University of Rouen

About: University of Rouen is a education organization based out in Rouen, France. It is known for research contribution in the topics: Population & Receptor. The organization has 7299 authors who have published 13209 publications receiving 313477 citations.

The concept and definition of therapeutic inertia in hypertension in primary care : a qualitative systematic review

Abstract: Therapeutic inertia has been defined as the failure of health-care provider to initiate or intensify therapy when therapeutic goals are not reached. It is regarded as a major cause of uncontrolled hypertension. The exploration of its causes and the interventions to reduce it are plagued by unclear conceptualizations and hypothesized mechanisms. We therefore systematically searched the literature for definitions and discussions on the concept of therapeutic inertia in hypertension in primary care, to try and form an operational definition. A systematic review of all types of publications related to clinical inertia in hypertension was performed. Medline, EMbase, PsycInfo, the Cochrane library and databases, BDSP, CRD and NGC were searched from the start of their databases to June 2013. Articles were selected independently by two authors on the basis of their conceptual content, without other eligibility criteria or formal quality appraisal. Qualitative data were extracted independently by two teams of authors. Data were analyzed using a constant comparative qualitative method. The final selection included 89 articles. 112 codes were grouped in 4 categories: terms and definitions (semantics), “who” (physician, patient or system), “how and why” (mechanisms and reasons), and “appropriateness”. Regarding each of these categories, a number of contradictory assertions were found, most of them relying on little or no empirical data. Overall, the limits of what should be considered as inertia were not clear. A number of authors insisted that what was considered deleterious inertia might in fact be appropriate care, depending on the situation. Our data analysis revealed a major lack of conceptualization of therapeutic inertia in hypertension and important discrepancies regarding its possible causes, mechanisms and outcomes. The concept should be split in two parts: appropriate inaction and inappropriate inertia. The development of consensual and operational definitions relying on empirical data and the exploration of the intimate mechanisms that underlie these behaviors are now needed.

Automatic COVID-19 CT segmentation using U-Net integrated spatial and channel attention mechanism.

Abstract: The coronavirus disease (COVID-19) pandemic has led to a devastating effect on the global public health. Computed Tomography (CT) is an effective tool in the screening of COVID-19. It is of great importance to rapidly and accurately segment COVID-19 from CT to help diagnostic and patient monitoring. In this paper, we propose a U-Net based segmentation network using attention mechanism. As not all the features extracted from the encoders are useful for segmentation, we propose to incorporate an attention mechanism including a spatial attention module and a channel attention module, to a U-Net architecture to re-weight the feature representation spatially and channel-wise to capture rich contextual relationships for better feature representation. In addition, the focal Tversky loss is introduced to deal with small lesion segmentation. The experiment results, evaluated on a COVID-19 CT segmentation dataset where 473 CT slices are available, demonstrate the proposed method can achieve an accurate and rapid segmentation result on COVID-19. The method takes only 0.29 second to segment a single CT slice. The obtained Dice Score and Hausdorff Distance are 83.1% and 18.8, respectively.