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Multicenter Study
. 2017 Dec;43(6):755-762.
doi: 10.1007/s00068-017-0811-9. Epub 2017 Jun 22.

Pediatric Emergency Care Applied Research Network (PECARN) prediction rules in identifying high risk children with mild traumatic brain injury

Affiliations
Multicenter Study

Pediatric Emergency Care Applied Research Network (PECARN) prediction rules in identifying high risk children with mild traumatic brain injury

B Nakhjavan-Shahraki et al. Eur J Trauma Emerg Surg. 2017 Dec.

Abstract

Purpose: Pediatric Emergency Care Applied Research Network (PECARN) traumatic brain injury (TBI) prognostic rules is a scoring system for prediction of the need for computed tomography (CT) scanning in children with mild TBI. However, its validation has not been assessed in developing countries. Therefore, the present study was designed to assess the value of PECARN rule in identification of children with clinically important TBI (ciTBI).

Method: In this prospective cross-sectional study, 594 children (mean age: 7.9 ± 5.3 years; 79.3% boys) with mild TBI brought to emergency ward of two healthcare centers in Tehran, Iran were assessed. PECARN checklist was filled for all patients and children were divided to three groups of low, intermediate and high risks. Patients were followed for 2 weeks by phone to assess their ciTBI status. At the end, discrimination power, calibration and overall performance of PECARN rule were assessed.

Results: PECARN had a sensitivity and specificity of 92.3 and 40.6%, respectively, in predicting ciTBI in children under 2 years and 100.0 and 57.8%, respectively, in individuals between the ages of 2 and 18. PECARN rule had a proper calibration in prediction of ciTBI and CT scan findings. Brier score (overall performance) of PECARN rule in predicting ciTBI in children under 2 and 2-18 years were 1.5 and 1.2, respectively.

Conclusion: PECARN prediction rule has a proper validity in the prediction of ciTBI. Therefor it can be used for screening and identification of high risk children with mild TBI.

Keywords: Decision Support Systems, Clinical; Emergency Service, Hospital; Pediatrics; Sensitivity and Specificity.

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