Sentence examples for burn index from inspiring English sources
We identified 2893 severe burns patients (burn index ≥10) treated at 583 hospitals between July 2010 and March 2013 using the Japanese diagnosis procedure combination inpatient database.
We therefore only included patients with severe burns (i.e. burn index >10) [15] in the current study.
However, we were able to identify the major factors that potentially affect mortality in patients with severe burns, such as age, sex, burn index, comorbidities, and use of mechanical ventilation [ 5, 20, 22, 26, 28, 33], and the baseline characteristics of selected patients with severe burns were well balanced in the propensity score matched groups.
The baseline patient characteristics in the unmatched groups suggested that antithrombin use was higher in patients with severe burns (e.g. those with higher mortality and higher burn index and those requiring mechanical ventilation, catecholamines, and other treatments).
The burn index takes into consideration both the surface area and thickness of the burn area: burn index = full thickness of total burn-surface area + 1/2 partial thickness of total burn-surface area [15, 19].
The burn index takes both the surface area and thickness of the burned area into consideration: burn index = full thickness of total burn surface area + 1/2 partial thickness of total burn surface area [ 22, 26].
Random forest modeling explained up to 63% of the Rim fire burn variance using seven predictors: time since previous fire, actual evapotranspiration (AET), climatic water deficit (Deficit), previous maximum burn severity, burning index, slope position, and solar radiation.
Low burn rate index (∼0.25) observed with addition of SrCO3 is captured by extending the model to include the effect of binder melt; the gas phase effect is accounted for by calibration against catalytic effect on the fine AP-binder propellant.
The objectives of this study were to (1) conduct field validation and statistical comparisons of the burned index rankings of 2015 wildfire areas near Tanana, Alaska to Landsat burn severity classes mapped (post-fires) in 2015 and 2016, and (2) estimate total ecosystem (live biomass and mineral topsoil) carbon emissions from the 2015 wildfires across the Yukon Koyukuk forest region.
Soil burn severity indexes have been developed to rapidly assess ecosystem damage from vegetation fires and predict associated risks during the post-fire period.
