Development of a clinical prediction instrument to estimate risk of initial violent injury. Issue 10 (October 2022)

• Record Type: Journal Article
• Authors: Li, Benjamin H.; Haukoos, Jason S.; Gangidine, Matthew M.; Hopkins, Emily; McDaniel, Michelle; Williams, Johnnie E.; Morgan, Jerry L.; Green, Erica; Mireles, Alma R.; Palacios, Jose; Ramirez, Jesus H.; Bakes, Katherine M.
• Is Part Of: Injury. Volume 53:Issue 10(2022)
• Page Start: 3263
• Page End: 3268
• Publication Date: 2022-10
• Subjects: Violent injury -- Injury prevention -- Modeling -- Risk prediction -- Prevalence -- Emergency department -- Social determinants of health -- Case-cohort; Wounds and injuries -- Surgery -- Periodicals; Accidents -- Periodicals; Wounds and Injuries -- surgery -- Periodicals; Lésions et blessures -- Chirurgie -- Périodiques; Electronic journals; Electronic journals; 617.1
• DOI: 10.1016/j.injury.2022.08.012
• Languages: English
• ISSNs: 0020-1383

Abstract

Highlights: Interpersonal violent injuries are a public health emergency, with high rates of morbidity, mortality, and recidivism, and previously described risk characteristics have primarily focused on re-injury, violence perpetration, and firearms. We described associations between sociobehavioral predictors and first-time violent injury victimization of all injury types, and developed an internally valid predictive risk score that grouped individuals by increasing prevalence of violent injury. Our risk score has the potential to be utilized as a primary prevention strategy across multiple clinical settings, in order to prevent initial violent injury victimization. Abstract: Background: Interpersonal violent injury is a public health crisis, disproportionately affecting young people of color. We aimed to evaluate associations between sociobehavioral predictors and first-time violent injury, and to develop a predictive risk score for violent injury. Methods: We performed a retrospective case-cohort study of adolescents aged 12–18 years. Multivariable logistic regression was used to estimate associations between 35 candidate variables and interpersonal first-time violent injury resulting in an emergency department (ED) visit. Multiple imputation was used to account for missing values and a risk score was developed by multiplying regression coefficients by 10 to generate a composite tool to predict initial violent injury (IVI). Discrimination and calibration were assessed using 10-fold cross validation. Results: 19, 210 adolescents were included, 276 (1.4%) as victims of IVI. The final model, the Initial Violent Injury Risk Prediction Tool (IVI-RPT), included: age, fight within the prior year, trouble with the law, and alcohol use. IVI-RPT scores were categorized as: 0–7 (low risk), 8–16 (moderate), and 17–26 (high), and IVI prevalence was 0.8% (95% confidence interval [CI]: 0.6%, 0.9%), 2.5% (95% CI: 1.9%, 3.1%), and 5.3% (95% CI: 4.1%, 6.6%), respectively. The area under the receiver operating characteristic curve was 0.70 (95% CI: 0.66, 0.73), while the slope of the calibration curve was 1.1 (95% CI: 0.9, 1.2). Conclusions: We developed a promising clinical prediction instrument, the IVI-RPT, that categorizes individuals into risk groups with increasing probabilities of violent injury. External validation of this tool is required prior to clinical practice implementation.