Prediction of fat-free mass using bioelectrical impedance analysis in young adults from five populations of African origin.

Background/objectives:Bioelectrical impedance analysis (BIA) is used in population and clinical studies as a technique for estimating body composition. Because of significant under-representation in existing literature, we sought to develop and validate predictive equation(s) for BIA for studies in populations of African origin.Subjects/methods:Among five cohorts of the Modeling the Epidemiologic Transition Study, height, weight, waist circumference and body composition, using isotope dilution, were measured in 362 adults, ages 25-45 with mean body mass indexes ranging from 24 to 32. BIA measures of resistance and reactance were measured using tetrapolar placement of electrodes and the same model of analyzer across sites (BIA 101Q, RJL Systems). Multiple linear regression analysis was used to develop equations for predicting fat-free mass (FFM), as measured by isotope dilution; covariates included sex, age, waist, reactance and height(2)/resistance, along with dummy variables for each site. Developed equations were then tested in a validation sample; FFM predicted by previously published equations were tested in the total sample.Results:A site-combined equation and site-specific equations were developed. The mean differences between FFM (reference) and FFM predicted by the study-derived equations were between 0.4 and 0.6âeuro0/00kg (that is, 1% difference between the actual and predicted FFM), and the measured and predicted values were highly correlated. The site-combined equation performed slightly better than the site-specific equations and the previously published equations.Conclusions:Relatively small differences exist between BIA equations to estimate FFM, whether study-derived or published equations, although the site-combined equation performed slightly better than others. The study-derived equations provide an important tool for research in these understudied populations.

Predicting hematologic toxicity in patients undergoing radioimmunotherapy with 90Y-ibritumomab tiuxetan or 131I-tositumomab.

This study aimed at identifying clinical factors for predicting hematologic toxicity after radioimmunotherapy with (90)Y-ibritumomab tiuxetan or (131)I-tositumomab in clinical practice. Hematologic data were available from 14 non-Hodgkin lymphoma patients treated with (90)Y-ibritumomab tiuxetan and 18 who received (131)I-tositumomab. The percentage baseline at nadir and 4 wk post nadir and the time to nadir were selected as the toxicity indicators for both platelets and neutrophils. Multiple linear regression analysis was performed to identify significant predictors (P < 0.05) of each indicator. For both platelets and neutrophils, pooled and separate analyses of (90)Y-ibritumomab tiuxetan and (131)I-tositumomab data yielded the time elapsed since the last chemotherapy as the only significant predictor of the percentage baseline at nadir. The extent of bone marrow involvement was not a significant factor in this study, possibly because of the short time elapsed since the last chemotherapy of the 7 patients with bone marrow involvement. Because both treatments were designed to deliver a comparable bone marrow dose, this factor also was not significant. None of the 14 factors considered was predictive of the time to nadir. The R(2) value for the model predicting percentage baseline at nadir was 0.60 for platelets and 0.40 for neutrophils. This model predicted the platelet and neutrophil toxicity grade to within ±1 for 28 and 30 of the 32 patients, respectively. For the 7 patients predicted with grade I thrombocytopenia, 6 of whom had actual grade I-II, dosing might be increased to improve treatment efficacy. The elapsed time since the last chemotherapy can be used to predict hematologic toxicity and customize the current dosing method in radioimmunotherapy.

The relationship between a short measure of health status and physical activity in a workplace population.

Many interventions promoting physical activity (PA) are effective in preventing disease onset, and although studies have found a positive relationship between health-related quality of life (HRQL) and PA, most of these studies have focused on older adults and those with chronic conditions. Less is known regarding the association between PA level and HRQL among healthy adults. Our objective was to analyse the relationship between PA level and HRQL among a sample of 573 employees aged 20-68 taking part in a workplace intervention to promote PA. Measures included HRQL (using a single item) and PA (i.e. Godin Leisure-Time Questionnaire). The Modified Canadian Aerobic Fitness Test (MCAFT) was also completed by 10% of the employees. MET-minute scores (assessing energy expenditure over one week) were compared across HRQL categories using ANOVA. A multiple linear regression analysis was conducted to further examine the relationship between HRQL and PA, controlling for potential covariates. Participants in the higher health status categories were found to report higher levels of energy expenditure (one-way ANOVA, p < 0.001). In the multiple linear regression model, each unit increase in health status level translated in a mean increase of 356 MET-minutes in energy expenditure (p < 0.001). This single-item assessment of health status explained six percent of the variance in energy expenditure. The study concludes that higher energy expenditure through PA among an adult workplace population is positively associated with increased health status, and it also suggests that a single-item HRQL measure is suitable for community- and population-based studies, reducing response burden and research costs.

Treatment of ruptured abdominal aortic aneurysm, a permanent challenge or a waste of resources? Prediction of outcome using a multi-organ-dysfunction score.

OBJECTIVES: in a retrospective study, attempts have been made to identify individual organ-dysfunction risk profiles influencing the outcome after surgery for ruptured abdominal aortic aneurysms. METHODS: out of 235 patients undergoing graft replacement for abdominal aortic aneurysms, 57 (53 men, four women, mean age 72 years [s.d. 8.8]) were treated for ruptured aneurysms in a 3-year period. Forty-eight preoperative, 13 intraoperative and 34 postoperative variables were evaluated statistically. A simple multi-organ dysfunction (MOD) score was adopted. RESULTS: the perioperative mortality was 32%. Three patients died intraoperatively, four within 48 h and 11 died later. A significant influence for pre-existing risk factors was identified only for cardiovascular diseases. Multiple linear-regression analysis indicated that a haemoglobin <90 g/l, systolic blood pressure <80 mmHg and ECG signs of ischaemia at admission were highly significant risk factors. The cause of death for patients, who died more than 48 h postoperatively, was mainly MOD. All patients with a MOD score >/=4 died (n=7). These patients required 27% of the intensive-care unit (ICU) days of all patients and 72% of the ICU days of the non-survivors. CONCLUSION: patients with ruptured aortic aneurysms from treatment should not be excluded. However, a physiological scoring system after 48 h appears justifiable in order to decide on the appropriateness of continual ICU support.

Trabecular bone score (TBS) the new parameter of 2D texture analysis for the evaluation of 3D bone micro architecture status

X-ray is a technology that is used for numerous applications in the medical field. The process of X-ray projection gives a 2-dimension (2D) grey-level texture from a 3- dimension (3D) object. Until now no clear demonstration or correlation has positioned the 2D texture analysis as a valid indirect evaluation of the 3D microarchitecture. TBS is a new texture parameter based on the measure of the experimental variogram. TBS evaluates the variation between 2D image grey-levels. The aim of this study was to evaluate existing correlations between 3D bone microarchitecture parameters - evaluated from μCT reconstructions - and the TBS value, calculated on 2D projected images. 30 dried human cadaveric vertebrae were acquired on a micro-scanner (eXplorer Locus, GE) at isotropic resolution of 93 μm. 3D vertebral body models were used. The following 3D microarchitecture parameters were used: Bone volume fraction (BV/TV), Trabecular thickness (TbTh), trabecular space (TbSp), trabecular number (TbN) and connectivity density (ConnD). 3D/2D projections has been done by taking into account the Beer-Lambert Law at X-ray energy of 50, 100, 150 KeV. TBS was assessed on 2D projected images. Correlations between TBS and the 3D microarchitecture parameters were evaluated using a linear regression analysis. Paired T-test is used to assess the X-ray energy effects on TBS. Multiple linear regressions (backward) were used to evaluate relationships between TBS and 3D microarchitecture parameters using a bootstrap process. BV/TV of the sample ranged from 18.5 to 37.6% with an average value at 28.8%. Correlations' analysis showedthat TBSwere strongly correlatedwith ConnD(0.856≤r≤0.862; p<0.001),with TbN (0.805≤r≤0.810; p<0.001) and negatively with TbSp (−0.714≤r≤−0.726; p<0.001), regardless X-ray energy. Results show that lower TBS values are related to "degraded" microarchitecture, with low ConnD, low TbN and a high TbSp. The opposite is also true. X-ray energy has no effect onTBS neither on the correlations betweenTBS and the 3Dmicroarchitecture parameters. In this study, we demonstrated that TBS was significantly correlated with 3D microarchitecture parameters ConnD and TbN, and negatively with TbSp, no matter what X-ray energy has been used. This article is part of a Special Issue entitled ECTS 2011. Disclosure of interest: None declared.

Strong EBV-specific CD8+ T-cell response in patients with early multiple sclerosis

Epstein-Barr virus (EBV) has been associated with multiple sclerosis (MS), however, most studies examining the relationship between the virus and the disease have been based on serologies, and if EBV is linked to MS, CD8+ T cells are likely to be involved as they are important both in MS pathogenesis and in controlling viruses. We hypothesized that valuable information on the link between MS and EBV would be ascertained from the study of frequency and activation levels of EBV-specific CD8+ T cells in different categories of MS patients and control subjects. We investigated EBV-specific cellular immune responses using proliferation and enzyme linked immunospot assays, and humoral immune responses by analysis of anti-EBV antibodies, in a cohort of 164 subjects, including 108 patients with different stages of MS, 35 with other neurological diseases and 21 healthy control subjects. Additionally, the cohort were all tested against cytomegalovirus (CMV), another neurotropic herpes virus not convincingly associated with MS, nor thought to be deleterious to the disease. We corrected all data for age using linear regression analysis over the total cohorts of EBV- and CMV-infected subjects. In the whole cohort, the rate of EBV and CMV infections were 99% and 51%, respectively. The frequency of IFN-gamma secreting EBV-specific CD8+ T cells in patients with clinically isolated syndrome (CIS) was significantly higher than that found in patients with relapsing-remitting MS (RR-MS), secondary-progressive MS, primary-progressive MS, patients with other neurological diseases and healthy controls. The shorter the interval between MS onset and our assays, the more intense was the EBV-specific CD8+ T-cell response. Confirming the above results, we found that EBV-specific CD8+ T-cell responses decreased in 12/13 patients with CIS followed prospectively for 1.0 +/- 0.2 years. In contrast, there was no difference between categories for EBV-specific CD4+ T cell, or for CMV-specific CD4+ and CD8+ T-cell responses. Anti-EBV-encoded nuclear antigen-1 (EBNA-1)-specific antibodies correlated with EBV-specific CD8+ T cells in patients with CIS and RR-MS. However, whereas EBV-specific CD8+ T cells were increased the most in early MS, EBNA-1-specific antibodies were increased in early as well as in progressive forms of MS. Our data show high levels of CD8+ T-cell activation against EBV--but not CMV--early in the course of MS, which support the hypothesis that EBV might be associated with the onset of this disease.

Predicting the physicochemical profile of diastereoisomeric histidine-containing dipeptides by property space analysis.

OBJECTIVES: This study aimed at measuring the lipophilicity and ionization constants of diastereoisomeric dipeptides, interpreting them in terms of conformational behavior, and developing statistical models to predict them. METHODS: A series of 20 dipeptides of general structure NH(2) -L-X-(L or D)-His-OMe was designed and synthetized. Their experimental ionization constants (pK(1) , pK(2) and pK(3) ) and lipophilicity parameters (log P(N) and log D(7.4) ) were measured by potentiometry. Molecular modeling in three media (vacuum, water, and chloroform) was used to explore and sample their conformational space, and for each stored conformer to calculate their radius of gyration, virtual log P (preferably written as log P(MLP) , meaning obtained by the molecular lipophilicity potential (MLP) method) and polar surface area (PSA). Means and ranges were calculated for these properties, as was their sensitivity (i.e., the ratio between property range and number of rotatable bonds). RESULTS: Marked differences between diastereoisomers were seen in their experimental ionization constants and lipophilicity parameters. These differences are explained by molecular flexibility, configuration-dependent differences in intramolecular interactions, and accessibility of functional groups. Multiple linear equations correlated experimental lipophilicity parameters and ionization constants with PSA range and other calculated parameters. CONCLUSION: This study documents the differences in lipophilicity and ionization constants between diastereoisomeric dipeptides. Such configuration-dependent differences are shown to depend markedly on differences in conformational behavior and to be amenable to multiple linear regression. Chirality 24:566-576, 2012. © 2012 Wiley Periodicals, Inc.

Birth weight, weight change, and blood pressure during childhood and adolescence: a school-based multiple cohort study.

OBJECTIVE: We assessed the association between birth weight, weight change, and current blood pressure (BP) across the entire age-span of childhood and adolescence in large school-based cohorts in the Seychelles, an island state in the African region. METHODS: Three cohorts were analyzed: 1004 children examined at age 5.5 and 9.1 years, 1886 children at 9.1 and 12.5, and 1575 children at 12.5 and 15.5, respectively. Birth and 1-year anthropometric data were gathered from medical files. The outcome was BP at age 5.5, 9.1, 12.5 or 15.5 years, respectively. Conditional linear regression analysis was used to estimate the relative contribution of changes in weight (expressed in z-score) during different age periods on BP. All analyses were adjusted for height. RESULTS: At all ages, current BP was strongly associated with current weight. Birth weight was not significantly associated with current BP. Upon adjustment for current weight, the association between birth weight and current BP tended to become negative. Conditional linear regression analyses indicated that changes in weight during successive age periods since birth contributed substantially to current BP at all ages. The strength of the association between weight change and current BP increased throughout successive age periods. CONCLUSION: Weight changes during any age period since birth have substantial impact on BP during childhood and adolescence, with BP being more responsive to recent than earlier weight changes.

Surfactant protein-D and exposure to bioaerosols in wastewater and garbage workers.

PURPOSE: Bioaerosols and their constituents, such as endotoxins, are capable of causing an inflammatory reaction at the level of the lung-blood barrier, which becomes more permeable. Thus, it was hypothesized that occupational exposure to bioaerosols can increase leakage of surfactant protein-D (SP-D), a lung-specific protein, into the bloodstream. METHODS: SP-D was determined by ELISA in 316 wastewater workers, 67 garbage collectors, and 395 control subjects. Exposure was assessed with four interview-based indicators and by preliminary endotoxin measurements using the Limulus amoebocyte lysate assay. Influence of exposure on serum SP-D was assessed by multiple linear regression considering smoking, glomerular function, lung diseases, obesity, and other confounders. RESULTS: Overall, mean exposure levels to endotoxins were below 100 EU/m(3). However, special tasks of wastewater workers caused higher endotoxin exposure. SP-D concentration was slightly increased in this occupational group and associated with the occurrence of splashes and contact to raw sewage. No effect was found in garbage collectors. Smoking increased serum SP-D. No clinically relevant correlation between spirometry results and SP-D concentrations appeared. CONCLUSIONS: These results support the hypothesis that inhalation of bioaerosols, even at low concentrations, has a subclinical effect on the lung-blood barrier, the permeability of which increases without associated spirometric changes.

Online estimation of respiratory mechanics in non-invasive pressure support ventilation: a bench model study.

An online algorithm for determining respiratory mechanics in patients using non-invasive ventilation (NIV) in pressure support mode was developed and embedded in a ventilator system. Based on multiple linear regression (MLR) of respiratory data, the algorithm was tested on a patient bench model under conditions with and without leak and simulating a variety of mechanics. Bland-Altman analysis indicates reliable measures of compliance across the clinical range of interest (± 11-18% limits of agreement). Resistance measures showed large quantitative errors (30-50%), however, it was still possible to qualitatively distinguish between normal and obstructive resistances. This outcome provides clinically significant information for ventilator titration and patient management.

Effect of antenatal corticosteroids on fetal growth and gestational age at birth.

OBJECTIVE: To estimate the effect of multiple courses of antenatal corticosteroids on neonatal size, controlling for gestational age at birth and other confounders, and to determine whether there was a dose-response relationship between number of courses of antenatal corticosteroids and neonatal size. METHODS: This is a secondary analysis of the Multiple Courses of Antenatal Corticosteroids for Preterm Birth Study, a double-blind randomized controlled trial of single compared with multiple courses of antenatal corticosteroids in women at risk for preterm birth and in which fetuses administered multiple courses of antenatal corticosteroids weighed less, were shorter, and had smaller head circumferences at birth. All women (n=1,858) and children (n=2,304) enrolled in the Multiple Courses of Antenatal Corticosteroids for Preterm Birth Study were included in the current analysis. Multiple linear regression analyses were undertaken. RESULTS: Compared with placebo, neonates in the antenatal corticosteroids group were born earlier (estimated difference and confidence interval [CI]: -0.428 weeks, CI -0.10264 to -0.75336; P=.01). Controlling for gestational age at birth and confounding factors, multiple courses of antenatal corticosteroids were associated with a decrease in birth weight (-33.50 g, CI -66.27120 to -0.72880; P=.045), length (-0.339 cm, CI -0.6212 to -0.05676]; P=.019), and head circumference (-0.296 cm, -0.45672 to -0.13528; P<.001). For each additional course of antenatal corticosteroids, there was a trend toward an incremental decrease in birth weight, length, and head circumference. CONCLUSION: Fetuses exposed to multiple courses of antenatal corticosteroids were smaller at birth. The reduction in size was partially attributed to being born at an earlier gestational age but also was attributed to decreased fetal growth. Finally, a dose-response relationship exists between the number of corticosteroid courses and a decrease in fetal growth. The long-term effect of these findings is unknown. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, www.clinicaltrials.gov, NCT00187382. LEVEL OF EVIDENCE: II.

Improving generalized regression analysis for the spatial prediction of forest communities

Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.

Early disturbances of gamma band dynamics in mild cognitive impairment.

Recent studies have indicated that gamma band oscillations participate in the temporal binding needed for the synchronization of cortical networks involved in short-term memory and attentional processes. To date, no study has explored the temporal dynamics of gamma band in the early stages of dementia. At baseline, gamma band analysis was performed in 29 cases with mild cognitive impairment (MCI) during the n-back task. Based on phase diagrams, multiple linear regression models were built to explore the relationship between the cognitive status and gamma oscillation changes over time. Individual measures of phase diagram complexity were made using fractal dimension values. After 1 year, all cases were assessed neuropsychologically using the same battery. A total of 16 MCI patients showed progressive cognitive decline (PMCI) and 13 remained stable (SMCI). When adjusted for gamma values at lag -2, and -3 ms, PMCI cases displayed significantly lower average changes in gamma values than SMCI cases both in detection and 2-back tasks. Gamma fractal dimension of PMCI cases displayed significantly higher gamma fractal dimension values compared to SMCI cases. This variable explained 11.8% of the cognitive variability in this series. Our data indicate that the progression of cognitive decline in MCI is associated with early deficits in temporal binding that occur during the activation of selective attention processes.

Surfactant protein A, exposure to endotoxin, and asthma in garbage collectors and in wastewater workers.

Endotoxin causes an inflammation at the bronchial and alveolar level. The inflammation-induced increase in permeability of the bronchoalveolar epithelial barrier is supposed to cause a leakage of pneumoproteins. Therefore, their concentrations are expected to increase in the bloodstream.This study aimed at examining the association between occupational exposure to endotoxin and a serum pneumoprotein, surfactant protein A, to look for nonoccupational factors capable of confounding this association, and examine the relation between surfactant protein A and spirometry. There were 369 control subjects, 325 wastewater workers, and 84 garbage collectors in the study. Exposure to endotoxin was assessed through personal sampling and the Limulus amebocytes lysate assay. Surfactant protein A was determined by an in house sandwich enzyme-linked immunosorbent assay (ELISA) in 697 subjects. Clinical and smoking history were ascertained and spirometry carried out according to American Thoracic Society criteria. Multiple linear regression was used for statistical analysis. Exposure was fairly high during some tasks in wastewater workers but did not influence surfactant protein A. Surfactant protein A was lower in asthmatics. Interindividual variability was large. No correlation with spirometry was found. Endotoxin has no effect on surfactant protein A at these endotoxin levels and serum surfactant protein A does not correlate with spirometry. The decreased surfactant protein A secretion in asthmatics requires further study.

Regression analysis of spatial data.

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.