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Background: Coronavirus disease 2019 (COVID-19) emerged as a worldwide health crisis, overwhelming healthcare systems. Elevated cardiac troponin T (cTn T) at admission was associated with increased in-hospital mortality. However, data addressing the role of cTn T in major adverse cardiovascular events (MACE) in COVID-19 are scarce. Therefore, we assessed the role of baseline cTn T and cTn T kinetics for MACE and in-hospital mortality prediction in COVID-19. Methods: Three hundred and ten patients were included prospectively . One hundred and eight patients were excluded due to incomplete records. Patients were divided into three groups according to cTn T kinetics: ascending, descending, and constant. The cTn T slope was defined as the ratio of the cTn T change over time. The primary and secondary endpoints were MACE and in-hospital mortality. Results: Two hundred and two patients were included in the analysis (mean age 64.4 ± 16.7 years, 119 [58.9%] males). Mean duration of hospitalization was 14.0 ± 12.3 days. Sixty (29.7%) patients had MACE, and 40 (19.8%) patients died. Baseline cTn T predicted both endpoints ( p = 0.047, hazard ratio [HR] 1.805, 95% confidence interval [CI] 1.009 – 3.231 ; p = 0.009, HR 2.322, 95% CI 1.234 – 4.369) . Increased cTn T slope predicted mortality (p = 0.041, HR 1.006, 95% CI 1.000–1.011). Constant cTn T was associated with lower MACE and mortality (p = 0.000, HR 3.080, 95% CI 1.914–4.954, p = 0.000, HR 2.851, 95% CI 1.828–4.447). Conclusions: The present study emphasizes the additional role of cTn T testing in COVID-19 patients for risk stratification and improved diagnostic pathway and management.

La pandémie de Covid-19 a bouleversé non seulement l'économie de la plupart des pays, mais aussi le domaine scientifique médical. Les opinions publiques se sont immiscées dans les choix des essais thérapeutiques comme le montrent les controverses autour des protocoles utilisant l'hydroxychloroquine. Le choix du public pour ces traitements est expliqué comme l'application d'un "pari de Pascal". Cet article analyse la formation du système de croyance des individus en appliquant la théorie de l'ambiguïté et la théorie de l'entropie d'information. Il montre que les choix du public sont le fruit de stratégies communication choisies par les promoteurs de tel ou tel traitement.

The Covid-19 pandemic upset both the economies of most countries, but also the field of medical science. As never, public opinion has interfered in the choice of therapeutic trials as evidenced by the controversies surrounding protocols using hydroxychloroquine. The public's choice for these treatments is explained as the application of a kind of individual "Pascal's wager". This article analyses the formation of the belief system of individuals by applying ambiguity theory's insights and information entropy. It shows that the public's choices are the result of efficient communication strategies chosen by these treatments' promoters.

International audience; The disruption of supplies during the Covid-19 crisis has led to shortages but has also shown the adaptability of some companies, which have succeeded in adapting their production chains quickly to produce goods experiencing shortages: hydroalcoholic gel, masks, and medical gowns. These productive jumps from product A to product B are feasible because of the know-how proximity between the two classes of products. The proximities were computed from the analysis of co-exports and resulted in the construction of the product space. Based on the product space, as well as the customer-supplier relationships resulting from the input-output matrices, we propose a recommender system for companies. The goal is to promote distributed manufacturing by recommending a list of local suppliers to each company. As there is not always a local supplier for a desired product class, we consider the proximity between products to identify, in the absence of a supplier, a substitute supplier able to adapt its production tools to provide the required product. Our experiments are based on French data, from which we build a graph of synergies illustrating the potential productive links between companies. Finally, we show that our approach offers new perspectives to determine the level of territories' industrial resilience considering potential productive jumps.

International audience; Many factors in the surrounding environment have been reported to influence erythrocyte deformability. It is likely that some influences represent reversible changes in erythrocyte rigidity that may be involved in physiological regulation, while others represent the early stages of eryptosis, i.e., the red cell self-programmed death. For example, erythrocyte rigidification during exercise is probably a reversible physiological mechanism, while the alterations of red blood cells (RBCs) observed in pathological conditions (inflammation, type 2 diabetes, and sickle-cell disease) are more likely to lead to eryptosis. The splenic clearance of rigid erythrocytes is the major regulator of RBC deformability. The physicochemical characteristics of the surrounding environment (thermal injury, pH, osmolality, oxidative stress, and plasma protein profile) also play a major role. However, there are many other factors that influence RBC deformability and eryptosis. In this comprehensive review, we discuss the various elements and circulating molecules that might influence RBCs and modify their deformability: purinergic signaling, gasotransmitters such as nitric oxide (NO), divalent cations (magnesium, zinc, and Fe++), lactate, ketone bodies, blood lipids, and several circulating hormones. Meal composition (caloric and carbohydrate intake) also modifies RBC deformability. Therefore, RBC deformability appears to be under the influence of many factors. This suggests that several homeostatic regulatory loops adapt the red cell rigidity to the physiological conditions in order to cope with the need for oxygen or fuel delivery to tissues. Furthermore, many conditions appear to irreversibly damage red cells, resulting in their destruction and removal from the blood. These two categories of modifications to erythrocyte deformability should thus be differentiated.

AbstractBackgroundPrevious studies have shown a negative impact of the COVID-19 pandemic and its associated sanitary measures on mental health, especially among adolescents and young adults. Such a context may raise many concerns about the COVID-19 pandemic long-term psychological effects. An analysis of administrative databases could be an alternative and complementary approach to medical interview-based epidemiological surveys to monitor the mental health of the population. We conducted a nationwide study to describe the consumption of anxiolytics, antidepressants and hypnotics during the first year of the COVID-19 pandemic, compared to the five previous years.MethodsA historic cohort study was conducted by extracting and analysing data from the French health insurance database between 1 January 2015 and 28 February 2021. Individuals were classified into five age-based classes. Linear regression models were performed to assess the impact of the COVID-19 pandemic period on the number of drug consumers, in introducing an interaction term between time and COVID-19 period.ResultsSince March 2020, in all five age groups and all three drug categories studied, the number of patients reimbursed weekly has increased compared to the period from January 2015 to February 2020. The youngest the patients, the more pronounced the magnitude.ConclusionsMonitoring the consumption of psychiatric medications could be of great interest as reliable indicators are essential for planning public health strategies. A post-crisis policy including reliable monitoring of mental health must be anticipated.

International audience; To face the new challenges caused by modern industry, logistics operations managers need to focus more on integrating sustainability goals, adapt to unexpected disruptions and find new strategies and models for logistics management. The COVID-19 pandemic has proven that unforeseen fragilities, negatively affecting the supply chain performance, can arise rapidly, and logistics systems may confront unprecedented vulnerabilities regarding network structure disruption and high demand fluctuations. The existing studies on a resilient logistics network design did not sufficiently consider sustainability aspects. In fact, they mainly addressed the independent planning of decision-making problems with economic objectives. To fill this research gap, this paper concentrates on the design of resilient and sustainable logistics networks under epidemic disruption and demand uncertainty. A two-stage stochastic mixed integer programming model is proposed to integrate key decisions of location–allocation, inventory and routing planning. Moreover, epidemic disruptions and demand uncertainty are incorporated through plausible scenarios using a Monte Carlo simulation. In addition, two resiliency strategies, namely, capacity augmentation and logistics collaboration, are included into the basic model in order to improve the resilience and the sustainability of a logistics chain network. Finally, numerical examples are presented to validate the proposed approach, evaluate the performance of the different design models and provide managerial insights. The obtained results show that the integration of two design strategies improves resilience and sustainability.

International audience