Laboratory-based versus non-laboratory-based CVD risk analysis.

Commentaire de: Gaziano TA, Young CR, Fitzmaurice G, Atwood S, Gaziano JM. Laboratory-based versus non-laboratory-based method for assessment of cardiovascular disease risk: the NHANES I Follow-up Study cohort. Lancet. 2008;371(9616):923-31. PMID: 18342687

Test of four colon cancer risk-scores in formalin fixed paraffin embedded microarray gene expression data.

BACKGROUND: Prognosis prediction for resected primary colon cancer is based on the T-stage Node Metastasis (TNM) staging system. We investigated if four well-documented gene expression risk scores can improve patient stratification. METHODS: Microarray-based versions of risk-scores were applied to a large independent cohort of 688 stage II/III tumors from the PETACC-3 trial. Prognostic value for relapse-free survival (RFS), survival after relapse (SAR), and overall survival (OS) was assessed by regression analysis. To assess improvement over a reference, prognostic model was assessed with the area under curve (AUC) of receiver operating characteristic (ROC) curves. All statistical tests were two-sided, except the AUC increase. RESULTS: All four risk scores (RSs) showed a statistically significant association (single-test, P < .0167) with OS or RFS in univariate models, but with HRs below 1.38 per interquartile range. Three scores were predictors of shorter RFS, one of shorter SAR. Each RS could only marginally improve an RFS or OS model with the known factors T-stage, N-stage, and microsatellite instability (MSI) status (AUC gains < 0.025 units). The pairwise interscore discordance was never high (maximal Spearman correlation = 0.563) A combined score showed a trend to higher prognostic value and higher AUC increase for OS (HR = 1.74, 95% confidence interval [CI] = 1.44 to 2.10, P < .001, AUC from 0.6918 to 0.7321) and RFS (HR = 1.56, 95% CI = 1.33 to 1.84, P < .001, AUC from 0.6723 to 0.6945) than any single score. CONCLUSIONS: The four tested gene expression-based risk scores provide prognostic information but contribute only marginally to improving models based on established risk factors. A combination of the risk scores might provide more robust information. Predictors of RFS and SAR might need to be different.

The Sequential Organ Failure Assessment score and copeptin for predicting survival in ventilator-associated pneumonia.

INTRODUCTION: Ventilator-associated pneumonia remains the most common nosocomial infection in the critically ill and contributes to significant morbidity. Eventual decisions regarding withdrawal or maximal therapy are demanding and rely on physicians' experience. Additional objective tools for risk assessment may improve medical judgement. Copeptin, reflecting vasopressin release, as well as the Sequential Organ Failure Assessment (SOFA) score, reflecting the individual degree of organ dysfunction, might qualify for survival prediction in ventilator-associated pneumonia. We investigated the predictive value of the SOFA score and copeptin in ventilator-associated pneumonia. METHODS: One hundred one patients with ventilator-associated pneumonia were prospectively assessed. Death within 28 days after ventilator-associated pneumonia onset was the primary end point. RESULTS: The SOFA score and the copeptin levels at ventilator-associated pneumonia onset were significantly elevated in nonsurvivors (P = .002 and P = .017, respectively). Both markers had different time courses in survivors and nonsurvivors (P < .001 and P = .006). Mean SOFA (average SOFA of 10 days after VAP onset) was superior in predicting 28-day survival as compared with SOFA and copeptin at ventilator-associated pneumonia onset (area under the curve, 0.90 vs 0.73 and 0.67, respectively). CONCLUSIONS: The predictive value of serial-measured SOFA significantly exceeds those of single SOFA and copeptin measurements. Serial SOFA scores accurately predict outcome in ventilator-associated pneumonia.

Osteoporotic fracture risk in elderly women: estimation with quantitative heel US and clinical risk factors

PURPOSE: To derive a prediction rule by using prospectively obtained clinical and bone ultrasonographic (US) data to identify elderly women at risk for osteoporotic fractures. MATERIALS AND METHODS: The study was approved by the Swiss Ethics Committee. A prediction rule was computed by using data from a 3-year prospective multicenter study to assess the predictive value of heel-bone quantitative US in 6174 Swiss women aged 70-85 years. A quantitative US device to calculate the stiffness index at the heel was used. Baseline characteristics, known risk factors for osteoporosis and fall, and the quantitative US stiffness index were used to elaborate a predictive rule for osteoporotic fracture. Predictive values were determined by using a univariate Cox model and were adjusted with multivariate analysis. RESULTS: There were five risk factors for the incidence of osteoporotic fracture: older age (>75 years) (P < .001), low heel quantitative US stiffness index (<78%) (P < .001), history of fracture (P = .001), recent fall (P = .001), and a failed chair test (P = .029). The score points assigned to these risk factors were as follows: age, 2 (3 if age > 80 years); low quantitative US stiffness index, 5 (7.5 if stiffness index < 60%); history of fracture, 1; recent fall, 1.5; and failed chair test, 1. The cutoff value to obtain a high sensitivity (90%) was 4.5. With this cutoff, 1464 women were at lower risk (score, <4.5) and 4710 were at higher risk (score, >or=4.5) for fracture. Among the higher-risk women, 6.1% had an osteoporotic fracture, versus 1.8% of women at lower risk. Among the women who had a hip fracture, 90% were in the higher-risk group. CONCLUSION: A prediction rule obtained by using quantitative US stiffness index and four clinical risk factors helped discriminate, with high sensitivity, women at higher versus those at lower risk for osteoporotic fracture.

Interét et limites de l'evaluation du risque de récidive d'actes illégaux dans les expertises psychiatriques [Benefits and limitation of the assessment of second offense risk in psychiatric expertise].

The legislatives evolutions imply an important recourse to the psychiatric expertise in order to evaluate the potential dangerousness of a subject. However, in spite of the development of techniques and tools for this evaluation, the dangerousness assessment of a subject is in practice extremely complex and discussed in the scientific literature. The evolution of the concept of dangerousness to the risk assessment involved a technicisation of this evaluation which should not make forget the limits of these tools and the need for restoring the subject, the meaning and the clinic in this evaluation.

Improvement of cardiovascular risk prediction: time to review current knowledge, debates, and fundamentals on how to assess test characteristics.

Cardiovascular risk assessment might be improved with the addition of emerging, new tests derived from atherosclerosis imaging, laboratory tests or functional tests. This article reviews relative risk, odds ratios, receiver-operating curves, posttest risk calculations based on likelihood ratios, the net reclassification improvement and integrated discrimination. This serves to determine whether a new test has an added clinical value on top of conventional risk testing and how this can be verified statistically. Two clinically meaningful examples serve to illustrate novel approaches. This work serves as a review and basic work for the development of new guidelines on cardiovascular risk prediction, taking into account emerging tests, to be proposed by members of the 'Taskforce on Vascular Risk Prediction' under the auspices of the Working Group 'Swiss Atherosclerosis' of the Swiss Society of Cardiology in the future.

Predictive accuracy of original and recalibrated Framingham risk score in the Swiss population.

OBJECTIVE: To compare the predictive accuracy of the original and recalibrated Framingham risk function on current morbidity from coronary heart disease (CHD) and mortality data from the Swiss population. METHODS: Data from the CoLaus study, a cross-sectional, population-based study conducted between 2003 and 2006 on 5,773 participants aged 35-74 without CHD were used to recalibrate the Framingham risk function. The predicted number of events from each risk function were compared with those issued from local MONICA incidence rates and official mortality data from Switzerland. RESULTS: With the original risk function, 57.3%, 21.2%, 16.4% and 5.1% of men and 94.9%, 3.8%, 1.2% and 0.1% of women were at very low (<6%), low (6-10%), intermediate (10-20%) and high (>20%) risk, respectively. With the recalibrated risk function, the corresponding values were 84.7%, 10.3%, 4.3% and 0.6% in men and 99.5%, 0.4%, 0.0% and 0.1% in women, respectively. The number of CHD events over 10 years predicted by the original Framingham risk function was 2-3 fold higher than predicted by mortality+case fatality or by MONICA incidence rates (men: 191 vs. 92 and 51 events, respectively). The recalibrated risk function provided more reasonable estimates, albeit slightly overestimated (92 events, 5-95th percentile: 26-223 events); sensitivity analyses showed that the magnitude of the overestimation was between 0.4 and 2.2 in men, and 0.7 and 3.3 in women. CONCLUSION: The recalibrated Framingham risk function provides a reasonable alternative to assess CHD risk in men, but not in women.

Residual venous obstruction, alone and in combination with D-dimer, as a risk factor for recurrence after anticoagulation withdrawal following a first idiopathic deep vein thrombosis in the prolong study.

OBJECTIVE: This study aims to assess the predictive value of residual venous obstruction (RVO) for recurrent venous thrombo-embolism (VTE) in a study using D-dimer to predict outcome. DESIGN: This is a multicentre randomised open-label study. METHODS: Patients with a first episode of idiopathic VTE were enrolled on the day of anticoagulation discontinuation when RVO was determined by compression ultrasonography in those with proximal deep vein thrombosis (DVT) of the lower limbs. D-dimer was measured after 1 month. Patients with normal D-dimer did not resume anticoagulation while patients with abnormal D-dimer were randomised to resume anticoagulation or not. The primary outcome measure was recurrent VTE over an 18-month follow-up. RESULTS: A total of 490 DVT patients were analysed (after excluding 19 for different reasons and 118 for isolated pulmonary embolism (PE)). Recurrent DVT occurred in 19% (19/99) of patients with abnormal D-dimer who did not resume anticoagulation and 10% (31/310) in subjects with normal D-dimer (adjusted hazard ratio: 2.1; p = 0.02). Recurrences were similar in subjects either with (11%, 17/151) or without RVO (13%, 32/246). Recurrent DVT rates were also similar for normal D-dimer, with or without RVO, and for abnormal D-dimer, with or without RVO. CONCLUSIONS: Elevated D-dimer at 1 month after anticoagulation withdrawal is a risk factor for recurrence, while RVO at the time of anticoagulation withdrawal is not.

Cardiovascular Risk Prediction with Ultrasound

This paper addresses primary care physicians, cardiologists, internists, angiologists and doctors desirous of improving vascular risk prediction in primary care. Many cardiovascular risk factors act aggressively on the arterial wall and result in atherosclerosis and atherothrombosis. Cardiovascular prognosis derived from ultrasound imaging is, however, excellent in subjects without formation of intimal thickening or atheromas. Since ultrasound visualises the arterial wall directly, the information derived from the arterial wall may add independent incremental information to the knowledge of risk derived from global risk assessment. This paper provides an overview on plaque imaging for vascular risk prediction in two parts: Part 1: Carotid IMT is frequently used as a surrogate marker for outcome in intervention studies addressing rather large cohorts of subjects. Carotid IMT as a risk prediction tool for the prevention of acute myocardial infarction and stroke has been extensively studied in many patients since 1987, and has yielded incremental hazard ratios for these cardiovascular events independently of established cardiovascular risk factors. However, carotid IMT measurements are not used uniformly and therefore still lack widely accepted standardisation. Hence, at an individual, practicebased level, carotid IMT is not recommended as a risk assessment tool. The total plaque area of the carotid arteries (TPA) is a measure of the global plaque burden within both carotid arteries. It was recently shown in a large Norwegian cohort involving over 6000 subjects that TPA is a very good predictor for future myocardial infarction in women with an area under the curve (AUC) using a receiver operating curves (ROC) value of 0.73 (in men: 0.63). Further, the AUC for risk prediction is high both for vascular death in a vascular prevention clinic group (AUC 0.77) and fatal or nonfatal myocardial infarction in a true primary care group (AUC 0.79). Since TPA has acceptable reproducibility, allows calculation of posttest risk and is easily obtained at low cost, this risk assessment tool may come in for more widespread use in the future and also serve as a tool for atherosclerosis tracking and guidance for intensity of preventive therapy. However, more studies with TPA are needed. Part 2: Carotid and femoral plaque formation as detected by ultrasound offers a global view of the extent of atherosclerosis. Several prospective cohort studies have shown that cardiovascular risk prediction is greater for plaques than for carotid IMT. The number of arterial beds affected by significant atheromas may simply be added numerically to derive additional information on the risk of vascular events. A new atherosclerosis burden score (ABS) simply calculates the sum of carotid and femoral plaques encountered during ultrasound scanning. ABS correlates well and independently with the presence of coronary atherosclerosis and stenosis as measured by invasive coronary angiogram. However, the prognostic power of ABS as an independent marker of risk still needs to be elucidated in prospective studies. In summary, the large number of ways to measure atherosclerosis and related changes in human arteries by ultrasound indicates that this technology is not yet sufficiently perfected and needs more standardisation and workup on clearly defined outcome studies before it can be recommended as a practice-based additional risk modifier.

Defining risk thresholds for a 10-year probability of hip fracture model that combines clinical risk factors and quantitative ultrasound: results using the EPISEM cohort.

Using a large prospective cohort of over 12,000 women, we determined 2 thresholds (high risk and low risk of hip fracture) to use in a 10-yr hip fracture probability model that we had previously described, a model combining the heel stiffness index measured by quantitative ultrasound (QUS) and a set of easily determined clinical risk factors (CRFs). The model identified a higher percentage of women with fractures as high risk than a previously reported risk score that combined QUS and CRF. In addition, it categorized women in a way that was quite consistent with the categorization that occurred using dual X-ray absorptiometry (DXA) and the World Health Organization (WHO) classification system; the 2 methods identified similar percentages of women with and without fractures in each of their 3 categories, but the 2 identified only in part the same women. Nevertheless, combining our composite probability model with DXA in a case findings strategy will likely further improve the detection of women at high risk of fragility hip fracture. We conclude that the currently proposed model may be of some use as an alternative to the WHO classification criteria for osteoporosis, at least when access to DXA is limited.

Diabetes risk scores and death: predictability and practicability in two different populations.

The aim was to examine the capacity of commonly used type 2 diabetes mellitus (T2DM) risk scores to predict overall mortality. The US-based NHANES III (n = 3138; 982 deaths) and the Swiss-based CoLaus study (n = 3946; 191 deaths) were used. The predictive value of eight T2DM risk scores regarding overall mortality was tested. The Griffin score, based on few self-reported parameters, presented the best (NHANES III) and second best (CoLaus) predictive capacity. Generally, the predictive capacity of scores based on clinical (anthropometrics, lifestyle, history) and biological (blood parameters) data was not better than of scores based solely on clinical self-reported data. T2DM scores can be validly used to predict mortality risk in general populations without diabetes. Comparison with other scores could further show whether such scores also suit as a screening tool for quick overall health risk assessment.

Prospective validation of the Pulmonary Embolism Severity Index. A clinical prognostic model for pulmonary embolism

Practice guidelines recommend outpatient care for selected patients with non-massive pulmonary embolism (PE), but fail to specify how these low-risk patients should be identified. Using data from U.S. patients, we previously derived the Pulmonary Embolism Severity Index (PESI), a prediction rule that risk stratifies patients with PE. We sought to validate the PESI in a European patient cohort. We prospectively validated the PESI in patients with PE diagnosed at six emergency departments in three European countries. We used baseline data for the rule's 11 prognostic variables to stratify patients into five risk classes (I-V) of increasing probability of mortality. The outcome was overall mortality at 90 days after presentation. To assess the accuracy of the PESI to predict mortality, we estimated the sensitivity, specificity, and predictive values for low- (risk classes I/II) versus higher-risk patients (risk classes III-V), and the discriminatory power using the area under the receiver operating characteristic (ROC) curve. Among 357 patients with PE, overall mortality was 5.9%, ranging from 0% in class I to 17.9% in class V. The 186 (52%) low-risk patients had an overall mortality of 1.1% (95% confidence interval [CI]: 0.1-3.8%) compared to 11.1% (95% CI: 6.8-16.8%) in the 171 (48%) higher-risk patients. The PESI had a high sensitivity (91%, 95% CI: 71-97%) and a negative predictive value (99%, 95% CI: 96-100%) for predicting mortality. The area under the ROC curve was 0.78 (95% CI: 0.70-0.86). The PESI reliably identifies patients with PE who are at low risk of death and who are potential candidates for outpatient care. The PESI may help physicians make more rational decisions about hospitalization for patients with PE.

Species distribution models for conservation-oriented studies in Switzerland : filling data and tools gaps

SUMMARYSpecies distribution models (SDMs) represent nowadays an essential tool in the research fields of ecology and conservation biology. By combining observations of species occurrence or abundance with information on the environmental characteristic of the observation sites, they can provide information on the ecology of species, predict their distributions across the landscape or extrapolate them to other spatial or time frames. The advent of SDMs, supported by geographic information systems (GIS), new developments in statistical models and constantly increasing computational capacities, has revolutionized the way ecologists can comprehend species distributions in their environment. SDMs have brought the tool that allows describing species realized niches across a multivariate environmental space and predict their spatial distribution. Predictions, in the form of probabilistic maps showing the potential distribution of the species, are an irreplaceable mean to inform every single unit of a territory about its biodiversity potential. SDMs and the corresponding spatial predictions can be used to plan conservation actions for particular species, to design field surveys, to assess the risks related to the spread of invasive species, to select reserve locations and design reserve networks, and ultimately, to forecast distributional changes according to scenarios of climate and/or land use change.By assessing the effect of several factors on model performance and on the accuracy of spatial predictions, this thesis aims at improving techniques and data available for distribution modelling and at providing the best possible information to conservation managers to support their decisions and action plans for the conservation of biodiversity in Switzerland and beyond. Several monitoring programs have been put in place from the national to the global scale, and different sources of data now exist and start to be available to researchers who want to model species distribution. However, because of the lack of means, data are often not gathered at an appropriate resolution, are sampled only over limited areas, are not spatially explicit or do not provide a sound biological information. A typical example of this is data on 'habitat' (sensu biota). Even though this is essential information for an effective conservation planning, it often has to be approximated from land use, the closest available information. Moreover, data are often not sampled according to an established sampling design, which can lead to biased samples and consequently to spurious modelling results. Understanding the sources of variability linked to the different phases of the modelling process and their importance is crucial in order to evaluate the final distribution maps that are to be used for conservation purposes.The research presented in this thesis was essentially conducted within the framework of the Landspot Project, a project supported by the Swiss National Science Foundation. The main goal of the project was to assess the possible contribution of pre-modelled 'habitat' units to model the distribution of animal species, in particular butterfly species, across Switzerland. While pursuing this goal, different aspects of data quality, sampling design and modelling process were addressed and improved, and implications for conservation discussed. The main 'habitat' units considered in this thesis are grassland and forest communities of natural and anthropogenic origin as defined in the typology of habitats for Switzerland. These communities are mainly defined at the phytosociological level of the alliance. For the time being, no comprehensive map of such communities is available at the national scale and at fine resolution. As a first step, it was therefore necessary to create distribution models and maps for these communities across Switzerland and thus to gather and collect the necessary data. In order to reach this first objective, several new developments were necessary such as the definition of expert models, the classification of the Swiss territory in environmental domains, the design of an environmentally stratified sampling of the target vegetation units across Switzerland, the development of a database integrating a decision-support system assisting in the classification of the relevés, and the downscaling of the land use/cover data from 100 m to 25 m resolution.The main contributions of this thesis to the discipline of species distribution modelling (SDM) are assembled in four main scientific papers. In the first, published in Journal of Riogeography different issues related to the modelling process itself are investigated. First is assessed the effect of five different stepwise selection methods on model performance, stability and parsimony, using data of the forest inventory of State of Vaud. In the same paper are also assessed: the effect of weighting absences to ensure a prevalence of 0.5 prior to model calibration; the effect of limiting absences beyond the environmental envelope defined by presences; four different methods for incorporating spatial autocorrelation; and finally, the effect of integrating predictor interactions. Results allowed to specifically enhance the GRASP tool (Generalized Regression Analysis and Spatial Predictions) that now incorporates new selection methods and the possibility of dealing with interactions among predictors as well as spatial autocorrelation. The contribution of different sources of remotely sensed information to species distribution models was also assessed. The second paper (to be submitted) explores the combined effects of sample size and data post-stratification on the accuracy of models using data on grassland distribution across Switzerland collected within the framework of the Landspot project and supplemented with other important vegetation databases. For the stratification of the data, different spatial frameworks were compared. In particular, environmental stratification by Swiss Environmental Domains was compared to geographical stratification either by biogeographic regions or political states (cantons). The third paper (to be submitted) assesses the contribution of pre- modelled vegetation communities to the modelling of fauna. It is a two-steps approach that combines the disciplines of community ecology and spatial ecology and integrates their corresponding concepts of habitat. First are modelled vegetation communities per se and then these 'habitat' units are used in order to model animal species habitat. A case study is presented with grassland communities and butterfly species. Different ways of integrating vegetation information in the models of butterfly distribution were also evaluated. Finally, a glimpse to climate change is given in the fourth paper, recently published in Ecological Modelling. This paper proposes a conceptual framework for analysing range shifts, namely a catalogue of the possible patterns of change in the distribution of a species along elevational or other environmental gradients and an improved quantitative methodology to identify and objectively describe these patterns. The methodology was developed using data from the Swiss national common breeding bird survey and the article presents results concerning the observed shifts in the elevational distribution of breeding birds in Switzerland.The overall objective of this thesis is to improve species distribution models as potential inputs for different conservation tools (e.g. red lists, ecological networks, risk assessment of the spread of invasive species, vulnerability assessment in the context of climate change). While no conservation issues or tools are directly tested in this thesis, the importance of the proposed improvements made in species distribution modelling is discussed in the context of the selection of reserve networks.RESUMELes modèles de distribution d'espèces (SDMs) représentent aujourd'hui un outil essentiel dans les domaines de recherche de l'écologie et de la biologie de la conservation. En combinant les observations de la présence des espèces ou de leur abondance avec des informations sur les caractéristiques environnementales des sites d'observation, ces modèles peuvent fournir des informations sur l'écologie des espèces, prédire leur distribution à travers le paysage ou l'extrapoler dans l'espace et le temps. Le déploiement des SDMs, soutenu par les systèmes d'information géographique (SIG), les nouveaux développements dans les modèles statistiques, ainsi que la constante augmentation des capacités de calcul, a révolutionné la façon dont les écologistes peuvent comprendre la distribution des espèces dans leur environnement. Les SDMs ont apporté l'outil qui permet de décrire la niche réalisée des espèces dans un espace environnemental multivarié et prédire leur distribution spatiale. Les prédictions, sous forme de carte probabilistes montrant la distribution potentielle de l'espèce, sont un moyen irremplaçable d'informer chaque unité du territoire de sa biodiversité potentielle. Les SDMs et les prédictions spatiales correspondantes peuvent être utilisés pour planifier des mesures de conservation pour des espèces particulières, pour concevoir des plans d'échantillonnage, pour évaluer les risques liés à la propagation d'espèces envahissantes, pour choisir l'emplacement de réserves et les mettre en réseau, et finalement, pour prévoir les changements de répartition en fonction de scénarios de changement climatique et/ou d'utilisation du sol. En évaluant l'effet de plusieurs facteurs sur la performance des modèles et sur la précision des prédictions spatiales, cette thèse vise à améliorer les techniques et les données disponibles pour la modélisation de la distribution des espèces et à fournir la meilleure information possible aux gestionnaires pour appuyer leurs décisions et leurs plans d'action pour la conservation de la biodiversité en Suisse et au-delà. Plusieurs programmes de surveillance ont été mis en place de l'échelle nationale à l'échelle globale, et différentes sources de données sont désormais disponibles pour les chercheurs qui veulent modéliser la distribution des espèces. Toutefois, en raison du manque de moyens, les données sont souvent collectées à une résolution inappropriée, sont échantillonnées sur des zones limitées, ne sont pas spatialement explicites ou ne fournissent pas une information écologique suffisante. Un exemple typique est fourni par les données sur 'l'habitat' (sensu biota). Même s'il s'agit d'une information essentielle pour des mesures de conservation efficaces, elle est souvent approximée par l'utilisation du sol, l'information qui s'en approche le plus. En outre, les données ne sont souvent pas échantillonnées selon un plan d'échantillonnage établi, ce qui biaise les échantillons et par conséquent les résultats de la modélisation. Comprendre les sources de variabilité liées aux différentes phases du processus de modélisation s'avère crucial afin d'évaluer l'utilisation des cartes de distribution prédites à des fins de conservation.La recherche présentée dans cette thèse a été essentiellement menée dans le cadre du projet Landspot, un projet soutenu par le Fond National Suisse pour la Recherche. L'objectif principal de ce projet était d'évaluer la contribution d'unités 'd'habitat' pré-modélisées pour modéliser la répartition des espèces animales, notamment de papillons, à travers la Suisse. Tout en poursuivant cet objectif, différents aspects touchant à la qualité des données, au plan d'échantillonnage et au processus de modélisation sont abordés et améliorés, et leurs implications pour la conservation des espèces discutées. Les principaux 'habitats' considérés dans cette thèse sont des communautés de prairie et de forêt d'origine naturelle et anthropique telles que définies dans la typologie des habitats de Suisse. Ces communautés sont principalement définies au niveau phytosociologique de l'alliance. Pour l'instant aucune carte de la distribution de ces communautés n'est disponible à l'échelle nationale et à résolution fine. Dans un premier temps, il a donc été nécessaire de créer des modèles de distribution de ces communautés à travers la Suisse et par conséquent de recueillir les données nécessaires. Afin d'atteindre ce premier objectif, plusieurs nouveaux développements ont été nécessaires, tels que la définition de modèles experts, la classification du territoire suisse en domaines environnementaux, la conception d'un échantillonnage environnementalement stratifié des unités de végétation cibles dans toute la Suisse, la création d'une base de données intégrant un système d'aide à la décision pour la classification des relevés, et le « downscaling » des données de couverture du sol de 100 m à 25 m de résolution. Les principales contributions de cette thèse à la discipline de la modélisation de la distribution d'espèces (SDM) sont rassemblées dans quatre articles scientifiques. Dans le premier article, publié dans le Journal of Biogeography, différentes questions liées au processus de modélisation sont étudiées en utilisant les données de l'inventaire forestier de l'Etat de Vaud. Tout d'abord sont évalués les effets de cinq méthodes de sélection pas-à-pas sur la performance, la stabilité et la parcimonie des modèles. Dans le même article sont également évalués: l'effet de la pondération des absences afin d'assurer une prévalence de 0.5 lors de la calibration du modèle; l'effet de limiter les absences au-delà de l'enveloppe définie par les présences; quatre méthodes différentes pour l'intégration de l'autocorrélation spatiale; et enfin, l'effet de l'intégration d'interactions entre facteurs. Les résultats présentés dans cet article ont permis d'améliorer l'outil GRASP qui intègre désonnais de nouvelles méthodes de sélection et la possibilité de traiter les interactions entre variables explicatives, ainsi que l'autocorrélation spatiale. La contribution de différentes sources de données issues de la télédétection a également été évaluée. Le deuxième article (en voie de soumission) explore les effets combinés de la taille de l'échantillon et de la post-stratification sur le la précision des modèles. Les données utilisées ici sont celles concernant la répartition des prairies de Suisse recueillies dans le cadre du projet Landspot et complétées par d'autres sources. Pour la stratification des données, différents cadres spatiaux ont été comparés. En particulier, la stratification environnementale par les domaines environnementaux de Suisse a été comparée à la stratification géographique par les régions biogéographiques ou par les cantons. Le troisième article (en voie de soumission) évalue la contribution de communautés végétales pré-modélisées à la modélisation de la faune. C'est une approche en deux étapes qui combine les disciplines de l'écologie des communautés et de l'écologie spatiale en intégrant leurs concepts de 'habitat' respectifs. Les communautés végétales sont modélisées d'abord, puis ces unités de 'habitat' sont utilisées pour modéliser les espèces animales. Une étude de cas est présentée avec des communautés prairiales et des espèces de papillons. Différentes façons d'intégrer l'information sur la végétation dans les modèles de répartition des papillons sont évaluées. Enfin, un clin d'oeil aux changements climatiques dans le dernier article, publié dans Ecological Modelling. Cet article propose un cadre conceptuel pour l'analyse des changements dans la distribution des espèces qui comprend notamment un catalogue des différentes formes possibles de changement le long d'un gradient d'élévation ou autre gradient environnemental, et une méthode quantitative améliorée pour identifier et décrire ces déplacements. Cette méthodologie a été développée en utilisant des données issues du monitoring des oiseaux nicheurs répandus et l'article présente les résultats concernant les déplacements observés dans la distribution altitudinale des oiseaux nicheurs en Suisse.L'objectif général de cette thèse est d'améliorer les modèles de distribution des espèces en tant que source d'information possible pour les différents outils de conservation (par exemple, listes rouges, réseaux écologiques, évaluation des risques de propagation d'espèces envahissantes, évaluation de la vulnérabilité des espèces dans le contexte de changement climatique). Bien que ces questions de conservation ne soient pas directement testées dans cette thèse, l'importance des améliorations proposées pour la modélisation de la distribution des espèces est discutée à la fin de ce travail dans le contexte de la sélection de réseaux de réserves.

IRM cardiaque dans le suivi des cardiopathies congénitales à l'âge adulte [Cardiac MRI in the follow-up of adult congenital cardiomyopathy patients].

Magnetic resonance imaging is a rapidly developing modality in cardiology. It offers an excellent image definition and a large field of view, allowing a more accurate morphological assessment of cardiac malformations. Due to its unique versatility and its ability to provide myocardial tissue characterization, cardiac magnetic resonance (CMR) is now recognized as a central imaging modality for a wide range of congenital heart diseases, including assessment of post-surgical cardiac anatomy, quantification of valvular disease and detection of myocardial ischemia. CMR provides useful diagnostic information without any radiation exposure, and improves the global management of patients with congenital heart disease.

Obesity markers and estimated 10-year fatal cardiovascular risk in Switzerland.

BACKGROUND AND AIM: There is an ongoing debate on which obesity marker better predicts cardiovascular disease (CVD). In this study, the relationships between obesity markers and high (>5%) 10-year risk of fatal CVD were assessed. METHODS AND RESULTS: A cross-sectional study was conducted including 3047 women and 2689 men aged 35-75years. Body fat percentage was assessed by tetrapolar bioimpedance. CVD risk was assessed using the SCORE risk function and gender- and age-specific cut points for body fat were derived. The diagnostic accuracy of each obesity marker was evaluated through receiver operating characteristics (ROC) analysis. In men, body fat presented a higher correlation (r=0.31) with 10-year CVD risk than waist/hip ratio (WHR, r=0.22), waist (r=0.22) or BMI (r=0.19); the corresponding values in women were 0.18, 0.15, 0.11 and 0.05, respectively (all p<0.05). In both genders, body fat showed the highest area under the ROC curve (AUC): in men, the AUC (95% confidence interval) were 76.0 (73.8-78.2), 67.3 (64.6-69.9), 65.8 (63.1-68.5) and 60.6 (57.9-63.5) for body fat, WHR, waist and BMI, respectively. In women, the corresponding values were 72.3 (69.2-75.3), 66.6 (63.1-70.2), 64.1 (60.6-67.6) and 58.8 (55.2-62.4). The use of the body fat percentage criterion enabled the capture of three times more subjects with high CVD risk than the BMI criterion, and almost twice as much as the WHR criterion. CONCLUSION: Obesity defined by body fat percentage is more related with 10-year risk of fatal CVD than obesity markers based on WHR, waist or BMI.