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This work aims to define the basic parameters for the automatic mapping of the channel between the Lagoa do Peixe and the Atlantic Ocean, which is located in the municipalities of Tavares and Mostardas, Rio Grande do Sul state, Brazil. The automatic mapping is based on an unsupervised classification of Landsat 8 satellite images at the Google Earth Engine cloud computing platform. The images used were selected to present both channel situations (opened and closed). Three images were selected with acquisition dates that presented the open channel and three that presented the closed channel. Each image was classified using the K-means clustering method, using separately band 6, band 7 (both located at shortwave infrared - SWIR) and the Normalized Difference Water Index (NDWI). Once the number of clusters must be defined a priori by the analyst, as well as the training sample area, these parameters were tested over the dataset and clustering results were compared. All of the generated clusters maps were analyzed over 10 random points, identifying the clustering hits and errors. Due to the absence of reference maps, all the final clustering maps for each date were compared with the composite true color image from the same acquisition date. The NDWI cluster maps showed the best results in separating water and non-water pixels. [ABSTRACT FROM AUTHOR]

Burn injuries have decreased markedly in high-income countries while the incidence of burns remains high in Low- and Middle-Income Countries (LMICs) where more than 90% of burns are thought to occur. However, the cause of burns in LMIC is poorly documented. The aim was to document the causes of severe burns and the changes over time. A cross-sectional survey was completed for 2014 and 2019 in eight burn centers across Africa, Asia, and Latin America: Cairo, Nairobi, Ibadan, Johannesburg, Dhaka, Kathmandu, Sao Paulo, and Guadalajara. The information summarised included demographics of burn patients, location, cause, and outcomes of burns. In total, 15,344 patients were admitted across all centers, 37% of burns were women and 36% of burns were children. Burns occurred mostly in household settings (43-79%). In Dhaka and Kathmandu, occupational burns were also common (32 and 43%, respectively). Hot liquid and flame burns were most common while electric burns were also common in Dhaka and Sao Paulo. The type of flame burns varies by center and year, in Dhaka, 77% resulted from solid fuel in 2014 while 74% of burns resulted from Liquefied Petroleum Gas in 2019. In Nairobi, a large proportion (32%) of burns were intentional self-harm or assault. The average length of stay in hospitals decreased from 2014 to 2019. The percentage of deaths ranged from 5% to 24%. Our data provide important information on the causes of severe burns which can provide guidance in how to approach the development of burn injury prevention programs in LMIC., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Burn Association.)

Objective: To identify risk factors for the development of hospital-acquired pneumonia (HAP) caused by multidrug-resistant (MDR) bacteria in non-ventilated patients., Methods: This was a retrospective observational cohort study conducted over a three-year period at a tertiary-care teaching hospital. We included only non-ventilated patients diagnosed with HAP and presenting with positive bacterial cultures. Categorical variables were compared with chi-square test. Logistic regression analysis was used to determine risk factors for HAP caused by MDR bacteria., Results: Of the 140 patients diagnosed with HAP, 59 (42.1%) were infected with MDR strains. Among the patients infected with methicillin-resistant Staphylococcus aureus and those infected with methicillin-susceptible S. aureus, mortality was 45.9% and 50.0%, respectively (p = 0.763). Among the patients infected with MDR and those infected with non-MDR gram-negative bacilli, mortality was 45.8% and 38.3%, respectively (p = 0.527). Univariate analysis identified the following risk factors for infection with MDR bacteria: COPD; congestive heart failure; chronic renal failure; dialysis; urinary catheterization; extrapulmonary infection; and use of antimicrobial therapy within the last 10 days before the diagnosis of HAP. Multivariate analysis showed that the use of antibiotics within the last 10 days before the diagnosis of HAP was the only independent predictor of infection with MDR bacteria (OR = 3.45; 95% CI: 1.56-7.61; p = 0.002)., Conclusions: In this single-center study, the use of broad-spectrum antibiotics within the last 10 days before the diagnosis of HAP was the only independent predictor of infection with MDR bacteria in non-ventilated patients with HAP.