Practical Computer Vision Application to Compute Total Body Surface Area Burn

Choi, Jeff; Patil, Advait; Vendrow, Edward; Touponse, Gavin; Aboukhater, Layla M.; Forrester, Joseph D.; Spain, David A.

doi:10.1001/jamasurg.2021.5848

Cited by 8 publications

(2 citation statements)

References 43 publications

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“…Notably, the rule of 9 s and more accurate Lund-Browder charts are both derived from paper-mâché molds from only 12 individuals ( 52 ). Very recently, our understanding of the human skin surface has been substantially advanced by high-resolution surface anthropometry laser body scans of 3,047 adults in the Civilian American and European Surface Anthropometry Resource ( 53 ), which proved that there is an enormous variability between individuals as to how much each body region contributes to the total BSA. Thus, regardless of evaluation by a dermatologist or in the burn unit, knowing the true BSA of an individual SJS/TEN patient is challenging.…”

Section: Updates In Diagnosis Assessment and Causalitymentioning

confidence: 99%

Updates in SJS/TEN: collaboration, innovation, and community

Marks,

Botta,

Abe

et al. 2023

Front. Med.

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Stevens-Johnson Syndrome/Toxic Epidermal Necrolysis (SJS/TEN) is a predominantly drug-induced disease, with a mortality rate of 15–20%, that engages the expertise of multiple disciplines: dermatology, allergy, immunology, clinical pharmacology, burn surgery, ophthalmology, urogynecology, and psychiatry. SJS/TEN has an incidence of 1–5/million persons per year in the United States, with even higher rates globally. One of the challenges of SJS/TEN has been developing the research infrastructure and coordination to answer questions capable of transforming clinical care and leading to improved patient outcomes. SJS/TEN 2021, the third research meeting of its kind, was held as a virtual meeting on August 28–29, 2021. The meeting brought together 428 international scientists, in addition to a community of 140 SJS/TEN survivors and family members. The goal of the meeting was to brainstorm strategies to support the continued growth of an international SJS/TEN research network, bridging science and the community. The community workshop section of the meeting focused on eight primary themes: mental health, eye care, SJS/TEN in children, non-drug induced SJS/TEN, long-term health complications, new advances in mechanisms and basic science, managing long-term scarring, considerations for skin of color, and COVID-19 vaccines. The meeting featured several important updates and identified areas of unmet research and clinical need that will be highlighted in this white paper.

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Section: Updates In Diagnosis Assessment and Causalitymentioning

confidence: 99%

Updates in SJS/TEN: collaboration, innovation, and community

Marks,

Botta,

Abe

et al. 2023

Front. Med.

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“…Evaluating clinical utility usually requires further prospective validation across multiple settings (eg, efficacy and incremental value assessment), further tool calibration, and societal utility assessment (eg, cost-benefit or cost-effectiveness analysis), which we hope the authors will pursue. Bedside usability (eg, mobile applications) should be considered at the onset of prediction tool design to facilitate these real-world evaluations. Ensuring the tools that impact clinical decision-making are trustworthy will require developers, reviewers, and users to be familiar with the rigor required for thoughtful prediction tool development and validation.…”

mentioning

confidence: 99%

Clinical Prediction Tools in Trauma: Where Do We Go From Here?

Choi

Forrester

2022

JAMA Netw Open

Self Cite

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Expeditious hemorrhage control is a fundamental tenet of trauma surgery. Every minute delayed before an emergency laparotomy for hemorrhage control has been associated with an increased probability of mortality. 1 Gutierrez et al 2 developed and validated a much needed tool to identify patients at risk of requiring early laparotomy within 2 hours of hospital arrival after injury. The Prehopsital Preparation for Surgery (PREPS) Score was derived using encounters of adults aged 18 years or older in the 2017 Trauma Quality Improvement Program database. The PREPS Score (0-20) comprised 7 binary variables, with factors more strongly associated with early laparotomy contributing more points and input variables that could be used by emergency medical service (EMS) technicians in the field.Building this type of clinical tool requires thoughtful study design. First, the tool should have the potential to alter clinical decision-making. The PREP Score certainly meets this criterion; early identification of patients requiring emergency laparotomy may help hospitals mobilize resources, ensure patients are triaged to appropriate centers, and alert clinicians to patients with a higher likelihood of deterioration. Second, variable selection must follow an a priori determined and statistically sound approach. Including too many variables in a model risks overfitting and lacks practicality. In addition to the variable selection strategy used by Gutierrez et al, 2 other strategies can be used, ranging from removing variables with near-zero variance to regularization and other machine learning algorithms. [3][4][5] Third, model validity must be assessed using appropriate performance metrics. Various performance metrics exist, including the C-statistic, which the authors used. The C-statistic is equivalent to area under the receiver operating characteristic curve (AUROC) for binary outcomes, a frequently reported yet commonly misunderstood value. Derived from the area under the curve plotting sensitivity (true positive rate) vs 1 − specificity (false positive rate), AUROC denotes the probability that a randomly selected point in the positive class will be scored higher than a randomly selected point in the negative class. While the concept that a higher C-statistic or AUROC close to 1 indicates good performance, applying the value itself for clinical decision-making is challenging.Alternative performance metrics rather than AUROC or C-statistic may be more interpretable.For example, if the cost of a false negative is high (eg, most screening tools), sensitivity or recall would be an appropriate performance metric to evaluate, while precision would be the more informative metric if the cost of a false positive is high (eg, if positive result necessitates invasive or high-risk intervention). Class imbalance (the ratio of positives to negatives in the study population) is an important consideration when choosing the performance metric. For example, in scenarios with few positives, accuracy would be a misleading metric. If a tool always ...

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Application of multiple deep learning models for automatic burn wound assessment

Che

Lai

et al. 2023

Burns

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Practical Computer Vision Application to Compute Total Body Surface Area Burn

Cited by 8 publications

References 43 publications

Updates in SJS/TEN: collaboration, innovation, and community

Updates in SJS/TEN: collaboration, innovation, and community

Clinical Prediction Tools in Trauma: Where Do We Go From Here?

Application of multiple deep learning models for automatic burn wound assessment

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