(1) Background: Burn injuries in children present a significant public health concern due to their potential for severe physical and psychological impact. (2) Methods: This study investigates the determinants of pediatric burn severity by analyzing the interplay of demographic and environmental factors. Through a retrospective analysis of pediatric burn cases over five years, encompassing patient demographics, burn causative agents, and clinical outcomes, this research aims to identify significant predictors of burn severity. (3) Results: This study presents a comprehensive analysis of pediatric burn injuries, focusing on the severity, clinical outcomes, and multifactorial aspects influencing recovery. We reviewed 1498 pediatric burn cases from January 2015 to December 2020. The mean age of patients was 5.8 years, with a slight male predominance (54%). Scalds (45%), flame burns (30%), and contact burns (15%) were the most common burn types. Our findings indicate significant differences in burn severity based on TBSA, with 32.5% of cases having TBSA greater than 20%. Multivariate logistic regression identified rural residence, male gender, flame burns, and lower socioeconomic status as significant predictors of severe burn outcomes. The overall mortality rate was 2.5%, with higher rates among patients with TBSA greater than 40%. These results highlight the need for targeted prevention strategies and improved access to specialized burn care. (4) Conclusions: Understanding these factors can inform targeted prevention strategies and improve treatment protocols.

UNASSIGNED: Burns are a prevalent form of unintentional injury and a significant public health concern in developing countries. We aimed to investigate the epidemiological and clinical characteristics of adult burn patients at a major center in Eastern China.
UNASSIGNED: This 6-year retrospective study analyzed patients with varying degrees of burns between January 2017 and December 2022 at the Suzhou Burns and Trauma Center. The study extracted demographic, clinical, and epidemiological data from electronic medical records for analysis.
UNASSIGNED: The study included 3,258 adult patients, of which 64.3% were male. The largest age group affected 30-59-year-old adults (63.04%). Scalds were the leading cause of burns (1,346, 41.31%), followed by flames (1,271, 39.01%). The majority of burn hospitalizations were those with moderate burns (1791, 54.97%). The morbidity rate was low at 0.68%, while mortality was strongly associated with age, etiology, and total body surface area. Patients with certain types of burns, such as explosions, hot crush injuries, and electric burns had more operations, longer lengths of hospital stay, and higher costs compared to those with scalds and flame injuries.
UNASSIGNED: Different prevention strategies should be formulated according to different etiologies, ages, and genders.

Temperate heathlands and blanket bogs are globally rare and face growing wildfire threats. Ecosystem impacts differ between low and high severity fires, where severity reflects immediate fuel consumption. This study assessed factors influencing fire severity in Scottish heathlands and blanket bogs, including the efficacy of the Canadian Fire Weather Index System (CFWIS). Using remote sensing, we measured the differenced Normalised Burn Ratio at 92 wildfire sites from 2015 to 2021. We used Generalised Additive Mixed Models to investigate the impact of topography, habitat wetness, CFWIS components and 30-day weather on severity. Dry heath exhibited higher severity than wet heath and blanket bog, and slope, elevation and south facing aspect were positively correlated to severity. Weather effects were less clear due to data scale differences, yet still indicated weather\'s significant role in severity. Rainfall had an increasingly negative effect from approximately 15 days before the fire, whilst temperature had an increasingly positive effect. Vapour Pressure Deficit (VPD) was the weather variable with highest explanatory value, and predicted severity better than any CFWIS component. The best-explained fire severity model (R2 = 0.25) incorporated topography, habitat wetness wind and VPD on the day of the fire. The Drought Code (DC), predicting organic matter flammability at ≥10 cm soil depth, was the CFWIS component with the highest predictive effect across habitats. Our findings suggest that wildfires in wet heath and blanket bogs are typically characterised by low severity, but that warmer, drier weather may increase the risk of severe, smouldering fires which threaten peatland carbon stores.

The aim of this study was to investigate the moderating role of gender in the relationship between burn severity, perceived stigmatization and depressive symptoms at multiple time points postburn.
This multi-center study included data from two cohorts. Cohort 1 consisted of 215 burn survivors, participating in a longitudinal study with measures at 3 and 12 months postburn. Cohort 2 consisted of 180 burn survivors cross-sectionally assessed at 5 - 7 years postburn. Both cohorts completed self-reported measures of perceived stigmatization and depressive symptoms. The number of acute surgeries (i.e., no surgery, 1 surgery or 2 or more surgeries) was used as indicator of burn severity. Relations between number of surgeries, depressive symptoms, and perceived stigmatization, including possible indirect effects, were evaluated with gender-specific path models.
In both men and women, number of surgical operations was related to higher levels of depressive symptoms and perceived stigmatization at 3 months after burn. In women, number of operations was still directly related to both constructs at 12 months after burn, which was cross-sectionally confirmed in the 5-7 years after burn cohort. In men, from 3 to 12 months after burn, depressive symptoms and perceived stigmatization were bidirectionally related, and, through these effects, number of surgeries was indirectly related to both outcomes. In the cross-sectional 5-7 years after burn cohort, number of operations was related to stigma but not to depressive symptoms of men.
Number of operations had a different effect on psychosocial adaptation of male and female burn survivors. In women, a persistent direct link from number of operations to both depressive symptoms and perceived stigmatization was found over time. In men, the effect of number of operations was most evident in the short-term, after which perceived stigmatization and depressive symptoms became interrelated. This indicates that burn severity remains a factor of significance in psychological adjustment in women, whereas in men, this significance seems to decrease over time.

Wildfires are pivotal to the functioning of many ecosystems globally, including the magnitude of surface erosion rates. This study aims to investigate the relationships between surface erosion rates and wildfire intensity in the tropical north savanna of Australia. The occurrence of fires in western Arnhem Land, Northern Territory, Australia was determined with remotely sensed digital datasets as well as analogue erosion measurement methods. Analysis was performed using satellite imagery to quantify burn severity via a monthly delta normalised burn ratio (dNBR). This was compared and correlated against on-ground erosion measurements (erosion pins) for 13 years. The dNBR for each year (up to +0.4) displayed no relationship with subsequent erosion (up to ±4 mm of erosion/deposition per year). Poor correlation was attributed to low fire severity, patchy burning, significant time between fires and erosion-inducing rainfall. Other influences included surface roughness from disturbances from feral pigs and cyclone impacts. The findings here oppose many other studies that have found that fires increase surface erosion. This accentuates the unique ecosystem characteristics and fire regime properties found in the tropical Northern Territory. Scenarios of late dry season fires with high severity were not observed in this study and require more investigations. Ecosystems such as the one examined here require specialised management practices acknowledging the specific ecosystem functions and processes. The methods employed here combine both analogue and digital sensors to improve understandings of a unique environmental system.

UNASSIGNED: Over the past decade, machine learning (ML) algorithms have rapidly become much more widespread for numerous biomedical applications, including the diagnosis and categorization of disease and injury.
UNASSIGNED: Here, we seek to characterize the recent growth of ML techniques that use imaging data to classify burn wound severity and report on the accuracies of different approaches.
UNASSIGNED: To this end, we present a comprehensive literature review of preclinical and clinical studies using ML techniques to classify the severity of burn wounds.
UNASSIGNED: The majority of these reports used digital color photographs as input data to the classification algorithms, but recently there has been an increasing prevalence of the use of ML approaches using input data from more advanced optical imaging modalities (e.g., multispectral and hyperspectral imaging, optical coherence tomography), in addition to multimodal techniques. The classification accuracy of the different methods is reported; it typically ranges from ∼70% to 90% relative to the current gold standard of clinical judgment.
UNASSIGNED: The field would benefit from systematic analysis of the effects of different input data modalities, training/testing sets, and ML classifiers on the reported accuracy. Despite this current limitation, ML-based algorithms show significant promise for assisting in objectively classifying burn wound severity.

Many fire-prone forests are experiencing wildfires that burn outside the historical range of variation in extent and severity. These fires impact pollinators and the ecosystem services they provide, but how the effects of fire are mediated by burn severity in different habitats is not well understood. We used generalized linear mixed models in a Bayesian framework to model the abundance of pollinators as a function of burn severity, habitat, and floral resources in post-fire, mid-elevation, conifer forest, and meadow in the Sierra Nevada, California. Although most species-level effects were not significant, we found highly consistent negative impacts of burn severity in meadows where pollinators were most abundant, with only hummingbirds and some butterfly families responding positively to burn severity in meadows. Moderate-severity fire tended to increase the abundance of most pollinator taxa in upland forest habitat, indicating that even in large fires that burn primarily at high- and moderate-severity patches may be associated with improved habitat conditions for pollinator species in upland forest. Nearly all pollinator taxa responded positively to floral richness but not necessarily to floral abundance. Given that much of the Sierra Nevada is predicted to burn at high severity, limiting high-severity effects in meadow and upland habitats may help conserve pollinator communities whereas low- to moderate-severity fire may be needed in both systems.

Understanding the landscape patterns of burn severity is vital for managing fire-prone ecosystems. Relatively limited research has been done about fire and burn severity patterns in subtropical forests. Here, we derived the pre-fire forest type data from a global land-cover product at 30 m resolution based on time-series Landsat imageries. Using Landsat 8 OLI remote sensing imagery and field-based composite burn index (CBI), this study spatially mapped the burn severity of 27 forest fires in the subtropical forest ecosystems in southern China from 2017 to 2021. The landscape pattern of patches with different burn severity was quantified using landscape indices. In addition, factors influencing the patterns of burn severity across the landscape were determined using the Geodetector model. Burn severity of patches varied significantly over space. High burn severity was common in forest patches with low fragmentation, low patch density, and regular shape. In contrast, moderate and low burn severity was prevalent in patches with smaller patch size, high patch density, and complex shapes. Extensively burned forest patches were located at higher elevations, while more fragmented patches were located in gently sloping areas. Topographic factors were the most significant factors influencing variances in burn severity across the forest patches, followed by weather conditions. Compared to low elevation areas, vegetation types at the high elevation areas (dominated by Masson pine) are more singular, with higher fuel loads, thus resulting in a more regularly-shaped distribution of highly severe burning patches. A detailed understanding of burn severity patterns and driving factors in a landscape can help develop sustainable forest management and restoration strategies. Practically, fire managers should conduct mechanical fuel treatments or thinning of forests at high-elevation areas to reduce the potential of severe fire behavior and the continuity of fire spread.

Wildfires alter the structure and functioning of ecosystems through changes in their biotic and abiotic components. A deeper understanding recovery process concerning diverse communities and properties within these components can provide valuable insights into the ecological effects of wildfires. Therefore, it is appropriate to enhance our understanding of the resilience of bacterial communities after wildfires within Mediterranean ecosystems. In this research, soil bacterial community resilience was evaluated in three types of ecosystems for two fire severities, two years after a large wildfire in Mediterranean ecosystems. The resilience of the soil bacterial community refers to its ability to return to original state after disturbance. This capacity can be estimated by the study of its recovery over time. In this study we evaluated the resilience using the variables: alpha diversity, beta diversity and the changes in abundance of both OTUs (Operational Taxonomic Units) and principal bacterial taxa (phyla, classes or orders). Our results showed that resilience depends on fire severity and type of ecosystem. We studied three ecosystems with different stage in the secondary succession: low maturity shrublands and heathlands, and high maturity oak forests. In general, high resilience in the soil bacterial community was observed in heathlands under low and high fire severity conditions. The other two ecosystems were resilient only under low fire severity. Stochastic replacement of the abundance of the OTUs was observed in all three ecosystems, with a notable impact on oak forests, under during high-severity conditions.

Due to complex interactions between climate and land use changes, large forest fires have increased in frequency and severity over the last decades, impacting dramatically on biodiversity and society. In southern European countries affected by demographic challenges, fire risk and danger play special relevance at the wildland-urban interfaces (WUIs), where decision-making and land management have strong socio-ecological implications. WUIs have been historically typified according to both fire occurrence probability and settlement vulnerability, but those classifications lack generality regarding fire regime components. We aim to develop an integrated and comprehensive scheme for identifying the WUI typologies most at risk to fire severity across large territories. We selected fourteen large wildfires (over than 500 ha) occurred in Spain (2016-2021) containing different WUI scenarios. First, based on a building cartography and a multi-temporal series of Sentinel-2 imagery, each WUI was delimited and spatially characterized according to building density and pre-fire fuel characteristics (type, amount, and structure). Afterwards, a decision tree regression model was applied to identify the most relevant pre-fire vegetation parameters driving burn severity. The combined effect of the selected pre-fire vegetation drivers and the building density patterns on fire severity was evaluated using linear mixed models. Finally, the WUI typologies most prone to high burn severity were recognized using Tukey post-hoc tests. Results indicated that building density, land cover class and vegetation cover fraction determined fire severity in areas close to human settlements. Specifically, isolated, scattered and sparsely clustered buildings enclosed in a high-cover shrub matrix were the WUI typologies most susceptible to high-severity fires. These findings contribute to the development of appropriate strategies to minimize the risk of severe fires in WUIs and avoid potential losses of multiple ecosystem services valuable for society.