Skip to content

Raising suspicion of maltreatment from burns: derivation and validation of the BuRN-Tool

Research output: Contribution to journalArticle (Academic Journal)

Original languageEnglish
Pages (from-to)335-343
Number of pages9
JournalBurns
Volume44
Issue number2
Early online date14 Sep 2017
DOIs
DateAccepted/In press - 25 Aug 2017
DateE-pub ahead of print - 14 Sep 2017
DatePublished (current) - 1 Mar 2018

Abstract

Background: 10–25% of childhood burns arise from maltreatment. Aim: To derive and validate a clinical prediction tool to assist the recognition of suspected maltreatment. Methods: Prospectively collected data from 1327 children with burns were analyzed using logistic regression. Regression coefficients for variables associated with ‘referral for child maltreatment investigation’ (112 cases) in multivariable analyses were converted to integers to derive the BuRN-Tool, scoring each child on a continuous scale. A cut-off score for referral was established from receiver operating curve analysis and optimal sensitivity and specificity values. We validated the BuRN-Tool on 787 prospectively collected novel cases. Results: Variables associated with referral were: age <5 years, known to social care, concerning explanation, full thickness burn, uncommon body location, bilateral pattern and supervision concern. We established 3 as cut-off score, resulting in a sensitivity and specificity for scalds of 87.5% (95% CI:61.7–98.4) and 81.5% (95% CI:77.1–85.4) respectively and for non-scalds sensitivity was 82.4% (95%CI:65.5–93.2) and specificity 78.7% (95% CI:73.9–82.9) when applied to validation data. Area under the curve was 0.87 (95% CI:0.83–0.90) for scalds and 0.85 (95% CI:0.81–0.88) for non-scalds. Conclusion: The BuRN-Tool is a potential adjunct to clinical decision-making, predicting which children warrant investigation for child maltreatment. The score is simple and easy to complete in an emergency department setting.

    Research areas

  • Maltreatment, Clinical prediction tool, Child, Burn

Download statistics

No data available

Documents

Documents

  • Full-text PDF (accepted author manuscript)

    Rights statement: This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Elsevier at https://www.sciencedirect.com/science/article/pii/S0305417917304734?via%3Dihub. Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 561 KB, PDF document

    Licence: CC BY-NC-ND

  • Supplimentary info PDF

    Accepted author manuscript, 640 KB, PDF document

    Licence: CC BY-NC-ND

DOI

View research connections

Related faculties, schools or groups