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The Development of a Probabilistic Dose-Response for a Burn Injury Model.

Objective: The objective was to augment a burn injury model, BURNSIM, with probabilistic dose-response risk curves.Methods: To develop the dose-response, we drew on a considerable amount of historical porcine burn injury data collected by U.S. Army Aeromedical Research Laboratory in the 1970s. The e...

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Published in:Military Medicine Vol. 182; pp. 202 - 210
Main Authors: Iyoho, Anthony, Ng, Laurel, Chan, Philemon
Format: equations & formulas research tables/charts Journal Article
Published: Oxford University Press / USA 2017 Supplement
Online Access:View this record in EBSCOhost
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      dt: 2017 Supplement
      vid: 182
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      pub: Oxford University Press / USA
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        atl: The Development of a Probabilistic Dose-Response for a Burn Injury Model.
      aug:
        au:
          Iyoho, Anthony
          Ng, Laurel
          Chan, Philemon
        affil: L-3 Applied Technologies Inc., 10180 Barnes Canyon Road, Suite 100, San Diego, CA 92121-5701.
      sug:
        subj:
          Burns Classification
          Patient Simulation
          Models, Biological
          Burns Diagnosis
          Burns Physiopathology
          Time Factors
          Logistic Regression
          Skin Temperature
          Animals
          Swine
          Burns Complications
          Reproducibility of Results
          Resource Databases
          Animal Studies
      ab: Objective: The objective was to augment a burn injury model, BURNSIM, with probabilistic dose-response risk curves.Methods: To develop the dose-response, we drew on a considerable amount of historical porcine burn injury data collected by U.S. Army Aeromedical Research Laboratory in the 1970s. The experimental parameters of each usable data point served as inputs to BURNSIM to calculate the burn damage integral (i.e., the internal dose) for 4 severities (mild, intermediate, deep second- and third-degree burns). The binary probability response was constructed and logistic regression was applied to generate the respective dose-response. Historic data collected at the University of Rochester in the 1950s were used for validation.Results: Four dose-response curves were generated, ranging from mild to third degree, with tight 95% confidence bands for mild to deep second degree, and slightly wider bands for third degree. Parametric sensitivity analysis revealed that epidermal and whole skin thicknesses, skin temperature, and blood flow rate have a large effect on predicted outcomes.Conclusions: Addition of dose-response curves provides a critical augmentation to BURNSIM to improve operational risk assessments of burn hazard. Future recommendations for BURNSIM include the use of body location- and gender-specific parameters with coupling to a thermoregulatory model.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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