Every year almost 3 million children are brought into emergency rooms with fall-related injuries, and in each case a physician must examine the child to determine if the injury was an accident or a case of abuse. The problem is daunting because accidental falls are common in children, but it’s also common for individuals to conceal child abuse by claiming accidental injury.
More than 600,000 children were determined to be victims of maltreatment in 2021, according to the Department of Health and Human Services Administration for Children and Families. Of that number, 1,820 children died due to maltreatment, and most of them were younger than 3 years of age.
For more than a decade the National Institute of Justice (NIJ) has supported research to help physicians and law enforcement sort accident from abuse cases when presented with an injured child. The research has often focused on bringing the science of biomechanics to the world of pediatric medical assessment. Although progress is being made, the challenges of getting definitive answers remains.
Two recently completed NIJ-funded studies continue that progress.
Computer Modeling Predicts Skull Fracture Patterns
The first study, by University of Utah bioengineer Brittany Coats, is designed to quantify the mechanical properties of infant and toddler skulls to develop a high-fidelity computational model for predicting the widening, lengthening, or increase in the number of cracks and fracture patterns in infant skull (cranial) bone.
The researchers tested human cranial bone specimens from decedents younger than 3 years old under several different impact and stress levels to determine force and fracture patterns. Each specific impact results in a distinct fracture pattern, allowing the researchers to develop a database correlating impacts to injuries.
The researchers concluded that computational toolsets, such as the one being developed by Coats’s team, could “evaluate specific cases of skull fracture, can alleviate confusion and uncertainty, and increase overall judicial accuracy.”
Statistical Models Help With Abuse Identification
The second study was conducted by bioengineer Gina Bertocci, University of Louisville, and physician Mary Clyde Pierce, a pediatric emergency medicine specialist at Lurie Children’s Hospital of Chicago.
The goal of their research was to “develop an evidenced-based statistical model capable of predicting the probability of head injury in young children involved in falls.” The model would improve physicians’ ability to determine if an accident was the cause of an injury. The model they developed is based on fall data collected through an earlier NIJ grant that used video to monitor children in a childcare center who wore head accelerometers, which measure the speed of the head in a fall.
The most recent study looked specifically at short-distance falls involving young children. The researchers reconstructed 80 falls for children brought to emergency rooms. Using that injury data combined with fall data from the childcare center project, the researchers developed a comprehensive database that helped create LCAST, a tool used at the Lurie Children’s Hospital that helps physicians identify abuse in children.
The injury modeling data developed by Bertocci and Pierce has already helped physicians and investigators identify pediatric abuse, but the researchers acknowledge there are limitations on what can be concluded from the modeling. The LCAST website describes the data system as “strictly a screening tool to help improve recognition of abuse and cannot be used to diagnose abuse.”
Republished courtesy of NIJ