196,461 research outputs found
Factors that cause University students to drop out. An alternative modelling of interaction terms in logistic regression models
No full textAssociation of inflammation with anemia in patients with chronic kidney disease not requiring chronic dialysis.
No full textBackground. Anaemia associated with chronic kidney disease (CKD) has substantial public health importance. However, the association of haemoglobin concentrations with inflammation in the setting of decreased kidney function is not well established. Methods. We analysed cross-sectional data from 7389 outpatient adults, who were referred by general practitioners for routine blood testing between June 2006 and June 2007. Glomerular filtration rate (eGFR) was estimated by the abbreviated Modification of Diet in Renal Disease (MDRD) equation. Multivariable linear regression analysis was used to identify factors independently associated with haemoglobin concentrations across eGFR categories as the main outcome. Results. Of the 7389 participants included in the analytic cohort 2221 (30.1%) participants had eGFR ≥90 mL/min/m2, 4310 (58.3%) 60-89 mL/min/m2 and 858 (11.6%) <60 mL/min/m2. There were significant, graded, increases in high sensitivity C-reactive protein (hs-CRP) and haemoglobin concentrations across eGFR categories independent of age, gender, plasma glucose and lipids (P < 0.0001 for trends). In the multivariable regression analysis, increased hs-CRP concentrations were independently associated with lower haemoglobin concentrations at different stages of eGFR (P < 0.0001 for all). Other independent predictors of lower haemoglobin were older age, female gender and lower eGFR. Conclusions. Our findings suggest that increased plasma hs-CRP concentrations are independently associated with anaemia in the setting of decreased kidney function in a large cohort of unselected adult outpatients. © The Author [2008]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved
Reference growth charts for assessing growth performance of Posidonia oceanica (L.) Delile
No full textPosidonia oceanica is considered a key species due to its different roles as primary producer, substrate for many species, shoreline erosion protector and long-term carbon store (1).The importance of P. oceanicahas stimulated several studies aimed at quantifying its status. In particular growth performance of rhizomes has become among the most used descriptors for monitoring changes of P. oceanicameadows induced by human or naturalexogenous factors (2). However, ability to detect any change of growth in space or in time is often confounded by natural age-induced variations, which involves serious interpretation problems (3). A general approach adopted to overcome this problem is to build growth charts as reference tool for comparison purposes. Charts describing patterns of biometric features conditioned to age are increasingly used as comparison tools, even if almost exclusively in Auxology(4). Their use can be extended to other disciplines, including ecological studies, although very large data sets are required for obtaining reliable estimates and curves should be flexible enough to account for non-linear growth pattern over age (5). In this work reference growth charts involving different P. oceanicagrowth performance measures (speed of growth and primary production of rhizomes) will be presented. Curves have been built using proper statistical frameworks (GLMM, Segmented and Quantile Regressions), based on more than 13000 annualgrowth data recorded by lepidochronology (6) on about 1600 shoots collected at 4–32 m depth range along Sicilian coasts.Growth patterns exhibited distinct trends as regards the relationships with depth: neither speed of growth nor primary production of rhizomes depended on depth until 14 m, while at deeper stands significant linear decrease by 3.5–2.0% for 1 m increase in depth was observed, due to light and sedimentation reduction. The considerable size of the dataset allowed to estimate the accurate shapes of the percentile curves (from 5thto 95th), revealing non monotonic relationships of growth with respect to shoot age with an initial increase followed by an overall decrease of 40% during the following years of the explored lifespan. The accompanying model-based classification procedures presented, will allow to obtain comparable results also when age of shoots is largely different (up to 20 years) (7). The growth charts may represent a noteworthy tool for researchers involved in studying of different aspects of seagrass monitoring. It is hoped that the proposed framework will facilitate assessment of growth performance status and comparative analysis of growth data from different populations around the Mediterranean Se
Analyzing Temperature Effects on Mortality Within the R Environment: The Constrained Segmented Distributed Lag Parameterization
No full textHere we present and discuss the R package modTempEff including a set of functions aimed at modelling temperature effects on mortality with time series data. The functions fit a particular log linear model which allows to capture the two main features of mortality- temperature relationships: nonlinearity and distributed lag effect. Penalized splines and segmented regression constitute the core of the modelling framework. We briefly review the model and illustrate the functions throughout a simulated dataset.
A segmented regression model for event history data: an application to the fertility patterns in Italy
No full textWe propose a segmented discrete-time model for the analysis of event history data in demographic research. Through a unified regression framework, the model provides estimates of the effects of explanatory variables and jointly accommodates flexibly non-proportional differences via segmented relationships. The main appeal relies on ready availability of parameters, changepoints, and slopes, which may provide meaningful and intuitive information on the topic. Furthermore, specific linear constraints on the slopes may also be set to investigate particular patterns. We investigate the intervals between cohabitation and first childbirth and from first to second childbirth using individual data for Italian women from the Second National Survey on Fertility. The model provides insights into dramatic decrease of fertility experienced in Italy, in that it detects a 'common' tendency in delaying the onset of childbearing for the more recent cohorts and a 'specific' postponement strictly depending on the educational level and age at cohabitation.segmented regression, discrete-time hazard models, changepoints, parity progression, event occurrence data,
Analyzing Temperature Effects on Mortality Within the R Environment: The Constrained Segmented Distributed Lag Parameterization
No full textHere we present and discuss the R package modTempEff including a set of functions aimed at modelling temperature effects on mortality with time series data. The functions fit a particular log linear model which allows to capture the two main features of mortality- temperature relationships: nonlinearity and distributed lag effect. Penalized splines and segmented regression constitute the core of the modelling framework. We briefly review the model and illustrate the functions throughout a simulated dataset
Comment on "Estimating average annual per cent change in trend analysis"
No full textWe discuss some issues relevant to paper of Clegg and co-authors published in Statistics in Medicine; 28, 3670-3682. Emphasis is on computation of the variance of the sum of products of two estimates, slopes and breakpoints
Self-reported exercise and quality of life in young type 1 diabetic subjects.
No full textEvaluation of quality of life is important in treatment strategies of chronic illnesses, such as diabetes mellitus. The present study aimed at measuring the impact of self-reported exercise on quality of life in T1DM patients. Fifty-three young T1DM patients on intensive insulin-treatment regime who were regularly attending the Diabetes Clinic were selected. At the end of the scheduled clinic visit, they were asked to fill in an Italian version of the Diabetes Quality of Life (DQOL) questionnaire; 30 patients exercised regularly, whereas 23 were sedentary. Patients with clinical and laboratory evidence of major eye, renal and cardiovascular diseases were excluded. A significant difference in the scale of satisfaction (1.9+/-0.3 vs 2.2+/-0.5; p=0.009), along with a better HbA(1c) level (7.0+/-1.0 vs 7.8+/-1.2; p=0.014), was observed in physically active patients as compared to sedentary ones, whereas there were no differences between the 2 groups with respect to the impact and worry scale. Moreover, there were no significant correlations between glucose control parameters and the quality of life scores. In conclusion, we showed that self-reported exercise is associated with both a better quality of life and a better metabolic control in young T1DM patients. Further efforts should however be made to recognize all factors that can help motivate patients to exercise
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