Validation of a Prediction Tool for Abusive Head Trauma

Abstract

BACKGROUND AND OBJECTIVES: Abusive head trauma (AHT) may be missed in the clinical setting. Clinical prediction tools are used to reduce variability in practice and inform decision-making. From a systematic review and individual patient data analysis we derived the Predicting Abusive Head Trauma (PredAHT) tool, using multilevel logistic regression to predict likelihood of AHT. This study aims to externally validate the PredAHT tool.METHODS: Consecutive children aged ,36 months admitted with an intracranial injury, confirmed as abusive or nonabusive, to 2 sites used in the original model were ascertained. Details of 6 influential features were recorded (retinal hemorrhage, rib and long -bone fractures, apnea, seizures, and head or neck bruising). We estimated the likelihood of an unrecorded feature being present with multiple imputation; analysis included sensitivity, specificity, and area under the curve, with 95% confidence intervals (CIs).RESULTS: Data included 133 non-AHT cases and 65 AHT cases, 97% of children were ,24 months old. Consistent with original predictions, when $3 features were present in a child ,36 months old with intracranial injury, the estimated probability of AHT was .81.5% (95% CI, 63.3-91.8). The sensitivity of the tool was 72.3% (95% CI, 60.4-81.7), the specificity was 85.7% (95% CI, 78.8-90.7), area under the curve 0.88 (95% CI, 0.823-0.926).CONCLUSIONS: When tested on novel data, the PredAHT tool performed well. This tool has the potential to contribute to decision-making in these challenging cases. An implementation study is needed to explore its performance and utility within the child protection process. WHAT'S KNOWN ON THIS SUBJECT:A previous multivariable statistical model, using individual patient data, estimated the probability of abusive head trauma based on the presence or absence of 6 clinical features: rib fracture, long-bone fracture, apnea, seizures, retinal hemorrhage, and head or neck bruising. WHAT THIS STUDY ADDS:The model performed well in this validation, with a sensitivity of 72.3%, specificity of 85.7%, and area under the curve of 0.88. In children ,3 years old with intracranial injury plus $3 features, the estimated probability of abuse is .81.5%. Ms Cowley drafted the Methods section, produced the tables, revised the article, formatted the article, and contributed to overall editing; Dr Morris collected the data in data set 1 and entered all anonymized data into the database; Dr. Maguire had the initial study idea, drafted and revised the article, and contributed to the study design and overall editing; Dr Farewell designed and conducted all statistical analyses, drafted the statistical components of the article, produced the figures, and contributed to overall editing; Prof Kemp revised the article and contributed to overall study design and editing; and all authors approved the final manuscript as submitted. Clinicians who undertake child protection investigations of children presenting with head injury can meet resistance and face a barrage of critici...

Clinical prediction rules for abusive head trauma: a systematic review

“…The search in PubMed and the Cochrane Database of Systematic Reviews and Cochrane Controlled Trials did not add any additional relevant studies. After removing duplicates, reviewing abstracts and excluding irrelevant articles, three recently published, externally validated CPredRs for AHT met the inclusion criteria: the Pediatric Brain Injury Research Network (PediBIRN) 4-Variable AHT CPredR,19 the Predicting Abusive Head Trauma (PredAHT) tool20 and the Pittsburgh Infant Brain Injury Score (PIBIS) for AHT21 (see figure 1 and table 1). …”

“…The PredAHT CPredR provides an estimated probability of AHT to assist clinicians in discussions with child abuse specialists 20. It was derived from a pooled analysis of individual patient data from six previously published studies, which included prospectively collected data on 133 children (58 AHT cases) and retrospective data on 920 children (290 AHT cases) with head injury 22.…”

“…This approach was an attempt to verify the true negatives as only 61% of controls had neuroimaging. The PediBIRN and the PIBIS CPredRs both proposed a clear course of action (PediBIRN—thorough evaluations for abuse, PIBIS—CT scan), whereas PredAHT provided a probability of AHT in order to ‘assist clinicians in their discussions with child abuse specialists, in addition to facilitating discussions between child abuse specialists and social welfare, law enforcement, or other professionals involved in the child protection process.’20 …”

“…In terms of published accuracy of the rules, the PediBIRN CPredR19 performed best with a sensitivity of 0.96, closely followed by PIBIS21 with 0.93, whereas the PredAHT CPredR detected 0.72 of AHT cases applying a 50% cut-off; however, the PredAHT tool provides a sliding scale of probability from 4% to nearly 100% depending on the presence or absence of each of the six features 20. In addition, the sensitivity and specificity of PredAHT depends on the probability cut-off applied.…”

“…These prediction rules are aimed at very different populations and different time points within the clinical assessment (figure 2): PIBIS21 is targeted at a specific population of well-appearing infants in the ED who might benefit from a head CT scan. PredAHT20 applies to children <3 years of age admitted to hospital with intracranial injury, where children have been examined and may have had some ophthalmological and radiological investigations, and PediBIRN19 applies to a narrower population of <3-year-olds admitted to PICU with a cranial or intracranial injury excluding head trauma resulting from motor vehicle collisions. It is notable that PredAHT20 does not apply to children with cranial injury only, as defined within the Centers for Disease Control and Prevention definition of AHT.…”