Cross-Cultural Adaptation and Validation of the Spinal Function Sort (SFS) for French- and German-Speaking Patients with Back Complaints

Aim: Functional subjective evaluation through questionnaire is fundamental, but not often realized in patients with back complaints, notably because of lack of validated tools, in accordance with recognized psychometric criteria. The Spinal Function Sort (SFS), developed according to actual standards, was only validated in English. The aim of this study is to translate, adapt and validate the French and German version of the SFS.Method and material: The translation and cross-cultural adaptation were performed following the methodology proposed by the American Association of Orthopedist Surgeon. A total of 344 patients, presenting varied back complaints (especially degenerative and traumatic), took part in this study in a tertiary French- (n=87; mean age 44y; 17 women) and German-speaking (n=257; mean age 41y; 53 women) center. Test-retest reliability was quantified using the intraclass correlation coefficient (ICC) and construct validity was assessed by estimating the Pearson's correlation with the SF-36 physical and mental scales, the Visual Analogue Scale for Pain Intensity (VAS), and subscales of the Hospital Anxiety and Depression Scale (HADS).Results: Respectively for the French and German version, ICC were 0.98 and 0.94. Correlations 0.63 and 0.67 with the SF-36 Physical Functioning subscale; 0.60 and 0.52 with the SF-36 Physical Summary Scale ; -0.33 and -0.51 with the VAS ; -0.08 and 0.25 with the SF-36 Mental Health scale; 0.01 and 0.28 with the SF-36 Mental Summary Scale; -0.26 and -0.42 with the HADS depression; -0.17 and -0.45 with the HADS anxiety.Discussion: For both the French and German version of the SFS, the reliability was excellent. Convergent construct validity with SF-36 physical scales is good, moderated with the VAS. We find out a low correlation with SF-36 mental scales (divergent construct validity). We find out a low correlation with HADS subscales in the French version, and a moderate one in the German version. Selection bias, chronicity of the complaints, as well as cultural differences could explain these results. In conclusion, both the French and German version of the SFS are valid and reliable for evaluation of perceived functional capacity for patients with back complaints.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

The Alcohol Use Disorders Identification Test (AUDIT) as a screening tool for excessive drinking in primary care: reliability and validity of a French version.

BACKGROUND: Excessive drinking is a major problem in Western countries. AUDIT (Alcohol Use Disorders Identification Test) is a 10-item questionnaire developed as a transcultural screening tool to detect excessive alcohol consumption and dependence in primary health care settings. OBJECTIVES: The aim of the study is to validate a French version of the Alcohol Use Disorders Identification Test (AUDIT). METHODS: We conducted a validation cross-sectional study in three French-speaking areas (Paris, Geneva and Lausanne). We examined psychometric properties of AUDIT as its internal consistency, and its capacity to correctly diagnose alcohol abuse or dependence as defined by DSM-IV and to detect hazardous drinking (defined as alcohol intake >30 g pure ethanol per day for men and >20 g of pure ethanol per day for women). We calculated sensitivity, specificity, positive and negative predictive values and Receiver Operator Characteristic curves. Finally, we compared the ability of AUDIT to accurately detect "alcohol abuse/dependence" with that of CAGE and MAST. RESULTS: 1207 patients presenting to outpatient clinics (Switzerland, n = 580) or general practitioners' (France, n = 627) successively completed CAGE, MAST and AUDIT self-administered questionnaires, and were independently interviewed by a trained addiction specialist. AUDIT showed a good capacity to discriminate dependent patients (with AUDIT > or =13 for males, sensitivity 70.1%, specificity 95.2%, PPV 85.7%, NPV 94.7% and for females sensitivity 94.7%, specificity 98.2%, PPV 100%, NPV 99.8%); and hazardous drinkers (with AUDIT > or =7, for males sensitivity 83.5%, specificity 79.9%, PPV 55.0%, NPV 82.7% and with AUDIT > or =6 for females, sensitivity 81.2%, specificity 93.7%, PPV 64.0%, NPV 72.0%). AUDIT gives better results than MAST and CAGE for detecting "Alcohol abuse/dependence" as showed on the comparative ROC curves. CONCLUSIONS: The AUDIT questionnaire remains a good screening instrument for French-speaking primary care.

Quantitative multi-parameter mapping of R1, PD(*), MT, and R2(*) at 3T: a multi-center validation.

Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM) was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1 mm high-resolution maps of the longitudinal relaxation rate (R1 = 1/T1), effective proton density (PD(*)), magnetization transfer saturation (MT) and effective transverse relaxation rate (R2(*) = 1/T2(*)). MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV) for typical morphometric measures [i.e., gray matter (GM) probability maps used in voxel-based morphometry] and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1 and 8%, respectively, except for the inter-site CoV of R2(*) (<20%). The GM probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived GM probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.

Automated detection of patient-ventilator asynchrony: new tool or new toy?

Although severe patient-ventilator asynchrony is frequent during invasive and non-invasive mechanical ventilation, diagnosing such asynchronies usually requires the presence at the bedside of an experienced clinician to assess the tracings displayed on the ventilator screen, thus explaining why evaluating patient-ventilator interaction remains a challenge in daily clinical practice. In the previous issue of Critical Care, Sinderby and colleagues present a new automated method to detect, quantify, and display patient-ventilator interaction. In this validation study, the automatic method is as efficient as experts in mechanical ventilation. This promising system could help clinicians extend their knowledge about patient-ventilator interaction and further improve assisted mechanical ventilation.

External validation of the ASTRAL score to predict 3- and 12-month functional outcome in the China National Stroke Registry.

BACKGROUND AND PURPOSE: The ASTRAL score was recently introduced as a prognostic tool for acute ischemic stroke. It predicts 3-month outcome reliably in both the derivation and the validation European cohorts. We aimed to validate the ASTRAL score in a Chinese stroke population and moreover to explore its prognostic value to predict 12-month outcome. METHODS: We applied the ASTRAL score to acute ischemic stroke patients admitted to 132 study sites of the China National Stroke Registry. Unfavorable outcome was assessed as a modified Rankin Scale score >2 at 3 and 12 months. Areas under the curve were calculated to quantify the prognostic value. Calibration was assessed by comparing predicted and observed probability of unfavorable outcome using Pearson correlation coefficient. RESULTS: Among 3755 patients, 1473 (39.7%) had 3-month unfavorable outcome. Areas under the curve for 3 and 12 months were 0.82 and 0.81, respectively. There was high correlation between observed and expected probability of unfavorable 3- and 12-month outcome (Pearson correlation coefficient: 0.964 and 0.963, respectively). CONCLUSIONS: ASTRAL score is a reliable tool to predict unfavorable outcome at 3 and 12 months after acute ischemic stroke in the Chinese population. It is a useful tool that can be readily applied in clinical practice to risk-stratify acute stroke patients.

Validation of an Adapted French Form of the Career Adapt-Abilities Scale in four Francophone Countries

This study presents the validation of a French version of the Career Adapt-Abilities Scale in four Francophone countries. The aim was to re-analyze the item selection and then compare this newly developed French-language form with the international form 2.0. Exploratory factor analysis was used as a tool for item selection, and confirmatory factor analysis (CFA) verified the structure of the CAAS French-language form. Measurement equivalence across the four countries was tested using multi-group CFA. Adults and adolescents (N=1,707) participated from Switzerland, Belgium, Luxembourg, and France. Items chosen for the final version of the CAAS French-language form are different to those in the CAAS international form 2.0 and provide an improvement in terms of reliability. The factor structure is replicable across country, age, and gender. Strong evidence for metric invariance and partial evidence for scalar invariance of the CAAS French-language form across countries is given. The CAAS French-language and CAAS international form 2.0 can be used in a combined form of 31 items. The CAAS French-language form will certainly be interesting for practitioners using interventions based on the life design paradigm or aiming at increasing career adapt-ability.

Validation of the Postnatal Perceived Stress Inventory in a French-speaking population of primiparous women

Objective To develop a Postnatal Perceived Stress Inventory (PNPSI) and assess its psychometric properties. Design Cross-sectional quantitative study. Setting One nurse-managed labor and delivery unit in a university hospital in a major metropolitan area. Participants One hundred seventy-nine (179) primiparous French speaking women who gave birth at term. Methods The PNPSI was validated at 6 weeks postpartum. Its predictive validity for depression and anxiety was assessed at the same time. Results The exploratory analysis revealed a 19-item structure divided into six factors. This inventory has good internal consistency (Cronbach's alpha = .815). The predictive validity shows that the PNPSI significantly predicts depression and anxiety at 6 weeks postpartum, and that certain factors are particularly prominent. Conclusion The PNPSI's psychometric properties make it a useful tool for future research to evaluate interventions for perceived stress during the postnatal period. Its predictive power for depression indicates that it is also a promising tool for clinical settings.

The business model ontology a proposition in a design science approach

The goal of this dissertation is to find and provide the basis for a managerial tool that allows a firm to easily express its business logic. The methodological basis for this work is design science, where the researcher builds an artifact to solve a specific problem. In this case the aim is to provide an ontology that makes it possible to explicit a firm's business model. In other words, the proposed artifact helps a firm to formally describe its value proposition, its customers, the relationship with them, the necessary intra- and inter-firm infrastructure and its profit model. Such an ontology is relevant because until now there is no model that expresses a company's global business logic from a pure business point of view. Previous models essentially take an organizational or process perspective or cover only parts of a firm's business logic. The four main pillars of the ontology, which are inspired by management science and enterprise- and processmodeling, are product, customer interface, infrastructure and finance. The ontology is validated by case studies, a panel of experts and managers. The dissertation also provides a software prototype to capture a company's business model in an information system. The last part of the thesis consists of a demonstration of the value of the ontology in business strategy and Information Systems (IS) alignment. Structure of this thesis: The dissertation is structured in nine parts: Chapter 1 presents the motivations of this research, the research methodology with which the goals shall be achieved and why this dissertation present a contribution to research. Chapter 2 investigates the origins, the term and the concept of business models. It defines what is meant by business models in this dissertation and how they are situated in the context of the firm. In addition this chapter outlines the possible uses of the business model concept. Chapter 3 gives an overview of the research done in the field of business models and enterprise ontologies. Chapter 4 introduces the major contribution of this dissertation: the business model ontology. In this part of the thesis the elements, attributes and relationships of the ontology are explained and described in detail. Chapter 5 presents a case study of the Montreux Jazz Festival which's business model was captured by applying the structure and concepts of the ontology. In fact, it gives an impression of how a business model description based on the ontology looks like. Chapter 6 shows an instantiation of the ontology into a prototype tool: the Business Model Modelling Language BM2L. This is an XML-based description language that allows to capture and describe the business model of a firm and has a large potential for further applications. Chapter 7 is about the evaluation of the business model ontology. The evaluation builds on literature review, a set of interviews with practitioners and case studies. Chapter 8 gives an outlook on possible future research and applications of the business model ontology. The main areas of interest are alignment of business and information technology IT/information systems IS and business model comparison. Finally, chapter 9 presents some conclusions.

Automatic target validation based on neuroscientific literature mining for tractography.

Target identification for tractography studies requires solid anatomical knowledge validated by an extensive literature review across species for each seed structure to be studied. Manual literature review to identify targets for a given seed region is tedious and potentially subjective. Therefore, complementary approaches would be useful. We propose to use text-mining models to automatically suggest potential targets from the neuroscientific literature, full-text articles and abstracts, so that they can be used for anatomical connection studies and more specifically for tractography. We applied text-mining models to three structures: two well-studied structures, since validated deep brain stimulation targets, the internal globus pallidus and the subthalamic nucleus and, the nucleus accumbens, an exploratory target for treating psychiatric disorders. We performed a systematic review of the literature to document the projections of the three selected structures and compared it with the targets proposed by text-mining models, both in rat and primate (including human). We ran probabilistic tractography on the nucleus accumbens and compared the output with the results of the text-mining models and literature review. Overall, text-mining the literature could find three times as many targets as two man-weeks of curation could. The overall efficiency of the text-mining against literature review in our study was 98% recall (at 36% precision), meaning that over all the targets for the three selected seeds, only one target has been missed by text-mining. We demonstrate that connectivity for a structure of interest can be extracted from a very large amount of publications and abstracts. We believe this tool will be useful in helping the neuroscience community to facilitate connectivity studies of particular brain regions. The text mining tools used for the study are part of the HBP Neuroinformatics Platform, publicly available at http://connectivity-brainer.rhcloud.com/.

Quality of life after pulmonary embolism: Prospective validation of the German version of the PEmb-QoL questionnaire.

BACKGROUND: The Pulmonary Embolism Quality of Life questionnaire (PEmb-QoL) is a 40-item questionnaire to measure health-related quality of life in patients with pulmonary embolism. It covers six 6 dimensions: frequency of complaints, limitations in activities of daily living, work-related problems, social limitations, intensity of complaints, and emotional complaints. Originally developed in Dutch and English, we prospectively validated a German version of the PEmb-QoL. METHODS: A forward-backward translation of the English version of the PEmb-QoL into German was performed. German-speaking consecutive adult patients aged ≥18 years with an acute, objectively confirmed pulmonary embolism discharged from a Swiss university hospital (01/2011-06/2013) were recruited telephonically. Established psychometric tests and criteria were used to evaluate the acceptability, reliability, and validity of the German PEmb-QoL questionnaire. To assess the underlying dimensions, an exploratory factor analysis was performed. RESULTS: Overall, 102 patients were enrolled in the study. The German version of the PEmb-QoL showed a good internal consistency (Cronbach's alpha ranging from 0.72 to 0.96), item-total (0.53-0.95) and inter-item correlations (>0.4), and test-retest reliability (intra-class correlation coefficients 0.59-0.89) for the dimension scores. A moderate correlation of the PEmb-QoL with SF-36 dimension and summary scores (0.21-0.83) indicated convergent validity, while low correlations of PEmb-QoL dimensions with clinical characteristics (-0.16-0.37) supported discriminant validity. The exploratory factor analysis suggested four underlying dimensions: limitations in daily activities, symptoms, work-related problems, and emotional complaints. CONCLUSION: The German version of the PEmb-QoL questionnaire is a valid and reliable disease-specific measure for quality of life in patients with pulmonary embolism.

Prédiction des complications après duodénopancréatectomie céphalique: validation d'un score de complications postopératoires = Prediction of complications after pancreaticoduodenectomy: validation of a postoperative complication score

Objectifs La chirurgie pancréatique reste associée à une morbidité postopératoire importante. Les efforts sont concentrés la plupart du temps sur la diminution de cette morbidité, mais la détection précoce de patients à risque de complications pourrait être une autre stratégie valable. Un score simple de prédiction des complications après duodénopancréatectomie céphalique a récemment été publié par Braga et al. La présente étude a pour but de valider ce score et de discuter de ses possibles implications cliniques. Méthodes De 2000 à 2015, 245 patients ont bénéficié d'une duodénopancréatectomie céphalique dans notre service. Les complications postopératoires ont été recensées selon la classification de Dindo et Clavien. Le score de Braga se base sur quatre paramètres : le score ASA (American Society of Anesthesiologists), la texture du pancréas, le diamètre du canal de Wirsung (canal pancréatique principal) et les pertes sanguines intra-opératoires. Un score de risque global de 0 à 15 peut être calculé pour chaque patient. La puissance de discrimination du score a été calculée en utilisant une courbe ROC (receiver operating characteristic). Résultats Des complications majeures sont apparues chez 31% des patients, alors que 17% des patients ont eu des complications majeures dans l'article de Braga. La texture du pancréas et les pertes sanguines étaient statistiquement significativement corrélées à une morbidité accrue. Les aires sous la courbe étaient respectivement de 0.95 et 0.99 pour les scores classés en quatre catégories de risques (de 0 à 3, 4 à 7, 8 à 11 et 12 à 15) et pour les scores individuels (de 0 à 15). Conclusions Le score de Braga permet donc une bonne discrimination entre les complications mineures et majeures. Notre étude de validation suggère que ce score peut être utilisé comme un outil pronostique de complications majeures après duodénopancréatectomie céphalique. Les implications cliniques, c'est-à-dire si les stratégies de prise en charge postopératoire doivent être adaptées en fonction du risque individuel du patient, restent cependant à élucider. -- Objectives Pancreatic surgery remains associated with important morbidity. Efforts are most commonly concentrated on decreasing postoperative morbidity, but early detection of patients at risk could be another valuable strategy. A simple prognostic score has recently been published. This study aimed to validate this score and discuss possible clinical implications. Methods From 2000 to 2012, 245 patients underwent pancreaticoduodenectomy. Complications were graded according to the Dindo-Clavien classification. The Braga score is based on American Society of Anesthesiologists score, pancreatic texture, Wirsung duct diameter, and blood loss. An overall risk score (from 0 to 15) can be calculated for each patient. Score discriminant power was calculated using a receiver operating characteristic curve. Results Major complications occurred in 31% of patients compared to 17% in Braga's data. Pancreatic texture and blood loss were independently statistically significant for increased morbidity. The areas under curve were 0.95 and 0.99 for 4-risk categories and for individual scores, respectively. Conclusions The Braga score discriminates well between minor and major complications. Our validation suggests that it can be used as prognostic tool for major complications after pancreaticoduodenectomy. The clinical implications, i.e., whether postoperative treatment strategies should be adapted according to the patient's individual risk, remain to be elucidated.

Radiographic volume analysis as a novel tool to determine nasopalatine duct cyst dimensions and its association with presenting symptoms and postoperative complications.

OBJECTIVES: The aims of the study were to use cone beam computed tomography (CBCT) images of nasopalatine duct cysts (NPDC) and to calculate the diameter, surface area, and 3D-volume using a custom-made software program. Furthermore, any associations of dimensions of NPDC with age, gender, presence/absence of maxillary incisors/canines (MI/MC), endodontic treatment of MI/MC, presenting symptoms, and postoperative complications were evaluated. MATERIAL AND METHODS: The study comprised 40 patients with a histopathologically confirmed NPDC. On preoperative CBCT scans, curves delineating the cystic borders were drawn in all planes and the widest diameter (in millimeter), surface area (in square millimeter), and volume (in cubic millimeter) were calculated. RESULTS: The overall mean cyst diameter was 15 mm (range 7-47 mm), the mean cyst surface area 566 mm(2) (84-4,516 mm(2)), and the mean cyst volume 1,735 mm(3) (65-25,350 mm(3)). For 22 randomly allocated cases, a second measurement resulted in a mean absolute aberration of ±4.2 % for the volume, ±2.8 % for the surface, and ±4.9 % for the diameter. A statistically significant association was found for the CBCT determined cyst measurements and the need for preoperative endodontic treatment to MI/MC and for postoperative complications. CONCLUSION: In the hands of a single experienced operator, the novel software exhibited high repeatability for measurements of cyst dimensions. Further studies are needed to assess the application of this tool for dimensional analysis of different jaw cysts and lesions including treatment planning. CLINICAL RELEVANCE: Accurate radiographic information of the bone volume lost (osteolysis) due to expansion of a cystic lesion in three dimensions could help in personalized treatment planning.

Le burnout de l'élève : validation du School Burnout Inventory, identification de facteurs de risque et de protection et exploration des liens avec la consomation de substances

Syndrome de stress scolaire chronique, le bumout de l'élève ou bumout scolaire suscite un intérêt grandissant mais ses déterminants sont encore peu connus. De plus, ce phénomène est rarement étudié chez les adolescents francophones et aucune recherche n'a encore été menée en Suisse. Par conséquent, au travers de ce travail de thèse, nous proposons d'étendre la recherche sur le bumout scolaire aux adolescents de Suisse francophone et d'apporter des précisions sur ses facteurs de risque ou de protection. Pour ce faire, nous avons mené deux recherches empiriques impliquant 861 adolescents âgés de 14 à 18 ans et scolarisés en Suisse francophone. Ces adolescents ont répondu à une série d'échelles évaluant notamment le burnout scolaire, le stress scolaire, le soutien social, la consommation de substances et le parcours scolaire. Les résultats montrent tout d'abord que l'inventaire de Burnout Scolaire, version française du School Burnout lnventory, est un outil fiable et valide. Ensuite, il apparaît que le burnout scolaire touche jusqu'à 24% des adolescents de Suisse francophone et que ce dernier se caractérise par une perte d'intérêt pour l'école, une grande remise en question du sens du travail scolaire ainsi qu'un sentiment élevé d'insuffisance à l'école. Il apparaît également que le stress scolaire lié au succès et à l'avenir scolaire augmente le risque de bumout alors que le soutien des parents et des enseignants le diminue. Par ailleurs, nous mettons en évidence que l'effet du soutien social sur le burnout scolaire est médiatisé par le stress scolaire, ce qui souligne d'autant plus le rôle protecteur du soutien social. Nos résultats montrent également que les niveaux de bumout scolaire varient en fonction, d'une part de certaines caractéristiques du contexte scolaire et d'autre part en fonction de la sévérité de la consommation de substances des adolescents. Enfin, les connaissances accumulées dans ce travail et leur mise en perspective dans un modèle d'intervention précoce permettent d'insister sur le rôle de l'école et des professionnels de l'école dans la prévention du burnout scolaire. -- Syndrome of chronic school stress, pupil 's bumout or school bumout is of growing interest. However, little is known about its determinants. Moreover, this phenomenon is rarely studied in French speaking adolescents and no research has yet been conducted in Switzerland. Therefore, through this thesis, we propose to extend the research on school bumout to Swiss French speaking adolescents and to clarify its risk and protective factors. To achieve this, we conducted two empirical research involving 861 adolescents aged 14 to 18 and enrolled in the French part of Switzerland. These adolescents were asked to answer a questionnaire about school bumout, academic stress, social support, substance use and schooling. Results first show, that the French version of the School Bumout Inventory is a reliable and valid tool. lt then appears that school bumout affects up to 24% of adolescents in the French speaking part of Switzerland and that this phenomenon is characterized by a loss of interest in school, a great challenge to the sense of school work and a high sense of insufissance school. lt also appears that stress related to school success and academic future increases the risk of bumout while parents and teachers support decreases it. Moreover, we highlight that the effect of social support on school bumout is mediated by school stress, which further underscores the protective role of social support. Our results also show that school bumout levels vary depending on characteristics of the school context and on the severity of substance use of adolecents. Finally, the knowledge accumulated in this work and putting it onto perspective within early intervention model enable to insist on the role of school and school professionals in the prevention of school bumout

Prediction of Complications After Pancreaticoduodenectomy: Validation of a Postoperative Complication Score.

OBJECTIVES: Pancreatic surgery remains associated with important morbidity. Efforts are most commonly concentrated on decreasing postoperative morbidity, but early detection of patients at risk could be another valuable strategy. A simple prognostic score has recently been published. This study aimed to validate this score and discuss possible clinical implications. METHODS: From 2000 to 2012, 245 patients underwent a pancreaticoduodenectomy. Complications were graded according to the Dindo-Clavien Classification. The Braga score is based on American Society of Anesthesiologists score, pancreatic texture, Wirsung duct diameter, and blood loss. An overall risk score (0-15) can be calculated for each patient. Score discriminant power was calculated using a receiver operating characteristic curve. RESULTS: Major complications occurred in 31% of patients compared with 17% in Braga's data. Pancreatic texture and blood loss were independently statistically significant for increased morbidity. Areas under the curve were 0.95 and 0.99 for 4-risk categories and for individual scores, respectively. CONCLUSIONS: The Braga score discriminates well between minor and major complications. Our validation suggests that it can be used as a prognostic tool for major complications after pancreaticoduodenectomy. The clinical implications, that is, whether postoperative treatment strategies should be adapted according to the patient's individual risk, remain to be elucidated.