Adherence to the emergency management of severe burns referral criteria in burn patients admitted to a hospital with or without a specialized burn center

Yperen, Daan T van; Lieshout, Esther M.M. Van; Nugteren, Leendert H T; Plaisier, Annemarie; Verhofstad, Michael H J; Vlies, Cornelis H. van der

doi:10.1016/j.burns.2021.02.023

Cited by 10 publications

(6 citation statements)

References 11 publications

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“…These criteria have been designed as a support tool for clinicians to decide whether a patient should be referred to a specialized burn center. Adherence to the EMSB referral criteria for patients presented to a non-burn center was 70.0% [2].…”

Section: Introductionmentioning

confidence: 99%

Epidemiology of burn patients admitted in the Netherlands: a nationwide registry study investigating incidence rates and hospital admission from 2014 to 2018

Yperen

Lieshout

Verhofstad

et al. 2021

Eur J Trauma Emerg Surg

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Purpose The aim of this study was to gain insight into the epidemiology of burn patients admitted to a hospital without a burn center or referred to a burn center. Methods This retrospective, nationwide, cohort study included patients with burns or inhalation trauma, admitted between 2014 and 2018, from a national trauma registry. The primary outcome measure was admission to a hospital with or without a burn center. Secondary outcome measures were patient and injury characteristics, Intensive Care Unit (ICU) admission and length of stay, and hospital length of stay (HLOS). Results Of the 5524 included patients, 2787 (50.4%) were treated at a non-burn center, 1745 (31.6%) were subsequently transferred to a burn center, and 992 (18.0%) were primarily presented and treated at a burn center. The annual number of patients decreased from 1199 to 1055 (− 12.4%). At all admission locations, a clear incidence peak was observed in children ≤ 4 years and in patients of ≥ 80 years. The number of ICU admissions for the entire population increased from 201 to 233 (33.0%). The mean HLOS for the entire population was 8 (SD 14) days per patient. This number remained stable over the years in all groups. Conclusion Half of all burn patients were admitted in a non-burn center and the other half in a burn center. The number and incidence rate of patients admitted with burns or inhalation trauma decreased over time. An increased incidence rate was found in children and elderly. The number of patients admitted to the ICU increased, whereas mean hospital length of stay remained stable.

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Section: Introductionmentioning

confidence: 99%

Epidemiology of burn patients admitted in the Netherlands: a nationwide registry study investigating incidence rates and hospital admission from 2014 to 2018

Yperen

Lieshout

Verhofstad

et al. 2021

Eur J Trauma Emerg Surg

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“…Since these centers are accepted as reference centers all over the world, the indications for referral and hospitalization to the burn center were determined with reference to certain clinical guidelines. Some studies have shown that it is very important that the initial evaluation of the burn patient is carried out in accordance with the published and applied referral and hospitalization guidelines (8). Evaluation of the patient as severe or mild may lead to unnecessary referral of the patient to the burn center or to long-term negative consequences, including death.…”

Section: Discussionmentioning

confidence: 99%

Outcomes of Consultations to Burn Units from Emergency Service

Akın¹,

Yastı²

2022

acmr

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Background: In addition to being painful, burns cause aesthetic anxiety, causing patients to apply to the emergencies as soon as it occurs, and their first interventions are made in the emergency. In this study, the compliance with the guidelines in the consultations requested from the burn center and the referral of the patients to the center was evaluated.Methods: Burn etiology, TBSA, burn depth, and area of adult patients were recorded, applied to our hospital's emergency with burns in 2019 and 2020, and were asked for consultation from the burn center.Results: Within two years, consultation was requested from the burn center for a total of 288 patients. Of the consulted patients, 73 (25.3%) were admitted to the center. When the evaluation was made between the patients who were hospitalized and not, the burn depth, etiology, and the percentage of TBSA were statistically significant. Conclusions:Indications for referral and hospitalization to burn centers have been determined with specific clinical guidelines. A significant result that stands out in this study is that 215 out of 288 consultations requested from the burn center didn't have an indication for hospitalization. With this study, the necessity of reconsidering the tendency to ask for a consultation has emerged. Emergency medicine physicians should be well-equipped with minor burn dressings as well as having knowledge about first response, referral decision and management. In this regard, if there is a burn unit/center in university hospitals or education hospitals, rotation of emergency medicine residents to burn treatment units should be discussed.

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“…The main symptoms include redness, pain, and minor swelling. Healing usually occurs within a few days without scarring 1 . Deep dermal burn affects the epidermis and part of the dermis (the second layer of skin).…”

Section: Introductionmentioning

confidence: 99%

Spatial attention-based residual network for human burn identification and classification

Yadav

Aljrees

Kumar

et al. 2023

Sci Rep

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Diagnosing burns in humans has become critical, as early identification can save lives. The manual process of burn diagnosis is time-consuming and complex, even for experienced doctors. Machine learning (ML) and deep convolutional neural network (CNN) models have emerged as the standard for medical image diagnosis. The ML-based approach typically requires handcrafted features for training, which may result in suboptimal performance. Conversely, DL-based methods automatically extract features, but designing a robust model is challenging. Additionally, shallow DL methods lack long-range feature dependency, decreasing efficiency in various applications. We implemented several deep CNN models, ResNeXt, VGG16, and AlexNet, for human burn diagnosis. The results obtained from these models were found to be less reliable since shallow deep CNN models need improved attention modules to preserve the feature dependencies. Therefore, in the proposed study, the feature map is divided into several categories, and the channel dependencies between any two channel mappings within a given class are highlighted. A spatial attention map is built by considering the links between features and their locations. Our attention-based model BuRnGANeXt50 kernel and convolutional layers are also optimized for human burn diagnosis. The earlier study classified the burn based on depth of graft and non-graft. We first classified the burn based on the degree. Subsequently, it is classified into graft and non-graft. Furthermore, the proposed model performance is evaluated on Burns_BIP_US_database. The sensitivity of the BuRnGANeXt50 is 97.22% and 99.14%, respectively, for classifying burns based on degree and depth. This model may be used for quick screening of burn patients and can be executed in the cloud or on a local machine. The code of the proposed method can be accessed at https://github.com/dhirujis02/Journal.git for the sake of reproducibility.

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Adherence to the emergency management of severe burns referral criteria in burn patients admitted to a hospital with or without a specialized burn center

Cited by 10 publications

References 11 publications

Epidemiology of burn patients admitted in the Netherlands: a nationwide registry study investigating incidence rates and hospital admission from 2014 to 2018

Epidemiology of burn patients admitted in the Netherlands: a nationwide registry study investigating incidence rates and hospital admission from 2014 to 2018

Outcomes of Consultations to Burn Units from Emergency Service

Spatial attention-based residual network for human burn identification and classification

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