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Journal Article

Citation

Li BH, Haukoos JS, Gangidine MM, Hopkins E, McDaniel M, Williams JEJ, Morgan JLJ, Green E, Mireles AR, Palacios J, Ramirez JH, Bakes KM. Injury 2022; ePub(ePub): ePub.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.injury.2022.08.012

PMID

35970636

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.


Language: en

Keywords

Prevalence; Injury prevention; Social determinants of health; Emergency department; Case-cohort; Modeling; Risk prediction; Violent injury

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