Coralie Hermetet1,2,3, Émeline Laurent4,5, Yasmine El Allali6, Christophe Gaborit4, Annie Urvois-Grange7, Mélanie Biotteau4,8, Anne Le Touze9, Leslie Grammatico-Guillon4,10. 1. Public Health and Epidemiology Unit, Teaching Hospital of Tours, 2 boulevard Tonnellé, 37044, Tours cedex 9, France. coralie.hermetet@etu.univ-tours.fr. 2. Research Team "Education, Ethics and Health" (EA 7505), University of Tours, 2 boulevard Tonnellé, 37044, Tours cedex 9, France. coralie.hermetet@etu.univ-tours.fr. 3. Medicolegal Unit, Teaching Hospital of Rennes, 2 rue Henri Le Guilloux, 35033, Rennes cedex 9, France. coralie.hermetet@etu.univ-tours.fr. 4. Public Health and Epidemiology Unit, Teaching Hospital of Tours, 2 boulevard Tonnellé, 37044, Tours cedex 9, France. 5. Research Team "Education, Ethics and Health" (EA 7505), University of Tours, 2 boulevard Tonnellé, 37044, Tours cedex 9, France. 6. Department of Paediatrics, Hospital of Blois, Les Sept Arpents, 41260, Blois, France. 7. Paediatric Emergency Department, Teaching Hospital of Tours, 49 boulevard Béranger, 37044, Tours cedex 9, France. 8. University Psychiatric Clinic, Teaching Hospital of Tours, 12 rue du Coq, 37540, Saint-Cyr-sur-Loire, France. 9. Pediatric Burn Unit, Teaching Hospital of Tours, 49 boulevard Béranger, 37044, Tours cedex 9, France. 10. University of Tours, 60 rue du Plat d'Étain, 37020, Tours cedex 1, France.
Abstract
OBJECTIVES: To build a detection algorithm of non-accidental pediatric burns (NAB) using hospital resumes from the French Hospital Discharge Database (HDD) and to describe cases with no judicial or administrative report. MATERIALS AND METHODS: Children aged 0-16 years old hospitalized at the University Hospital of Tours from 2012 to 2017 with a coded burn were included. "Probable" or "possible" HDD cases of NAB were defined based on the International Classification of Diseases 10th version codes during the inclusion stay or the previous year. A chart review was performed on all the HDD cases and HDD non cases matched on sex and age with a 1:2 ratio. Performance parameters were estimated for three clinical definitions of child maltreatment: excluding neglect, including neglect in a restrictive definition, and in a broad definition. For clinical cases, report to the judicial or administrative authorities was searched. RESULTS: Among the 253 included children, 83 "probable" cases and 153 non-cases were analyzed. Sensitivity varied from 48 (95%CI [36-60], excluding neglect) to 90% [55-100] and specificity from 70 [63;77] to 68% [61;74]. The proportion of clinical cases with no report without justification varied from 0 (excluding neglect) to > 85% (with the broadest definition); all corresponded to possible isolated neglect. CONCLUSION: The performances of the algorithm varied tremendously according to the clinical definition of child maltreatment. Neglect is obviously complex and tough to clinically detect. Training for healthcare professionals and qualitative studies on obstacles to report should be added to this work.
OBJECTIVES: To build a detection algorithm of non-accidental pediatric burns (NAB) using hospital resumes from the French Hospital Discharge Database (HDD) and to describe cases with no judicial or administrative report. MATERIALS AND METHODS:Children aged 0-16 years old hospitalized at the University Hospital of Tours from 2012 to 2017 with a coded burn were included. "Probable" or "possible" HDD cases of NAB were defined based on the International Classification of Diseases 10th version codes during the inclusion stay or the previous year. A chart review was performed on all the HDD cases and HDD non cases matched on sex and age with a 1:2 ratio. Performance parameters were estimated for three clinical definitions of child maltreatment: excluding neglect, including neglect in a restrictive definition, and in a broad definition. For clinical cases, report to the judicial or administrative authorities was searched. RESULTS: Among the 253 included children, 83 "probable" cases and 153 non-cases were analyzed. Sensitivity varied from 48 (95%CI [36-60], excluding neglect) to 90% [55-100] and specificity from 70 [63;77] to 68% [61;74]. The proportion of clinical cases with no report without justification varied from 0 (excluding neglect) to > 85% (with the broadest definition); all corresponded to possible isolated neglect. CONCLUSION: The performances of the algorithm varied tremendously according to the clinical definition of child maltreatment. Neglect is obviously complex and tough to clinically detect. Training for healthcare professionals and qualitative studies on obstacles to report should be added to this work.
Authors: Robert F Anda; Vincent J Felitti; J Douglas Bremner; John D Walker; Charles Whitfield; Bruce D Perry; Shanta R Dube; Wayne H Giles Journal: Eur Arch Psychiatry Clin Neurosci Date: 2005-11-29 Impact factor: 5.270
Authors: Dragana Seifert; Julia Krohn; Mandi Larson; Andrea Lambe; Klaus Püschel; Henrike Kurth Journal: Int J Legal Med Date: 2009-04-28 Impact factor: 2.686