Leptospirosis: An Unusual Cause of ARDS

Severe leptospirosis usually associates shock, jaundice, renal failure, and thrombocytopenia. Massive hemoptysis due to diffuse alveolar haemorrhage may rarely occur leading to an acute respiratory failure and multiple organ failure. We present the case of an acute respiratory distress syndrome caused by a severe leptospirosis. The severity of the respiratory failure contrasted with the absence of significant liver or renal dysfunction. Bedside open lung biopsy was only consistent with a postinfectious BOOP. The diagnosis was retrospective when the niece of the patient presented with similar inaugural symptoms ten days later after being scratched by a wild rat which was considered by our patient as a pet

Uncertainty quantification in virtual surgery hemodynamics predictions for single ventricle palliation.

International audienceThe adoption of simulation tools to predict surgical outcomes is increasingly leading to questions about the variability of these predictions in the presence of uncertainty associated with the input clinical data. In the present study, we propose a methodology for full propagation of uncertainty from clinical data to model results that, unlike deterministic simulation, enables estimation of the confidence associated with model predictions.We illustrate this problem in a virtual stage II single ventricle palliation surgery example. First, probability density functions (PDFs) of right pulmonary artery (PA) flow split ratio and average pulmonary pressure are determined from clinical measurements, complemented by literature data. Starting from a zero dimensional semi-empirical approximation, Bayesian parameter estimation is used to find the distributions of boundary conditions that produce the expected PA flow split and average pressure PDFs as pre-operative model results. To reduce computational cost, this inverse problem is solved using a Kriging approximant. Second, uncertainties in the boundary conditions are propagated to simulation predictions. Sparse grid stochastic collocation is employed to statistically characterize model predictions of post-operative hemodynamics in models with and without PA stenosis. The results quantify the statistical variability in virtual surgery predictions, allowing for placement of confidence intervals on simulation outputs

Uncertainty quantification in virtual surgery hemodynamics predictions for single ventricle palliation.

International audienceThe adoption of simulation tools to predict surgical outcomes is increasingly leading to questions about the variability of these predictions in the presence of uncertainty associated with the input clinical data. In the present study, we propose a methodology for full propagation of uncertainty from clinical data to model results that, unlike deterministic simulation, enables estimation of the confidence associated with model predictions.We illustrate this problem in a virtual stage II single ventricle palliation surgery example. First, probability density functions (PDFs) of right pulmonary artery (PA) flow split ratio and average pulmonary pressure are determined from clinical measurements, complemented by literature data. Starting from a zero dimensional semi-empirical approximation, Bayesian parameter estimation is used to find the distributions of boundary conditions that produce the expected PA flow split and average pressure PDFs as pre-operative model results. To reduce computational cost, this inverse problem is solved using a Kriging approximant. Second, uncertainties in the boundary conditions are propagated to simulation predictions. Sparse grid stochastic collocation is employed to statistically characterize model predictions of post-operative hemodynamics in models with and without PA stenosis. The results quantify the statistical variability in virtual surgery predictions, allowing for placement of confidence intervals on simulation outputs

Predictive modeling of the virtual Hemi-Fontan operation for second stage single ventricle palliation: Two patient-specific cases

Single ventricle hearts are congenital cardiovascular defects in which the heart has only one functional pumping chamber. The treatment for these conditions typically requires a three-staged operative process where Stage 1 is typically achieved by a shunt between the systemic and pulmonary arteries, and Stage 2 by connecting the superior venous return to the pulmonary circulation. Surgically, the Stage 2 circulation can be achieved through a procedure called the Hemi-Fontan, which reconstructs the right atrium and pulmonary artery to allow for an enlarged confluence with the superior vena cava. Based on pre-operative data obtained from two patients prior to Stage 2 surgery, we developed two patient-specific multi-scale computational models, each including the 3D geometrical model of the surgical junction constructed from magnetic resonance imaging, and a closed-loop systemic lumped-parameter network derived from clinical measurements. “Virtual” Hemi-Fontan surgery was performed on the 3D model with guidance from clinical surgeons, and a corresponding multi-scale simulation predicts the patient\u27s post-operative hemodynamic and physiologic conditions. For each patient, a post-operative active scenario with an increase in the heart rate (HR) and a decrease in the pulmonary and systemic vascular resistance (PVR and SVR) was also performed. Results between the baseline and this “active” state were compared to evaluate the hemodynamic and physiologic implications of changing conditions. Simulation results revealed a characteristic swirling vortex in the Hemi-Fontan in both patients, with flow hugging the wall along the SVC to Hemi-Fontan confluence. One patient model had higher levels of swirling, recirculation, and flow stagnation. However, in both models, the power loss within the surgical junction was less than 13% of the total power loss in the pulmonary circulation, and less than 2% of the total ventricular power. This implies little impact of the surgical junction geometry on the SVC pressure, cardiac output, and other systemic parameters. In contrast, varying HR, PVR, and SVR led to significant changes in theses clinically relevant global parameters. Adopting a work-flow of customized virtual planning of the Hemi-Fontan procedure with patient-specific data, this study demonstrates the ability of multi-scale modeling to reproduce patient specific flow conditions under differing physiological states. Results demonstrate that the same operation performed in two different patients can lead to different hemodynamic characteristics, and that modeling can be used to uncover physiologic changes associated with different clinical conditions

Integration of Clinical Data Collected at Different Times for Virtual Surgery in Single Ventricle Patients: A Case Study

International audienceNewborns with single ventricle physiology are usually palliated with a multi-staged procedure. When cardiovascular complications e.g., collateral vessel formation occur during the inter-stage periods, further treatments are required. An 8-month-old patient, who underwent second stage (i.e., bi-directional Glenn, BDG) surgery at 4 months, was diagnosed with a major veno-venous collateral vessel (VVC) which was endovascularly occluded to improve blood oxygen saturations. Few clinical data were collected at 8 months, whereas at 4 months a more detailed data set was available. The aim of this study is threefold: (i) to show how to build a patient-specific model describing the hemodynamics in the presence of VVC, using patient-specific clinical data collected at different times; (ii) to use this model to perform virtual VVC occlusion for quantitative hemodynamics prediction; and (iii) to compare predicted hemodynamics with post-operative measurements. The three-dimensional BDG geometry, resulting from the virtual surgery on the first stage model, was coupled with a lumped parameter model (LPM) of the 8-month patient's circulation. The latter was developed by scaling the 4-month LPM to account for changes in vascular impedances due to growth and adaptation. After virtual VVC closure, the model confirmed the 2 mmHg BDG pressure increase, as clinically observed, suggesting the importance of modeling vascular adaptation following the BDG procedure

Le pseudopilus (biogenèse, structure et fonction dans la sécrétion)

PARIS-BIUSJ-Thèses (751052125) / SudocPARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF