Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

Background: Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies. Methods: In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality. Findings: Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42\ub74% vs 44\ub72%; absolute difference \u20131\ub769 [\u20139\ub758 to 6\ub711] p=0\ub767; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5\u20138] vs 6 [5\u20138] cm H2O; p=0\ub70011). ICU mortality was higher in MICs than in HICs (30\ub75% vs 19\ub79%; p=0\ub70004; adjusted effect 16\ub741% [95% CI 9\ub752\u201323\ub752]; p<0\ub70001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0\ub780 [95% CI 0\ub775\u20130\ub786]; p<0\ub70001). Interpretation: Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status. Funding: No funding

Application of CMC as Thickener on Nanoemulsions Based on Olive Oil: Physical Properties and Stability

Carboxymethyl cellulose (CMC) is a hydrocolloid with surface activity that could act as emulsifiers in oil-in-water emulsions; however the principal role is that it acts as structuring, thickening, or gelling agent in the aqueous phase. This study aims to evaluate the application of CMC as thickener into nanoemulsions based on olive oil and their influence on particle characteristics, flow behavior, and color. Four nanoemulsions with different oil (5% and 15% w/w olive oil) and CMC (0.5% and 0.75% w/w) concentration and two control samples without CMC added were prepared using Tween 80 as emulsifier. All physical properties studied on nanoemulsions were depending on both oil and CMC concentration. In general, z-average particle size varied among 107–121 nm and those samples with 5% oil and CMC were the most polydisperse. The addition of CMC increased anionic charge of nanoemulsions obtaining zeta potential values among −41 and −55 mV. The oil concentration increased both consistency and pseudoplasticity of samples, although samples were more stable to gravitational separation at the highest CMC concentration. Color of nanoemulsions was affected principally by the oil concentration. Finally, the results showed that CMC could be applied in nanoemulsions as thickener increasing their physical stability although modifying their physical properties

Dependent Component Analysis: A Hyperspectral Unmixing

Abstract. Linear unmixing decomposes a hyperspectral image into a collection of reflectance spectra of the materials present in the scene, called endmember signatures, and the corresponding abundance fractions at each pixel in a spatial area of interest. This paper introduces a new unmixing method, called Dependent Component Analysis (DECA), which overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical properties of hyperspectral data. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. The performance of the method is illustrated using simulated and real data.

SAR Moving Objects Trajectory Estimation: Solving the Blind Angle Ambiguity with a Single Sensor

The Fisher information matrix for the unknown moving targets velocity parameters is computed as function of the antenna radiation pattern. The resultant matrix is analysed and the characteristics that the antenna gain should exhibit in order to enhance the estimation of the unknown moving objects velocity vector are deduced. Simulation results comparing the various antenna radiation patterns envisioning the velocity vector estimation using a single SAR sensor are presented