[⇓][1] 

SERIES “ATS/ERS TASK FORCE: STANDARDISATION OF LUNG FUNCTION TESTING” 

Edited by V. Brusasco, R. Crapo and G. Viegi 

Number 2 in this Series

 [1]: #F13

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Standardisation of spirometry

Background Traditional approaches to mechanical ventilation use tidal volumes of 10 to 15 ml per kilogram of body weight and may cause stretch-induced lung injury in patients with acute lung injury and the acute respiratory distress syndrome. We therefore conducted a trial to determine whether ventilation with lower tidal volumes would improve the clinical outcomes in these patients. Methods Patients with acute lung injury and the acute respiratory distress syndrome were enrolled in a multicenter, randomized trial. The trial compared traditional ventilation treatment, which involved an initial tidal volume of 12 ml per kilogram of predicted body weight and an airway pressure measured after a 0.5-second pause at the end of inspiration (plateau pressure) of 50 cm of water or less, with ventilation with a lower tidal volume, which involved an initial tidal volume of 6 ml per kilogram of predicted body weight and a plateau pressure of 30 cm of water or less. The primary outcomes were death before a patient was discharged home and was breathing without assistance and the number of days without ventilator use from day 1 to day 28. Results The trial was stopped after the enrollment of 861 patients because mortality was lower in the group treated with lower tidal volumes than in the group treated with traditional tidal volumes (31.0 percent vs. 39.8 percent, P=0.007), and the number of days without ventilator use during the first 28 days after randomization was greater in this group (mean [+/-SD], 12+/-11 vs. 10+/-11; P=0.007). The mean tidal volumes on days 1 to 3 were 6.2+/-0.8 and 11.8+/-0.8 ml per kilogram of predicted body weight (P Conclusions In patients with acute lung injury and the acute respiratory distress syndrome, mechanical ventilation with a lower tidal volume than is traditionally used results in decreased mortality and increases the number of days without ventilator use.

Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome.

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

Objective:To provide an update to the “Surviving Sepsis Campaign Guidelines for Management of Severe Sepsis and Septic Shock,” last published in 2008.Design:A consensus committee of 68 international experts representing 30 international organizations was convened. Nominal groups were assembled at ke

Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock: 2012.

The acute respiratory distress syndrome (ARDS) was defined in 1994 by the American-European Consensus Conference (AECC); since then, issues regarding the reliability and validity of this definition have emerged. Using a consensus process, a panel of experts convened in 2011 (an initiative of the European Society of Intensive Care Medicine endorsed by the American Thoracic Society and the Society of Critical Care Medicine) developed the Berlin Definition, focusing on feasibility, reliability, validity, and objective evaluation of its performance. A draft definition proposed 3 mutually exclusive categories of ARDS based on degree of hypoxemia: mild (200 mm Hg < PaO2/FIO2 ≤ 300 mm Hg), moderate (100 mm Hg < PaO2/FIO2 ≤ 200 mm Hg), and severe (PaO2/FIO2 ≤ 100 mm Hg) and 4 ancillary variables for severe ARDS: radiographic severity, respiratory system compliance (≤40 mL/cm H2O), positive end-expiratory pressure (≥10 cm H2O), and corrected expired volume per minute (≥10 L/min). The draft Berlin Definition was empirically evaluated using patient-level meta-analysis of 4188 patients with ARDS from 4 multicenter clinical data sets and 269 patients with ARDS from 3 single-center data sets containing physiologic information. The 4 ancillary variables did not contribute to the predictive validity of severe ARDS for mortality and were removed from the definition. Using the Berlin Definition, stages of mild, moderate, and severe ARDS were associated with increased mortality (27%; 95% CI, 24%-30%; 32%; 95% CI, 29%-34%; and 45%; 95% CI, 42%-48%, respectively; P < .001) and increased median duration of mechanical ventilation in survivors (5 days; interquartile [IQR], 2-11; 7 days; IQR, 4-14; and 9 days; IQR, 5-17, respectively; P < .001). Compared with the AECC definition, the final Berlin Definition had better predictive validity for mortality, with an area under the receiver operating curve of 0.577 (95% CI, 0.561-0.593) vs 0.536 (95% CI, 0.520-0.553; P < .001). This updated and revised Berlin Definition for ARDS addresses a number of the limitations of the AECC definition. The approach of combining consensus discussions with empirical evaluation may serve as a model to create more accurate, evidence-based, critical illness syndrome definitions and to better inform clinical care, research, and health services planning.

Acute respiratory distress syndrome: the Berlin Definition.

Current approaches to classification of left ventricular scar rely on manual segmentation of myocardial borders and manual classification of scar tissue. In this paper, we propose an novel, semi-automatic approach to segment the left ventricular wall and classify scar tissue using a combination of modern image processing techniques. We obtained high-resolution magnetic resonance angiograms (MRA) and late-gadolinium enhanced magnetic resonance imaging (LGE-MRI) in 14 patients who had ventricular scar from a prior myocardial infarction. We applied (1) a level set-based segmentation approach using a combination of the MRA and LGE-MRI to segment the myocardium and then (2) an automated signal intensity algorithm (Otsu thresholding) to identify ventricular scar tissue. We compared results from both steps to those of expert observers. The LV geometry using the semi-automated segmentation method had a mean overlap of 94% with the manual segmentations. The scar volumes obtained with the Otsu method correlated with the expert observer scar volumes (Dice comparison coefficient of 0.85± 0.11). This proof of concept segmentation pipeline provides a more objective method for identifying scar in the left ventricle than manual approaches.

https://www.cinc.org/archives/2014/pdf/0105.pdf

A practical algorithm for improving localization and quantification of left ventricular scar

The goal of the FACETS project (Framework Application for Core-Edge Transport Simulations) was to provide a multiphysics, parallel framework application (FACETS) that will enable whole-device modeling for the U.S. fusion program, to provide the modeling infrastructure needed for ITER, the next step fusion confinement device. Through use of modern computational methods, including component technology and object oriented design, FACETS is able to switch from one model to another for a given aspect of the physics in a flexible manner. This enables use of simplified models for rapid turnaround or high-fidelity models that can take advantage of the largest supercomputer hardware. FACETS does so in a heterogeneous parallel context, where different parts of the application execute in parallel by utilizing task farming, domain decomposition, and/or pipelining as needed and applicable. ParaTools, Inc. was tasked with supporting the performance analysis and tuning of the FACETS components and framework in order to achieve the parallel scaling goals of the project. The TAU Performance System® was used for instrumentation, measurement, archiving, and profile / tracing analysis. ParaTools, Inc. also assisted in FACETS performance engineering efforts. Through the use of the TAU Performance System, ParaTools provided instrumentation, measurement, analysis and archival support for the FACETSmore » project. Performance optimization of key components has yielded significant performance speedups. TAU was integrated into the FACETS build for both the full coupled application and the UEDGE component. The performance database provided archival storage of the performance regression testing data generated by the project, and helped to track improvements in the software development.« less

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Framework Application for Core Edge Transport Simulation (FACETS)

A valve assembly for studying pulmonary function in trauma patients.

Randomized Clinical Trial of Pressure-Controlled Inverse Ratio Ventilation and Extracorporeal CO2 Removal for Adult Respiratory Distress Syndrome

Clinical investigations of anatomy's structural changes over time could greatly benefit from population-level quantification of shape, or spatiotemporal statistic shape modeling (SSM). Such a tool enables characterizing patient organ cycles or disease progression in relation to a cohort of interest. Constructing shape models requires establishing a quantitative shape representation (e.g., corresponding landmarks). Particle-based shape modeling (PSM) is a data-driven SSM approach that captures population-level shape variations by optimizing landmark placement. However, it assumes cross-sectional study designs and hence has limited statistical power in representing shape changes over time. Existing methods for modeling spatiotemporal or longitudinal shape changes require predefined shape atlases and pre-built shape models that are typically constructed cross-sectionally. This paper proposes a data-driven approach inspired by the PSM method to learn population-level spatiotemporal shape changes directly from shape data. We introduce a novel SSM optimization scheme that produces landmarks that are in correspondence both across the population (inter-subject) and across time-series (intra-subject). We apply the proposed method to 4D cardiac data from atrial-fibrillation patients and demonstrate its efficacy in representing the dynamic change of the left atrium. Furthermore, we show that our method outperforms an image-based approach for spatiotemporal SSM with respect to a generative time-series model, the Linear Dynamical System (LDS). LDS fit using a spatiotemporal shape model optimized via our approach provides better generalization and specificity, indicating it accurately captures the underlying time-dependency.

Alan H. Morris

Papers

A practical algorithm for improving localization and quantification of left ventricular scar

Framework Application for Core Edge Transport Simulation (FACETS)

A valve assembly for studying pulmonary function in trauma patients.

Randomized Clinical Trial of Pressure-Controlled Inverse Ratio Ventilation and Extracorporeal CO2 Removal for Adult Respiratory Distress Syndrome

Spatiotemporal Cardiac Statistical Shape Modeling: A Data-Driven Approach