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

PURPOSE. Longevity has been attributed to decreased cardiovascular mortality. Subjects with long-lived parents may represent a valuable group to study cardiovascular risk factors (CVRF) associated with longevity, possibly leading to new ways of preventing cardiovascular disease. Purpose: Longevity has been attributed to decreased cardiovascular mortality. Subjects with long-lived parents may represent a valuable group to study cardiovascular risk factors (CVRF) associated with longevity, possibly leading to new ways of preventing cardiovascular disease. 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. Conclusion: 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.

Neurally adjusted ventilatory assist can improve arterial oxygenation

INTRODUCTION. Neurally Adjusted Ventilatory Assist (NAVA) [1] is a new spontaneousassisted ventilatory mode which uses the diaphragmatic electrical activity (Eadi) to pilot the ventilator. Eadi is used to initiate the ventilator's pressurization and cycling off. Delivered inspiratory assistance is proportional to Eadi. NAVA can improve patient-ventilator synchrony [2] compared to pressure support (PS), but little is known about its effect on minute ventilation and oxygenation. OBJECTIVES. To compare the effects of NAVA and PS on minute ventilation and oxygenation and to analyze potential determinant factors for oxygenation. METHODS. Comparison between two 20-min periods under NAVA and PS. NAVA gain (proportionality factor between Eadi and delivered pressure) set as to obtain the same peak pressure as in PS. FIO2 and positive end-expiratory pressure (PEEP) were the same in NAVA and PS. Blood gas analyses were performed at the end of both recording periods. Statistical analysis: groups were compared with paired t tests or non parametric Wilcoxon signed-rank tests. p\0.05 was considered significant. RESULTS. [Mean ± SD]: 22 patients (age 66 ± 12 year, 7 M/15F, BMI 23.4 ± 3.1 kg/m2), 8 patients with COPD. Initial settings: PS 13 ± 3 cmH2O, PEEP 7 ± 2 cmH2O, NAVA gain 2.2 ± 1.8. Minute ventilation and PaCO2 were the same with both modes (p = 0.296 and 0.848, respectively). Tidal volume was lower with NAVA (427 ± 102 vs. 477 ± 102 ml, p\0.001). In contrast respiratory rate was higher with NAVA (25.6 ± 9.5 vs. 22.3 ± 8.9 cycles/min). Arterial oxygenation was improved with NAVA (PaO2 85.1 ± 28.9 vs. 75.8 ± 11.9 mmHg, p = 0.017, PaO2/FIO2 210 ± 53 vs. 195 ± 58 mmHg, p = 0.019). Neural inspiratory time (Tin) was comparable between NAVA and PS (p = 0.566). Among potential determinant factors for oxygenation, mean airway pressure (Pmean) was lower with NAVA (10.6 ± 2.6 vs. 11.1 ± 2.4 cmH2O, p = 0.006), as was the pressure time product (PTP) (6.8 ± 3.0 vs. 9.2 ± 3.5 cmH2O 9 s, p = 0.004). There were less asynchrony events with NAVA (2.3 ± 2.0 vs. 4.4 ± 3.8, p = 0.009).Tidal volume variability was higher with NAVA (variation coefficient: 30 ± 19.5 vs. 13.5 ± 8.6, p\0.001). Inspiratory time in excess (Tiex) was lower with NAVA (56 ± 23 vs. 202 ± 200 ms, p = 0.001). CONCLUSION. Despite lower Pmean and PTP in NAVA, arterial oxygenation was improved compared to PS. As asynchronies may be associated with an increased work of breathing and a higher oxygen consumption, their decrease in number with NAVA could be an explanation for oxygenation improvement. Another explanation could be the increase in VT variability. Further studies should now be performed to confirm the potential of NAVA in improving arterial oxygenation and explore the underlying mechanisms.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

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.

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.