Effect of once-yearly zoledronic acid on the spine and hip as measured by quantitative computed tomography: results of the HORIZON Pivotal Fracture Trial.

Changes in bone mineral density and bone strength following treatment with zoledronic acid (ZOL) were measured by quantitative computed analysis (QCT) or dual-energy X-ray absorptiometry (DXA). ZOL treatment increased spine and hip BMD vs placebo, assessed by QCT and DXA. Changes in trabecular bone resulted in increased bone strength. INTRODUCTION: To investigate bone mineral density (BMD) changes in trabecular and cortical bone, estimated by quantitative computed analysis (QCT) or dual-energy X-ray absorptiometry (DXA), and whether zoledronic acid 5 mg (ZOL) affects bone strength. METHODS: In 233 women from a randomized, controlled trial of once-yearly ZOL, lumbar spine, total hip, femoral neck, and trochanter were assessed by DXA and QCT (baseline, Month 36). Mean percentage changes from baseline and between-treatment differences (ZOL vs placebo, t-test) were evaluated. RESULTS: Mean between-treatment differences for lumbar spine BMD were significant by DXA (7.0%, p < 0.01) and QCT (5.7%, p < 0.0001). Between-treatment differences were significant for trabecular spine (p = 0.0017) [non-parametric test], trabecular trochanter (10.7%, p < 0.0001), total hip (10.8%, p < 0.0001), and compressive strength indices at femoral neck (8.6%, p = 0.0001), and trochanter (14.1%, p < 0.0001). CONCLUSIONS: Once-yearly ZOL increased hip and spine BMD vs placebo, assessed by QCT vs DXA. Changes in trabecular bone resulted in increased indices of compressive strength.

The Dyadic and Triadic Therapeutic Alliance in Cross-cultural Health Care: The case of Hispanic American Patients

This research project conducted in the Psychology Department of the University of Lausanne (Switzerland) evaluated the therapeutic alliance with Hispanic American Patients. From the patient's perspective, the therapeutic alliance was explored in two types of frameworks: the dyadic and the triadic setting. The dyadic setting is the encounter between a therapist (health professional) and a patient who ideally share the same language. The triadic setting is the encounter of a therapist and a patient who speak different languages, but are able to interact using the help of an interpreter. My specific interest focuses on studying the therapeutic alliance in a cross- cultural setting through a mixed methodology. As part of the quantitative phase, non- parametric tests were used to analyze 55 questionnaires of the Therapeutic Alliance for Migrants - Health Professionals' version (QALM-PS). For the qualitative phase, a thematic analysis was used to analyze 20 transcript interviews. While no differences were found concerning the strength of the therapeutic alliance between the triadic and dyadic settings, results showed that the factors that enrich the therapeutic alliance with migrant patients depend more on an emotional alliance (bond) than on a rational alliance (agreements). Indeed, the positive relationship with the interpreter, and especially with the therapist, relies considerably on human qualities and moral values, bringing the conception of humanity as an important need when meeting foreign patients in health care settings. In addition, the quality of communication, which could be attributed to the type of interpreter in the triadic setting, plays an important role in the establishment of a positive therapeutic relationship. Ce projet de recherche mené au Département de psychologie de l'Université de Lausanne (Suisse) a évalué l'alliance thérapeutique avec les patients hispano-américains. Du point de vue du patient, l'alliance thérapeutique a été étudiée dans deux types de dispositifs: le cadre dyadique et triadique. Le cadre dyadique est la rencontre d'un thérapeute (professionnel de la santé) et d'un patient qui, idéalement, partagent la même langue. Le cadre triadique est la rencontre d'un thérapeute et d'un patient qui parlent différentes langues, mais sont capables d'interagir grâce à l'aide d'un interprète. Mon intérêt porte en particulier sur l'étude de l'alliance thérapeutique dans un cadre interculturel au travers d'une méthodologie mixte. Dans la phase quantitative, des tests non paramétriques ont été utilisés pour les analyses des 55 questionnaires de l'alliance thérapeutique pour les migrants, version - professionnels de la santé (QALM-PS). Pour la phase qualitative, une analyse thématique a été utilisée pour l'analyse des 20 entretiens transcrits. Bien qu'aucune différence n'a été constatée en ce qui concerne la force de l'alliance thérapeutique entre les cadres dyadiques et triadiques, les résultats montrent que les facteurs qui enrichissent l'alliance thérapeutique avec les patients migrants dépendent plus de l'alliance émotionnelle (lien) que sur une alliance rationnelle (accords). En effet, la relation positive avec l'interprète, et en particulier avec le thérapeute, repose en grande partie sur des qualités humaines et des valeurs morales, ce qui porte la conception de l'humanité comme un besoin important lors de la rencontre des patients étrangers dans un cadre de santé. En outre, la qualité de la communication, qui pourrait être attribuée au type d'interprète dans le cadre triadique, joue un rôle important dans l'établissement d'une relation thérapeutique positive.

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.

Rapid fluidic exchange microsystem for recording of fast ion channel kinetics in Xenopus oocytes.

We present a new lab-on-a-chip system for electrophysiological measurements on Xenopus oocytes. Xenopus oocytes are widely used host cells in the field of pharmacological studies and drug development. We developed a novel non-invasive technique using immobilized non-devitellinized cells that replaces the traditional "two-electrode voltage-clamp" (TEVC) method. In particular, rapid fluidic exchange was implemented on-chip to allow recording of fast kinetic events of exogenous ion channels expressed in the cell membrane. Reducing fluidic exchange times of extracellular reagent solutions is a great challenge with these large millimetre-sized cells. Fluidic switching is obtained by shifting the laminar flow interface in a perfusion channel under the cell by means of integrated poly-dimethylsiloxane (PDMS) microvalves. Reagent solution exchange times down to 20 ms have been achieved. An on-chip purging system allows to perform complex pharmacological protocols, making the system suitable for screening of ion channel ligand libraries. The performance of the integrated rapid fluidic exchange system was demonstrated by investigating the self-inhibition of human epithelial sodium channels (ENaC). Our results show that the response time of this ion channel to a specific reactant is about an order of magnitude faster than could be estimated with the traditional TEVC technique.

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.

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

A comparison of mean phase difference and generalized least squares for analyzing single-case data

The present study focuses on single-case data analysis and specifically on two procedures for quantifying differences between baseline and treatment measurements The first technique tested is based on generalized least squares regression analysis and is compared to a proposed non-regression technique, which allows obtaining similar information. The comparison is carried out in the context of generated data representing a variety of patterns (i.e., independent measurements, different serial dependence underlying processes, constant or phase-specific autocorrelation and data variability, different types of trend, and slope and level change). The results suggest that the two techniques perform adequately for a wide range of conditions and researchers can use both of them with certain guarantees. The regression-based procedure offers more efficient estimates, whereas the proposed non-regression procedure is more sensitive to intervention effects. Considering current and previous findings, some tentative recommendations are offered to applied researchers in order to help choosing among the plurality of single-case data analysis techniques.

A multicentre, retrospective case-control study assessing the role of trabecular bone score (TBS) in menopausal Caucasian women with low areal bone mineral density (BMDa): Analysing the odds of vertebral fracture.

INTRODUCTION: The trabecular bone score (TBS) is a new parameter that is determined from grey level analysis of DXA images. It relies on the mean thickness and volume fraction of trabecular bone microarchitecture. This was a preliminary case-control study to evaluate the potential diagnostic value of TBS, both alone and combined with bone mineral density (BMDa), in the assessment of vertebral fracture. METHODS: Out of a subject pool of 441 Caucasian, postmenopausal women between the ages of 50 and 80 years, we identified 42 women with osteoporosis-related vertebral fractures, and compared them with 126 age-matched women without any fractures (1 case: 3 controls). Primary outcomes were BMDa and TBS. Inter-group comparisons were undertaken using Student's t-tests and Wilcoxon signed ranks tests for parametric and non-parametric data, respectively. Odds ratios for vertebral fracture were calculated for each incremental one standard deviation decrease in BMDa and TBS, and areas under the receiver operating curve (AUC) calculated and sensitivity analysis were conducted to compare BMDa alone, TBS alone, and the combination of BMDa and TBS. Subgroup analyses were performed specifically for women with osteopenia, and for women with T-score-defined osteoporosis. RESULTS: Across all subjects (n=42, 126) weight and body mass index were greater and BMDa and TBS both less in women with fractures. The odds of vertebral fracture were 3.20 (95% CI, 2.01-5.08) for each incremental decrease in TBS, 1.95 (1.34-2.84) for BMDa, and 3.62 (2.32-5.65) for BMDa + TBS combined. The AUC was greater for TBS than for BMDa (0.746 vs. 0.662, p=0.011). At iso-specificity (61.9%) or iso-sensitivity (61.9%) for both BMDa and TBS, TBS + BMDa sensitivity or specificity was 19.1% or 16.7% greater than for either BMDa or TBS alone. Among subjects with osteoporosis (n=11, 40) both BMDa (p=0.0008) and TBS (p=0.0001) were lower in subjects with fractures, and both OR and AUC (p=0.013) for BMDa + TBS were greater than for BMDa alone (OR=4.04 [2.35-6.92] vs. 2.43 [1.49-3.95]; AUC=0.835 [0.755-0.897] vs. 0.718 [0.627-0.797], p=0.013). Among subjects with osteopenia, TBS was lower in women with fractures (p=0.0296), but BMDa was not (p=0.75). Similarly, the OR for TBS was statistically greater than 1.00 (2.82, 1.27-6.26), but not for BMDa (1.12, 0.56-2.22), as was the AUC (p=0.035), but there was no statistical difference in specificity (p=0.357) or sensitivity (p=0.678). CONCLUSIONS: The trabecular bone score warrants further study as to whether it has any clinical application in osteoporosis detection and the evaluation of fracture risk.

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.

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.