title: Estimating the probability of abusive head trauma: a pooled analysis.
abstract: OBJECTIVE
  To determine which combinations of clinical features assist in distinguishing abusive head trauma (AHT) from nonabusive head trauma.
  
  
  METHODS
  Individual patient data from 6 comparative studies of children younger than 3 years with intracranial injury were analyzed to determine the association between AHT and combinations of apnea; retinal hemorrhage; rib, skull, and long-bone fractures; seizures; and head and/or neck bruising. An aggregate analysis of data from these studies used multiple imputation of combined clinical features using a bespoke hotdeck imputation strategy, which accounted for uncertainty arising from missing information.
  
  
  RESULTS
  Analyzing 1053 children (348 had AHT), excluding nonsignificant variables (gender, age, skull fractures), for a child with an intracranial injury and 1 or 2 of the 6 features, the positive predictive value (PPV) of AHT varies from 4% to 97% according to the different combinations. Although rarely recorded, apnea is significantly associated with AHT (odds ratio [OR]: 6.89 [confidence interval: 2.08-22.86]). When rib fracture or retinal hemorrhage was present with any 1 of the other features, the OR for AHT is >100 (PPV > 85%). Any combination of 3 or more of the 6 significant features yielded an OR of >100 (PPV for AHT > 85%).
  
  
  CONCLUSIONS
  Probabilities of AHT can be estimated on the basis of different combinations of clinical features. The model could be further developed in a prospective large-scale study, with an expanded clinical data set, to contribute to a more refined tool to inform clinical decisions about the likelihood of AHT.
authors.affiliation: Department of Child Health, School of Medicine, Cardiff University, Cardiff, United Kingdom. sabinemaguire@yahoo.co.uk
authors.forename: Sabine Ann
authors.initials: SA
authors.lastname: Maguire
authors.forename: Alison Mary
authors.initials: AM
authors.lastname: Kemp
authors.forename: Rebecca Caroline
authors.initials: RC
authors.lastname: Lumb
authors.forename: Daniel Mark
authors.initials: DM
authors.lastname: Farewell
mesh_terms: D000293:Adolescent; D000328:Adult; D001049:Apnea / Q000453:epidemiology*; D002648:Child; D002649:Child Abuse / Q000706:statistics & numerical data*; D002675:Child, Preschool; D006259:Craniocerebral Trauma / Q000453:epidemiology*; D005260:Female; D006801:Humans; D007223:Infant; D016015:Logistic Models; D008297:Male; D015233:Models, Statistical; D011336:Probability; D012166:Retinal Hemorrhage / Q000453:epidemiology*; D012253:Rib Fractures / Q000453:epidemiology; D012887:Skull Fractures / Q000453:epidemiology*; D055815:Young Adult