ME or Scott and Smith`s models. As population variances are rarely known, we propose method of moment estimators to obtain empirical predictors and conduct a simulation study to evaluate their performance. The results suggest that the finite population mixed model empirical predictor is more stable than its competitors since, in terms of MSE, it is either the best or the second best and when second best, its performance lies within acceptable limits. When both cluster and unit intra-class correlation coefficients are very high (e.g., 0.95 or more), the performance of the empirical predictors derived under the three models is similar. (c) 2007 Elsevier B.V. All rights reserved.