Bootstrapping pairs in Distance-Based Regression

La regressió basada en distàncies és un mètode de predicció que consisteix en dos passos: a partir de les distàncies entre observacions obtenim les variables latents, les quals passen a ser els regressors en un model lineal de mínims quadrats ordinaris. Les distàncies les calculem a partir dels predictors originals fent us d'una funció de dissimilaritats adequada. Donat que, en general, els regressors estan relacionats de manera no lineal amb la resposta, la seva selecció amb el test F usual no és possible. En aquest treball proposem una solució a aquest problema de selecció de predictors definint tests estadístics generalitzats i adaptant un mètode de bootstrap no paramètric per a l'estimació dels p-valors. Incluim un exemple numèric amb dades de l'assegurança d'automòbils.

Benchmarking therapeutic drug monitoring software: A systematic evaluation of available computer tools

Introduction: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on measurement of blood concentrations. Maintaining concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. In the last decades computer programs have been developed to assist clinicians in this assignment. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Method: Literature and Internet search was performed to identify software. All programs were tested on common personal computer. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software's characteristics. Numbers of drugs handled vary widely and 8 programs offer the ability to the user to add its own drug model. 10 computer programs are able to compute Bayesian dosage adaptation based on a blood concentration (a posteriori adjustment) while 9 are also able to suggest a priori dosage regimen (prior to any blood concentration measurement), based on individual patient covariates, such as age, gender, weight. Among those applying Bayesian analysis, one uses the non-parametric approach. The top 2 software emerging from this benchmark are MwPharm and TCIWorks. Other programs evaluated have also a good potential but are less sophisticated (e.g. in terms of storage or report generation) or less user-friendly.¦Conclusion: Whereas 2 integrated programs are at the top of the ranked listed, such complex tools would possibly not fit all institutions, and each software tool must be regarded with respect to individual needs of hospitals or clinicians. Interest in computing tool to support therapeutic monitoring is still growing. Although developers put efforts into it the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capacity of data storage and report generation.

Pericardial fat volume correlates with coronary vasomotion

Purpose: Recent studies showed that pericardial fat was independently correlated with the development of coronary artery disease (CAD). The mechanism remains unclear. We aimed at assessing a possible relationship between pericardial fat volume and endothelium-dependent coronary vasomotion, a surrogate of future cardiovascular events.Methods: Fifty healthy volunteers without known CAD or cardiovascular risk factors (CRF) were enrolled. They all underwent a dynamic Rb- 82 cardiac PET/CT to quantify myocardial blood flow (MBF) at rest, during MBF response to cold pressure test (CPT-MBF) and adenosine stress. Pericardial fat volume (PFV) was measured using a 3D volumetric CT method and common biological CRF (glucose and insulin levels, HOMA-IR, cholesterol, triglyceride, hs-CRP). Relationships between MBF response to CPT, PFV and other CRF were assessed using non-parametric Spearman correlation and multivariate regression analysis of variables with significant correlation on univariate analysis (Stata 11.0).Results: All of the 50 participants had normal MBF response to adenosine (2.7±0.6 mL/min/g; 95%CI: 2.6−2.9) and myocardial flow reserve (2.8±0.8; 95%CI: 2.6−3.0) excluding underlying CAD. Simple regression analysis revealed a significant correlation between absolute CPTMBF and triglyceride level (rho = −0.32, p = 0.024) fasting blood insulin (rho = −0.43, p = 0.0024), HOMA-IR (rho = −0.39, p = 0.007) and PFV (rho = −0.52, p = 0.0001). MBF response to adenosine was only correlated with PFV (rho = −0.32, p = 0.026). On multivariate regression analysis PFV emerged as the only significant predictor of MBF response to CPT (p = 0.002).Conclusion: PFV is significantly correlated with endothelium-dependent coronary vasomotion. High PF burden might negatively influence MBF response to CPT, as well as to adenosine stress, even in persons with normal hyperemic myocardial perfusion imaging, suggesting a link between PF and future cardiovascular events. While outside-to-inside adipokines secretion through the arterial wall has been described, our results might suggest an effect upon NO-dependent and -independent vasodilatation. Further studies are needed to elucidate this mechanism.

Benchmarking therapeutic drug monitoring software: A systematic evaluation of available computer tools

Objectives: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on blood concentrations measurement. Maintaining concentrations within a target range requires pharmacokinetic (PK) and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Methods: Literature and Internet were searched to identify software. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software characteristics. Numbers of drugs handled vary from 2 to more than 180, and integration of different population types is available for some programs. Nevertheless, 8 programs offer the ability to add new drug models based on population PK data. 10 computer tools incorporate Bayesian computation to predict dosage regimen (individual parameters are calculated based on population PK models). All of them are able to compute Bayesian a posteriori dosage adaptation based on a blood concentration while 9 are also able to suggest a priori dosage regimen, only based on individual patient covariates. Among those applying Bayesian analysis, MM-USC*PACK uses a non-parametric approach. The top 2 programs emerging from this benchmark are MwPharm and TCIWorks. Others programs evaluated have also a good potential but are less sophisticated or less user-friendly.¦Conclusions: Whereas 2 software packages are ranked at the top of the list, such complex tools would possibly not fit all institutions, and each program must be regarded with respect to individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Although interest in TDM tools is growing and efforts were put into it in the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capability of data storage and automated report generation.

Learning wind fields with multiple kernels

This paper presents multiple kernel learning (MKL) regression as an exploratory spatial data analysis and modelling tool. The MKL approach is introduced as an extension of support vector regression, where MKL uses dedicated kernels to divide a given task into sub-problems and to treat them separately in an effective way. It provides better interpretability to non-linear robust kernel regression at the cost of a more complex numerical optimization. In particular, we investigate the use of MKL as a tool that allows us to avoid using ad-hoc topographic indices as covariables in statistical models in complex terrains. Instead, MKL learns these relationships from the data in a non-parametric fashion. A study on data simulated from real terrain features confirms the ability of MKL to enhance the interpretability of data-driven models and to aid feature selection without degrading predictive performances. Here we examine the stability of the MKL algorithm with respect to the number of training data samples and to the presence of noise. The results of a real case study are also presented, where MKL is able to exploit a large set of terrain features computed at multiple spatial scales, when predicting mean wind speed in an Alpine region.

How single-trial electrical neuroimaging contributes to multisensory research.

This study details a method to statistically determine, on a millisecond scale and for individual subjects, those brain areas whose activity differs between experimental conditions, using single-trial scalp-recorded EEG data. To do this, we non-invasively estimated local field potentials (LFPs) using the ELECTRA distributed inverse solution and applied non-parametric statistical tests at each brain voxel and for each time point. This yields a spatio-temporal activation pattern of differential brain responses. The method is illustrated here in the analysis of auditory-somatosensory (AS) multisensory interactions in four subjects. Differential multisensory responses were temporally and spatially consistent across individuals, with onset at approximately 50 ms and superposition within areas of the posterior superior temporal cortex that have traditionally been considered auditory in their function. The close agreement of these results with previous investigations of AS multisensory interactions suggests that the present approach constitutes a reliable method for studying multisensory processing with the temporal and spatial resolution required to elucidate several existing questions in this field. In particular, the present analyses permit a more direct comparison between human and animal studies of multisensory interactions and can be extended to examine correlation between electrophysiological phenomena and behavior.

An active contour-based atlas registration model applied to automatic subthalamic nucleus targeting on MRI: method and validation.

This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

Contribution of genome-wide significant single-nucleotide polymorphisms and antiretroviral therapy to dyslipidemia in HIV-infected individuals: a longitudinal study.

BACKGROUND: HIV-infected individuals have an increased risk of myocardial infarction. Antiretroviral therapy (ART) is regarded as a major determinant of dyslipidemia in HIV-infected individuals. Previous genetic studies have been limited by the validity of the single-nucleotide polymorphisms (SNPs) interrogated and by cross-sectional design. Recent genome-wide association studies have reliably associated common SNPs to dyslipidemia in the general population. METHODS AND RESULTS: We validated the contribution of 42 SNPs (33 identified in genome-wide association studies and 9 previously reported SNPs not included in genome-wide association study chips) and of longitudinally measured key nongenetic variables (ART, underlying conditions, sex, age, ethnicity, and HIV disease parameters) to dyslipidemia in 745 HIV-infected study participants (n=34 565 lipid measurements; median follow-up, 7.6 years). The relative impact of SNPs and ART to lipid variation in the study population and their cumulative influence on sustained dyslipidemia at the level of the individual were calculated. SNPs were associated with lipid changes consistent with genome-wide association study estimates. SNPs explained up to 7.6% (non-high-density lipoprotein cholesterol), 6.2% (high-density lipoprotein cholesterol), and 6.8% (triglycerides) of lipid variation; ART explained 3.9% (non-high-density lipoprotein cholesterol), 1.5% (high-density lipoprotein cholesterol), and 6.2% (triglycerides). An individual with the most dyslipidemic antiretroviral and genetic background had an approximately 3- to 5-fold increased risk of sustained dyslipidemia compared with an individual with the least dyslipidemic therapy and genetic background. CONCLUSIONS: In the HIV-infected population treated with ART, the weight of the contribution of common SNPs and ART to dyslipidemia was similar. When selecting an ART regimen, genetic information should be considered in addition to the dyslipidemic effects of ART agents.

Is it appropriate to index glomerular filtration rate for body surface area

Purpose: Obesity is an established independent risk factor for chronic kidney disease. Thus, measurement of glomerular filtration rate (GFR) is important in this population. Traditionally, GFR has been indexed for body surface area (BSA), but this indexation may not be appropriate in obese individuals. Therefore, the objective of the study was to compare absolute GFR with GFR indexed for BSA and with GFR indexed for height. Methods and materials: The study was conducted in 66 families from the Seychelles islands that included several members with hypertension. GFR and effective renal plasma flow (ERPF) were measured using inulin and PAH clearances, respectively. Antihypertensive treatment, if used, was withheld 2 weeks before conducting the clearances. Participants with diabetes mellitus were excluded from the analysis. BSA was calculated using the Dubois formula. We assessed trend across BMI categories using a non parametric test. Results: Participants included 174 women and 127 men. The prevalence of hypertension was 61%, of which 68% were treated. The table shows that absolute GFR, GFR indexed for height, ERPF, filtration fraction were significantly higher across BMI categories. When GFR was indexed for BSA, the association between GFR and BMI categories was lost. Conclusion: Indexing GFR for BSA in overweight and obese individuals leads to a substantial underestimation of GFR. Filtration fraction, which does not depend on BSA, is higher in obese individuals, which suggests glomerular hyperfiltration. Indexing GFR for BSA therefore would mask the underlying glomerular hyperfiltration. As the number of nephrons does not increase with weight gain, absolute GFR represents a better marker of single nephron GFR and is more appropriate.

Frequency and chronology of extraintestinal manifestations in the Swiss Inflammatory Bowel Disease Cohort

Background: Data on the frequency of extraintestinal manifestations (EIM) in inflammatory bowel disease (IBD) is scarce, especially the one evaluating the time of occurrence of the EIM relative to IBD diagnosis. Aim: To assess the type and frequency of EIM in IBD patients and to evaluate when EIMs occur relative to IBD diagnosis. Methods: Analysis of data from the Swiss Inflammatory Bowel Disease Cohort (SIBDCS) which collects data on a large sample of IBD patients from hospitals and private practices across Switzerland starting in 2005. While parametric data are shown as mean ± SD, non-parametric data are presented as median and interquartile range (IQR). Results: A total of 1143 patients were analyzed (572 (50%) female, mean age 42.1 ± 14.4 years): 629 (55%) with Crohn's disease (CD), 501 (44%) with ulcerative colitis (UC), and 13 (1%) with indeterminate colitis (IC). Of 1143 patients, 374 (32.7%) presented with EIM (65% with CD, 33% with UC, 2% with IC). Of those patients suffering from EIMs, 37.4% presented with one, 41.7% with two, 12.4% with three, 5.3% with four, and 3.2% with five EIM during their lifetime. The IBD patients initially presented with the following EIMs: peripheral arthritis (PA) 63.4%, ankylosing spondylitis (AS) 8.1%, primary sclerosing cholangitis (PSC) 6.0%, uveitis 5.7%, oral aphthosis 5.7%, erythema nodosum (EN) 5.0%, pyoderma gangrenosum 1.8%, psoriasis 0.7%. While 92.9% of EIM occurred once IBD diagnosis was established (median 72 months, IQR 9-147 months, p < 0.001), 7.1% of EIMs preceded IBD diagnosis (median time 28 months before IBD diagnosis, IQR 7-60 months). Over a course of a lifetime, IBD patients presented with the following EIM (total exceeds 100 due to potential presence of multiple EIM): peripheral arthritis 69.3%, oral aphthosis 23%, ankylosing spondylitis 19.4%, uveitis 15.5%, erythema nodosum 14.5%, PSC 7.8%, pyoderma gangrenosum 6%, psoriasis 2.8%. Conclusion: EIMs frequently occur in a lifetime of IBD patients. The vast majority of patients present with EIMs once IBD diagnosis has been established. IBD patients most often present with peripheral arthritis, ankylosing spondylitis and PSC as their first EIM. However, peripheral arthritis, oral aphthosis, and ankylosing spondylitis are the most common EIMs in a lifetime of IBD patients.

Impact of videogame playing on glucose metabolism in children with type 1 diabetes.

Phan-Hug F, Thurneysen E, Theintz G, Ruffieux C, Grouzmann E. Impact of videogame playing on glucose metabolism in children with type 1 diabetes. Time spent playing videogames (VG) occupies a continually increasing part of children's leisure time. They can generate an important state of excitation, representing a form of mental and physical stress. This pilot study aimed to assess whether VG influences glycemic balance in children with type 1 diabetes. Twelve children with type 1 diabetes were subjected to two distinct tests at a few weeks interval: (i) a 60-min VG session followed by a 60-min rest period and (ii) a 60-min reading session followed by a 60-min rest period. Heart rate, blood pressure, glycemia, epinephrine (E), norepinephrine (NE), cortisol (F), and growth hormone (GH) were measured at 30 min intervals from -60 to +120 min. Non-parametric Wilcoxon tests for paired data were performed on Δ-values computed from baseline (0 min). Rise in heart rate (p = 0.05) and NE increase (p = 0.03) were shown to be significantly higher during the VG session when compared to the reading session and a significant difference of Δ-glycemic values was measured between the respective rest periods. This pilot study suggests that VG playing could induce a state of excitation sufficient to activate the sympathetic system and alter the course of glycemia. Dietary and insulin dose recommendations may be needed to better control glycemic excursion in children playing VG.

Prevalence of cognitive disorders in HIV plus patients with long-term suppression of viremia

Background: HAART has contributed to decrease the HIV-related mortality and morbidity. However, the prevalence of HIV-associated neurocognitive disorders (HAND) seems to have increased. The aim of this study was to determine the prevalence of cognitive complaint and of HAND in a cohort of aviremic HIV_patients in the South-western part of Switzerland. Design/Methods: Two hundred HIV_ patients who had (1) undetectable HIV RNA concentrations in the plasma for_3 months, (2) no history of major opportunistic infection of the CNS in the past three years, (3) no current use of IV drugs and (4) no signs of major depression according to the DSM-IV criteria, answered a questionnaire designed to elicit cognitive complaints. Cognitive functions of a subset of HIV_ patients with or without cognitive complaints were assessed using the HIV Dementia scale (HDS) and a battery of neuropsychological tests evaluating the sub-cortical functions. Cognitive impairment was defined according to the revised diagnostic criteria for HAND. Non-parametric tests were used for statistics and a Bonferroni corrected standard p level of pB0.002 was applied for multiple comparisons. Results: The prevalence of cognitive complaints was 27% (54 patients) among the 200 questioned patients. At the time of writing this abstract, cognitive functions of 50 complaining and 28 noncomplaining aviremic patients had been assessed with the HDS and the full neuropsychological battery. The prevalence of HAND producing at least mild interference in daily functioning (mild neurocognitive disorders [MND] or HIV-associated dementia [HAD]) was 44% (34/78 patients) in the group who underwent neuropsychological testing. Objective evidences of HAND were more frequent in complaining than in non-complaining patients (pB0.001). Using a ROC curve, a cut-off of 13 on the HDS was found to have a sensitivity of 74% and a specificity of 71% (p_0.001) for the diagnosis of HAND. A trend for lower CNS Penetrating-Effectiveness scores for HAART in patients with MND or HAD as compared to the others was present (1.59 0.6 vs. 1.990.6; p_0.006 [Bonferroni correction]). Conclusions/Relevance: So far, our results suggest that (1) the prevalence of HAND is high in HIV_ patients with a long-term suppression of viremia, and (2) cognitive complaints expressed by aviremic HIV_ patients should be carefully investigated as they correlate with objective evidences of cognitive decline in a neuropsychological testing. HAART with a high CNS penetrating-effectiveness may contribute to prevent HAND. Funding: Swiss HIV Cohort Study.

Long-term changes in rice development in Southern Brazil, during the last ten decades

The objective of this work was to test long-term trends in the duration of rice development phases in Santa Maria, RS, Brazil. The duration from emergence to V3 (EM-V3), emergence to panicle differentiation (EM-R1), emergence to anthesis (EM-R4), and emergence to all grains with brown hull (EM-R9) was calculated using leaf appearance and developmental models for four rice cultivars (IRGA 421, IRGA 417, EPAGRI 109, and EEA 406), for the period from 1912 to 2011, considering three emergence dates (early, mid, and late). The trend of the time series was tested with the non-parametric Mann-Kendall test, and the magnitude of the trend was estimated with simple linear regression. Rice development has changed over the last ten decades in this location, leading to an anticipation of harvest time of 17 to 31 days, depending on the cultivar maturity group and emergence date, which is related to trends of temperature increase during the growing season. Warmer temperatures over the evaluated time period are responsible for changing rice phenology in this location, since minimum and maximum daily temperature drive the rice developmental models used.

Obesity-related phenotypes are associated to parental longevity in a Swiss population-based study

METHODS. We analyzed data from a population-based sample of 2561 participants (1163 men and 1398 women) aged 55-75 years from the city of Lausanne, Switzerland (CoLaus study). Participants were stratified by the number of parents (0, 1, 2) who survived to 85 years or more. Trend across these strata was assessed using a non-parametric kmean test. The associations of parental age (independent covariate used as a proxy for longevity) with fasting blood glucose, blood pressures, blood lipids, body mass index (BMI), weight, height or liver enzymes (continuous dependent variables) were analyzed using multiple linear regressions. Models were adjusted for age, sex, alcohol consumption, smoking and educational level, and BMI for liver enzymes. RESULTS. For subjects with 0 (N = 1298), 1 (N = 991) and 2 (N = 272) long-lived parents, median BMI (interquartile range) was 25.4 (6.5), 24.9 (6.1) and 23.7 (4.8) kg/m2 in women (P <0.001), and 27.3 (4.8), 27.0 (4.5) and 25.9 (4.9) kg/m2 in men (P = 0.04), respectively; median weight was 66.5 (16.1), 65.0 (16.4) and 63.4 (13.7) kg in women (P = 0.003), and 81.5 (17.0), 81.4 (16.4) and 80.3 (17.1) kg in men (P = 0.36). Median height was 161 (8), 162 (9) and 163 (8) cm in women (P = 0.005) and 173 (9), 174 (9) and 174 (11) cm in men (P = 0.09). The corresponding medians for AST (Aspartate Aminotransferase) were 31 (13), 29 (11) and 28 (10) U/L (P = 0.002), and 28 (17), 27 (14) and 26 (19) U/L for ALT (Alanin Aminotransferase, P = 0.053) in men. In multivariable analyses, greater parental longevity was associated with lower BMI, lower weight and taller stature in women (P < 0.01) and lower AST in men (P = 0.011). No significant associations were observed for the other variables analyzed. Sensitivity analyses restricted to subjects whose parents were dead (N = 1844) led to similar results, with even stronger associations of parental longevity with liver enzymes in men. CONCLUSIONS. In women, increased parental longevity was associated with smaller BMI, attributable to lower weight and taller stature. In men, the association of increased parental longevity with lower liver enzymes, independently of BMI, suggests that parental longevity may be associated with decreased nonalcoholic fatty liver disease.