L'apport du patient simulé dans l'apprentissage de la relation médecin-malade: résultats d'une évaluation préliminaire

Contexte : Les étudiants de 4° année des études de médecine à la faculté de biologie et de médecine de Lausanne bénéficient d'un enseignement des habiletés à la communication médecin-malade, ayant recours à un patient simulé joué par un comédien. But : Évaluer la pertinence de cette méthode active dans l'optique de renforcer cet enseignement dans le curriculum. Méthodes : Un questionnaire demande aux étudiants d'apprécier leurs apprentissages, ainsi que le dispositif d'enseignement. Un autre questionnaire évalue les compétences de l'étudiant qui mène l'entretien par l'étudiant lui-même (étudiant actif), par les étudiants observateurs, par l'enseignant et par le patient simulé. Résultats : Ce dispositif d'enseignement est apprécié des étudiants et permet aux étudiants qui ont mené l'entretien et aux étudiants observateurs d'en tirer un bénéfice. Les étudiants actifs ont tendance à évaluer leurs compétences d'entretien plus négativement que ne le font l'enseignant, le comédien et les étudiants observateurs .Conclusion : Ce dispositif d'enseignement est perçu comme pertinent par l'ensemble des participants, mais devrait être renforcé pour donner à chaque étudiant l'occasion de participer activement à l'entrevue simulée. -- Context: 4th year medicine students at the Faculty of Biology and Medicine of Lausanne were taught to develop patient-doctor communication skills, using a simulated patient played by an actor. Objective: To assess the relevance of this active method in the perspective of reinforcing this teaching approach in the curriculum. Method: This new form of teaching was assessed by questionnaires filled by all participants, i.e. students involved in the communication (active student), students who were bystanders (observer students), the tutor, as well as the actor. Results: This teaching approach was appreciated from all students, active and observer, allowing them to gain benefit from the interview on communication skills acquirement. The active students assessed their communication skills more negatively than did the teacher, the actor and the observer students. Conclusion: This teaching method seems to be relevant for all participants and should be reinforced to give the opportunity for each student to participate as an active student.

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.

Automatic Mallampati Classification Using Active Appearance Models

Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.

The management of iron deficiency in inflammatory bowel disease--an online tool developed by the RAND/UCLA appropriateness method.

BACKGROUND: Iron deficiency is a common and undertreated problem in inflammatory bowel disease (IBD). AIM: To develop an online tool to support treatment choice at the patient-specific level. METHODS: Using the RAND/UCLA Appropriateness Method (RUAM), a European expert panel assessed the appropriateness of treatment regimens for a variety of clinical scenarios in patients with non-anaemic iron deficiency (NAID) and iron deficiency anaemia (IDA). Treatment options included adjustment of IBD medication only, oral iron supplementation, high-/low-dose intravenous (IV) regimens, IV iron plus erythropoietin-stimulating agent (ESA), and blood transfusion. The panel process consisted of two individual rating rounds (1148 treatment indications; 9-point scale) and three plenary discussion meetings. RESULTS: The panel reached agreement on 71% of treatment indications. 'No treatment' was never considered appropriate, and repeat treatment after previous failure was generally discouraged. For 98% of scenarios, at least one treatment was appropriate. Adjustment of IBD medication was deemed appropriate in all patients with active disease. Use of oral iron was mainly considered an option in NAID and mildly anaemic patients without disease activity. IV regimens were often judged appropriate, with high-dose IV iron being the preferred option in 77% of IDA scenarios. Blood transfusion and IV+ESA were indicated in exceptional cases only. CONCLUSIONS: The RUAM revealed high agreement amongst experts on the management of iron deficiency in patients with IBD. High-dose IV iron was more often considered appropriate than other options. To facilitate dissemination of the recommendations, panel outcomes were embedded in an online tool, accessible via http://ferroscope.com/.

A gene-rich, transcriptionally active environment and the pre-deposition of repressive marks are predictive of susceptibility to KRAB/KAP1-mediated silencing.

AbstractBACKGROUND: KRAB-ZFPs (Krüppel-associated box domain-zinc finger proteins) are vertebrate-restricted transcriptional repressors encoded in the hundreds by the mouse and human genomes. They act via an essential cofactor, KAP1, which recruits effectors responsible for the formation of facultative heterochromatin. We have recently shown that KRAB/KAP1 can mediate long-range transcriptional repression through heterochromatin spreading, but also demonstrated that this process is at times countered by endogenous influences.METHOD: To investigate this issue further we used an ectopic KRAB-based repressor. This system allowed us to tether KRAB/KAP1 to hundreds of euchromatic sites within genes, and to record its impact on gene expression. We then correlated this KRAB/KAP1-mediated transcriptional effect to pre-existing genomic and chromatin structures to identify specific characteristics making a gene susceptible to repression.RESULTS: We found that genes that were susceptible to KRAB/KAP1-mediated silencing carried higher levels of repressive histone marks both at the promoter and over the transcribed region than genes that were insensitive. In parallel, we found a high enrichment in euchromatic marks within both the close and more distant environment of these genes.CONCLUSION: Together, these data indicate that high levels of gene activity in the genomic environment and the pre-deposition of repressive histone marks within a gene increase its susceptibility to KRAB/KAP1-mediated repression.

Experimental Uveitis can be Maintained in Rabbits for a Period of Six Weeks After a Safe Sensitization Method.

Abstract Purpose: New treatments against long-lasting uveitis need to be tested. Our aim was to develop a six-week model of uveitis in rabbits. Methods: Rabbits were presensitized with an s.c. injection of Mycobacterium tuberculosis H37RA emulsified with TiterMax® Gold adjuvant. Uveitis was induced at day 28 and 50, by intravitreal challenges of antigen suspension. Ocular inflammation was assessed till euthanasia at day 71 after s.c. injection of M. tuberculosis H37RA by: (a) the number of inflammatory cells in aqueous humor (AH); (b) the protein concentration in AH; (c) the clinical score (mean of conjunctival hyperaemia, conjunctival chemosis, oedema and secretion); (d) the microscopical score (mean presence of fibrin and synechiae, aqueous cell density and aqueous flare grade, as scored by slit lamp). Results: At the sites of presensitization injection, rabbits presented flat nodules which progressively vanished. The first challenge induced a significant increase in the four parameters (p < 0.05 the Wilcoxon/Kruskal-Wallis test). The AH contained 764 ± 82 cells/µl and 32 ± 0.77 mg protein/ml. During the following days, inflammatory parameters decreased slightly. The second intravitreal challenge increased inflammation (3564 ± 228 cells/µl AH and 31 ± 1 mg protein/ml), which remained at a high level for a longer period of time. Conclusion: We developed a model of long-term uveitis, which could be maintained in rabbits for at least six weeks. Such a model could be used to test the efficacy of either new drugs or various drug delivery systems intended to deliver active agents during a few months.

Active screening for pulmonary tuberculosis by chest x-ray among immigrants at the Swiss border

Summary : Aim: To assess the number of immigrants with pulmonary tuberculosis detected by chest x-ray screening at the Swiss border. Method: All adult immigrants entering Switzerland in 2004 were screened by chest x-ray (CXR). The number of radiological abnormalities suggestive of pulmonary tuberculosis, and the proportion requiring treatment for tuberculosis, were assessed retrospectively. The frequency of symptoms among immigrants with documented TB was compared with a sample of immigrants with a normal CXR. Results: Among 8995 immigrants, 8240 had a normal CXR, 630 had some abnormality not suggestive of active TB and 125 (1.4%) had a CXR suggestive of pulmonary TB. A final diagnosis of tuberculosis requiring treatment was made in SO (1 l with positive smear and culture, 16 with positive culture and 23 with negative culture), 57 had fibrotic lesions and 18 had another disease or a normal x-ray on control. The prevalence of symptoms did not differ between 27 immigrants with documented TB (smear+/culture+: 82%, smear-/ culture+: 75%), and 23 with smear-/culturetuberculosis (91%), but lower in 57 immigrants with fibrotic lesions (60%). Cough was more frequent among the 27 immigrants with documented TB (70%) than among 198 smokers without TB (37%) and among 229 non-smokers without TB (15%) Conclusions: Only 22% (27/125) of immigrants with CXR abnormalities suggestive of pulrnonary tuberculosis were documented by smear and/or culture and 40% (50/125) needed antituberculous treatment. 2/11 smear-positive immigrants would not have been detected by a questionnaire on symptoms. Rapport de synthèse : Le but de l'étude est d'évaluer le rendement du dépistage radiologique de la tuberculose pulmonaire chez les immigrés à l'entrée en Suisse. Méthode: parmi les immigrés adultes entrés en Suisse en 2004, qui ont tous passé un contrôle radiologique, le nombre de porteurs de clichés thoraciques suspects de tuberculose et la proportion de cas chez lesquels un traitement antituberculeux a été prescrit ont été évalués rétrospectivement. La fréquence des symptômes chez les immigrés atteints de tuberculose a été comparée à celle d'un groupe contrôle sans tuberculose. Résultats: parmi 8995 immigrés, 8240 avaient un cliché thoracique normal, 630 étaient porteurs d'une anomalie non suspecte de tuberculose active et 125 (1.4%) montraient des signes radiologiques suspects de tuberculose. Un diagnostic final de tuberculose nécessitant un traitement a été posé dans 50 cas (11 cas à frottis et culture positifs, 16 cas à culture positive, 23 cas à culture négative), 57 présentaient des lésions cicatricielles compatibles avec une ancienne tuberculose et 18 avaient une autre affection pulmonaire ou un cliché normal au contrôle. La prévalence des plaintes n'était pas différente entre les 27 immigrés porteurs d'une tuberculose documentée (frottis+ /culture+: 82%, frottis-/culture+ : 75%) et les 23 immigrés atteints d'une tuberculose non documentée (frottis-/culture-: 91%), mais elle était plus élevée que chez les 57 immigrés porteurs de lésions cicatricielles (59%). La toux était plus fréquente chez les 27 tuberculeux documentés (70%) que chez 198 fumeurs sans tuberculose (37%) et chez 229 non fumeurs sans tuberculose (15%). Conclusions: seuls 22% (27/125) des immigrés dont le cliché thoracique est suspect de tuberculose sont porteurs d'une tuberculose documentée par examen direct ou culture et 40% (50/125) nécessitent un traitement antituberculeux. Deux immigrants sur les 11 cas frottis positifs n'auraient pas été dépistés par un questionnaire.

Active Learning of Very-High Resolution Optical Imagery with SVM: Entropy vs Margin Sampling

An active learning method is proposed for the semi-automatic selection of training sets in remote sensing image classification. The method adds iteratively to the current training set the unlabeled pixels for which the prediction of an ensemble of classifiers based on bagged training sets show maximum entropy. This way, the algorithm selects the pixels that are the most uncertain and that will improve the model if added in the training set. The user is asked to label such pixels at each iteration. Experiments using support vector machines (SVM) on an 8 classes QuickBird image show the excellent performances of the methods, that equals accuracies of both a model trained with ten times more pixels and a model whose training set has been built using a state-of-the-art SVM specific active learning method

Harmonic active contours.

We propose a segmentation method based on the geometric representation of images as 2-D manifolds embedded in a higher dimensional space. The segmentation is formulated as a minimization problem, where the contours are described by a level set function and the objective functional corresponds to the surface of the image manifold. In this geometric framework, both data-fidelity and regularity terms of the segmentation are represented by a single functional that intrinsically aligns the gradients of the level set function with the gradients of the image and results in a segmentation criterion that exploits the directional information of image gradients to overcome image inhomogeneities and fragmented contours. The proposed formulation combines this robust alignment of gradients with attractive properties of previous methods developed in the same geometric framework: 1) the natural coupling of image channels proposed for anisotropic diffusion and 2) the ability of subjective surfaces to detect weak edges and close fragmented boundaries. The potential of such a geometric approach lies in the general definition of Riemannian manifolds, which naturally generalizes existing segmentation methods (the geodesic active contours, the active contours without edges, and the robust edge integrator) to higher dimensional spaces, non-flat images, and feature spaces. Our experiments show that the proposed technique improves the segmentation of multi-channel images, images subject to inhomogeneities, and images characterized by geometric structures like ridges or valleys.

Appropriateness of therapy for active Crohn's disease: results of a multidisciplinary international Expert Panel (EPACT II)

INTRODUCTION: The development of novel therapies and the increasing number of trials testing management strategies for luminal Crohn's disease (CD) have not filled all the gaps in our knowledge. Thus, in clinical practice, many decisions for CD patients need to be taken without high quality evidence. For this reason, a multidisciplinary European expert panel followed the RAND method to develop explicit criteria for the management of individual patients with active, steroid-dependent (ST-D) and steroid-refractory (ST-R) CD. AIMS & METHODS: Twelve international experts convened in Geneva, Switzerland in December 2007, to rate explicit clinical scenarios, corresponding to real daily practice, on a 9-point scale according to the literature evidence and their own expertise. Median ratings were stratified into three categories: appropriate (7-9), uncertain (4-6) and inappropriate (1-3). RESULTS: Overall, panelists rated 296 indications pertaining to mild-to-moderate, severe, ST-D, and ST-R CD. In anti-TNF naïve patients, budesonide and prednisone were found appropriate for mild-moderate CD, and infliximab (IFX) when those had previously failed or had not been tolerated. In patients with prior success with IFX, this drug with or without co-administration of a thiopurine analog was favored. Other anti-TNFs were appropriate in case of intolerance or resistance to IFX. High doses steroids, IFX or adalimumab were appropriate in severe active CD. Among 105 indications for ST-D or ST-R disease, the panel considered appropriate the thiopurine analogs, methotrexate, IFX, adalimumab and surgery for limited resection, depending on the outcome of prior therapies. Anti-TNFs were generally considered appropriate in ST-R. CONCLUSION: Steroids, including budesonide for mild-to-moderate CD, remain first-line therapies in active luminal CD. Anti-TNFs, in particular IFX with respect to the amount of available evidence, remain second-line for most indications. Thiopurine analogs are preferred to anti-TNFs when steroids are not appropriate, except when anti-TNFs were previously successful. These recommendations are available online (www.epact.ch). A prospective evaluation of these criteria in a large database in Switzerland in underway to validate these criteria.

Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework

In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.

Predicting the evolution of Kaposi sarcoma, in the highly active antiretroviral therapy era.

BACKGROUND: The outcome of Kaposi sarcoma varies. While many patients do well on highly active antiretroviral therapy, others have progressive disease and need chemotherapy. In order to predict which patients are at risk of unfavorable evolution, we established a prognostic score. METHOD: The survival analysis (Kaplan-Meier method; Cox proportional hazards models) of 144 patients with Kaposi sarcoma prospectively included in the Swiss HIV Cohort Study, from January 1996 to December 2004, was conducted. OUTCOME ANALYZED: use of chemotherapy or death. VARIABLES ANALYZED: demographics, tumor staging [T0 or T1 (16)], CD4 cell counts and HIV-1 RNA concentration, human herpesvirus 8 (HHV8) DNA in plasma and serological titers to latent and lytic antigens. RESULTS: Of 144 patients, 54 needed chemotherapy or died. In the univariate analysis, tumor stage T1, CD4 cell count below 200 cells/microl, positive HHV8 DNA and absence of antibodies against the HHV8 lytic antigen at the time of diagnosis were significantly associated with a bad outcome.Using multivariate analysis, the following variables were associated with an increased risk of unfavorable outcome: T1 [hazard ratio (HR) 5.22; 95% confidence interval (CI) 2.97-9.18], CD4 cell count below 200 cells/microl (HR 2.33; 95% CI 1.22-4.45) and positive HHV8 DNA (HR 2.14; 95% CI 1.79-2.85).We created a score with these variables ranging from 0 to 4: T1 stage counted for two points, CD4 cell count below 200 cells/microl for one point, and positive HHV8 viral load for one point. Each point increase was associated with a HR of 2.26 (95% CI 1.79-2.85). CONCLUSION: In the multivariate analysis, staging (T1), CD4 cell count (<200 cells/microl), positive HHV8 DNA in plasma, at the time of diagnosis, predict evolution towards death or the need of chemotherapy.

Active learning methods for remote sensing image classification

In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.

Method to assess and optimise dependability of complex macro-systems: application to a railway signalling system

Achieving a high degree of dependability in complex macro-systems is challenging. Because of the large number of components and numerous independent teams involved, an overview of the global system performance is usually lacking to support both design and operation adequately. A functional failure mode, effects and criticality analysis (FMECA) approach is proposed to address the dependability optimisation of large and complex systems. The basic inductive model FMECA has been enriched to include considerations such as operational procedures, alarm systems. environmental and human factors, as well as operation in degraded mode. Its implementation on a commercial software tool allows an active linking between the functional layers of the system and facilitates data processing and retrieval, which enables to contribute actively to the system optimisation. The proposed methodology has been applied to optimise dependability in a railway signalling system. Signalling systems are typical example of large complex systems made of multiple hierarchical layers. The proposed approach appears appropriate to assess the global risk- and availability-level of the system as well as to identify its vulnerabilities. This enriched-FMECA approach enables to overcome some of the limitations and pitfalls previously reported with classical FMECA approaches.