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Saint-Sauveur-en-Rue, France

Roquet D.,CNRS Computer Science and Engineering Laboratory | Roquet D.,University of Strasbourg | Foucher J.R.,CNRS Computer Science and Engineering Laboratory | Foucher J.R.,University of Strasbourg | And 15 more authors.
NeuroImage: Clinical | Year: 2016

Purpose Locked-in syndrome and vegetative state are distinct outcomes from coma. Despite their differences, they are clinically difficult to distinguish at the early stage and current diagnostic tools remain insufficient. Since some brain functions are preserved in locked-in syndrome, we postulated that networks of spontaneously co-activated brain areas might be present in locked-in patients, similar to healthy controls, but not in patients in a vegetative state. Methods Five patients with locked-in syndrome, 12 patients in a vegetative state and 19 healthy controls underwent a resting-state fMRI scan. Individual spatial independent component analysis was used to separate spontaneous brain co-activations from noise. These co-activity maps were selected and then classified by two raters as either one of eight resting-state networks commonly shared across subjects or as specific to a subject. Results The numbers of spontaneous co-activity maps, total resting-state networks, and resting-state networks underlying high-level cognitive activity were shown to differentiate controls and locked-in patients from patients in a vegetative state. Analyses of each common resting-state network revealed that the default mode network accurately distinguished locked-in from vegetative-state patients. The frontoparietal network also had maximum specificity but more limited sensitivity. Conclusions This study reinforces previous reports on the preservation of the default mode network in locked-in syndrome in contrast to vegetative state but extends them by suggesting that other networks might be relevant to the diagnosis of locked-in syndrome. The aforementioned analysis of fMRI brain activity at rest might be a step in the development of a diagnostic biomarker to distinguish locked-in syndrome from vegetative state. © 2016 Published by Elsevier Inc.

Guillot M.,Hopitaux Universitaires Of Strasbourg | Guillot M.,Institute Of Physiologie | Herbrecht J.-E.,Hopitaux Universitaires Of Strasbourg | Sahraoui M.,Hopitaux Universitaires Of Strasbourg | And 4 more authors.
Reanimation | Year: 2013

Acute respiratory distress syndrome (ARDS) is due to the increase in permeability of the capillary alveolar membrane leading to non-cardiogenic pulmonary edema and hypoxia. Because ARDS is often associated with shock, its mortality rate remains high. One of the difficulties in ARDS is the management of fluid and volume expansion. During shock, volume expansion may lead to increase in oxygen transport related to increase in cardiac output, thus improving the patient's outcome. However, in case of ARDS, pulmonary capillary leakage could raise hypoxia and lead to decrease in oxygen transport during volume expansion. Therefore, hemodynamic monitoring is mandatory in ARDS. Monitoring allows analyzing the right ventricular function and pulmonary capillary leakage, helping to predict fluid responsiveness and risk of increased pulmonary edema. In ARDS, monitoring should be based on oxygen transport that would take into account all hemodynamic and respiratory parameters. © 2013 Société de réanimation de langue française (SRLF) and Springer-Verlag France.

Guillot M.,Hopitaux Universitaires Of Strasbourg | Guillot M.,Institute Of Physiologie | Sahraoui M.,Hopitaux Universitaires Of Strasbourg | Herbrecht J.-E.,Hopitaux Universitaires Of Strasbourg | And 4 more authors.
Praticien en Anesthesie Reanimation | Year: 2012

The incidence of mortality is high in acute respiratory distress syndrome (ARDS) because of the frequent association with septic shock. Oxygen transport optimization in septic shock by volume expansion should be used carefully in patients with ARDS. Fluid replacement may indeed induce right ventricular failure and pulmonary edema. Different methods have been developed to minimize the deleterious effects of volume expansion while improving oxygen transport: predicting the effect of volume expansion on cardiac output, blood volume management, optimization of osmotic and hydrostatic pressures, and assessment of the permeability of the pulmonary vasculature. Eventually, the management of volemia in ARDS should be based on the optimization of oxygen transport that takes into account both the hemodynamic and the respiratory parameters. © 2012 Published by Elsevier Masson SAS.

Goette-Di Marco P.,Service de Physiologie et dExplorations Fonctionnelles | Goette-Di Marco P.,Institute Of Physiologie | Talha S.,Service de Physiologie et dExplorations Fonctionnelles | Talha S.,Institute Of Physiologie | And 11 more authors.
Transplant International | Year: 2010

Summary Brain natriuretic peptide (BNP) increases in proportion to the extent of right ventricular dysfunction in pulmonary hypertension and after heart transplantation. No data are available after lung transplantation. Clinical, biological, respiratory, echocardiographic characteristics and circulating BNP and its second messenger cyclic guanosine monophosphate (cGMP) were determined in thirty matched subjects (10 lung-, 10 heart-transplant recipients (Ltx, Htx) and 10 healthy controls). Eventual correlations between these parameters were investigated. Heart rate and pulmonary arterial blood pressure were slightly increased after transplantation. Creatinine clearance was decreased. Mean of forced expiratory volume in 1 s was 76.6 ± 5.3% and vital capacity was 85.3 ± 6.4% of the predicted values in Ltx. BNP was similarly increased in Ltx and Htx, as compared with control values (54.1 ± 14.2 and 45.6 ± 9.2 vs. 6.2 ± 1.8 pg/ml, respectively). Significant relationships were observed between plasma BNP and cGMP values (r = 0.62; P < 0.05 and r = 0.75; P < 0.01, in Ltx and Htx) and between BNP and right ventricular fractional shortening and tricuspid E/Ea ratio in Ltx (r = -0.75 and r = 0.93; P < 0.01, respectively). BNP is increased after lung transplantation, like after heart transplantation. The relationships observed suggest that the cardiac hormone might counterbalance possible deleterious effects of lung-transplantation on right functioning of patient's heart. © 2010 European Society for Organ Transplantation.

Enache I.,Institute Of Physiologie | Enache I.,Hopitaux Universitaires | Oswald-Mammosser M.,Institute Of Physiologie | Scarfone S.,Institute Of Physiologie | And 4 more authors.
Respiration | Year: 2011

Background: Studies on the diffusing capacity of the lung for carbon monoxide (DL CO) in obese patients are conflicting, some studies showing increased DL CO and others unaltered or reduced values in these subjects. Objectives: To compare obese patients to controls, examine the contribution of alveolar volume (VA) and CO transfer coefficient (K CO) to DL CO, and calculate DL CO values adjusted for VA. Methods: We measured body mass index (BMI), waist circumference (WC), spirometry and DL CO in 98 adult obese patients without cardiopulmonary or smoking history and 48 healthy subjects. All tests were performed in the same laboratory. Results: Using conventional reference values, mean DL CO and VA were lower (-6%, p < 0.05, and -13%, p < 0.001, respectively), and K CO was higher (+9%, p < 0.05) in obese patients than in controls. VA decreased whereas K CO increased with increasing BMI and WC in the obese group. Patients with lower DL CO had low K CO in addition to decreased VA. In contrast, some obese patients maintained normal VA, which, coupled with high K CO, resulted in higher DL CO. The main result is that diffusion capacity differences between obese patients and controls disappeared using reference equations adjusting DL CO for VA. Conclusions: Using conventional reference equations, our obese patients show slightly lower mean DL CO, lower mean VA and higher mean K CO than controls, but with a large range of DL CO values and patterns. Adjusting DL CO for VA suggests that low lung volumes are the main cause of low DL CO and high K CO values in obese patients. Copyright © 2010 S. Karger AG, Basel.

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