European Journal of Trauma and Emergency Surgery

, Volume 43, Issue 6, pp 755–762 | Cite as

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

  • B. Nakhjavan-Shahraki
  • M. Yousefifard
  • M. J. Hajighanbari
  • A. Oraii
  • S. Safari
  • M. Hosseini
Original Article



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).


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.


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.


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.


Decision Support Systems, Clinical Emergency Service, Hospital Sensitivity and Specificity Pediatrics 



We appreciate the efforts by radiologists and emergency medicine physicians who collaborated with us in this study.

Compliance with ethical standards

Conflict of interest

Babak Nakhjavan-Shahraki, Mahmoud Yousefifard, Mohammad Javad Hajighanbari, Alireza Oraii, Saeed Safari and Mostafa Hosseini declare that they have no conflict of interest.

Ethical approval

The study protocol was approved by the ethics committee of Tehran University of Medical Sciences. ll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.


  1. 1.
    Thurman DJ. The epidemiology of traumatic brain injury in children and youths. J Child Neurol. 2014;31(1):20–7.CrossRefPubMedGoogle Scholar
  2. 2.
    Alexander MP. Mild traumatic brain injury: pathophysiology, natural history, and clinical management. Neurology. 1995;45(7):1253–60.CrossRefPubMedGoogle Scholar
  3. 3.
    Fred HL. Drawbacks and limitations of computed tomography: views from a medical educator. Tex Heart Inst J. 2004;31(4):345–8.PubMedPubMedCentralGoogle Scholar
  4. 4.
    Wildenschild D, Vaz C, Rivers M, Rikard D, Christensen B. Using X-ray computed tomography in hydrology: systems, resolutions, and limitations. J Hydrol. 2002;267(3):285–97.CrossRefGoogle Scholar
  5. 5.
    Atabaki SM, Hoyle JD Jr, Schunk JE, Monroe DJ, Alpern ER, Quayle KS, et al. Comparison of prediction rules and clinician suspicion for identifying children with clinically important brain injuries after blunt head trauma. Acad Emerg Med. 2016;23(5):566–75.CrossRefPubMedGoogle Scholar
  6. 6.
    Safari S, Yousefifard M, Baikpour M, Rahimi-Movaghar V, Abiri S, Falaki M, et al. Validation of thoracic injury rule out criteria as a decision instrument for screening of chest radiography in blunt thoracic trauma. J Clin Orthop Trauma. 2016;7(2):95–100.CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Safari S, Yousefifard M, Hashemi B, Baratloo A, Forouzanfar M, Rahmati F, et al. The role of scoring systems and urine dipstick in prediction of rhabdomyolysis-induced acute kidney injury: a systematic review. Iran J Kidney Dis. 2016;10(3):101–6.PubMedGoogle Scholar
  8. 8.
    Tham E, Swietlik M, Deakyne S, Hoffman JM, Grundmeier RW, Paterno MD, et al. Clinical decision support for a multicenter trial of pediatric head trauma. Appl Clin Inform. 2016;7(2):534–42.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Schonfeld D, Bressan S, Da Dalt L, Henien MN, Winnett JA, Nigrovic LE. Pediatric emergency care applied research network head injury clinical prediction rules are reliable in practice. Postgrad Med J. 1081;2015(91):634–8.Google Scholar
  10. 10.
    Kuppermann N, Holmes JF, Dayan PS, Hoyle JD Jr, Atabaki SM, Holubkov R, et al. Identification of children at very low risk of clinically-important brain injuries after head trauma: a prospective cohort study. Lancet. 2009;374(9696):1160–70.CrossRefPubMedGoogle Scholar
  11. 11.
    Babl FE, Lyttle MD, Bressan S, Borland M, Phillips N, Kochar A, et al. A prospective observational study to assess the diagnostic accuracy of clinical decision rules for children presenting to emergency departments after head injuries (protocol): the Australasian Paediatric Head Injury Rules Study (APHIRST). BMC Pediatr. 2014;14:148.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Lyttle MD, Crowe L, Oakley E, Dunning J, Babl FE. Comparing CATCH, CHALICE and PECARN clinical decision rules for paediatric head injuries. Emerg Med J. 2012;29(10):785–94.CrossRefPubMedGoogle Scholar
  13. 13.
    Yousefzadeh Chabok S, Ramezani S, Kouchakinejad L, Saneei Z. Epidemiology of pediatric head trauma in Guilan. Arch Trauma Res. 2012;1(1):19–22.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Alexiou GA, Sfakianos G, Prodromou N. Pediatric head trauma. J Emerg Trauma Shock. 2011;4(3):403–8.CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Hajian-Tilaki K. Sample size estimation in diagnostic test studies of biomedical informatics. J Biomed Inform. 2014;48:193–204.CrossRefPubMedGoogle Scholar
  16. 16.
    Easter JS, Bakes K, Dhaliwal J, Miller M, Caruso E, Haukoos JS. Comparison of PECARN, CATCH, and CHALICE rules for children with minor head injury: a prospective cohort study. Ann Emerg Med. 2014;64(2):145–52.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Ide K, Uematsu S, Tetsuhara K, Yoshimura S, Kato T, Kobayashi T. External validation of the PECARN Head trauma prediction rules in Japan. Acad Emerg Med. 2017;24(3):308–14.CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • B. Nakhjavan-Shahraki
    • 1
  • M. Yousefifard
    • 2
  • M. J. Hajighanbari
    • 3
  • A. Oraii
    • 4
  • S. Safari
    • 5
  • M. Hosseini
    • 6
  1. 1.Sina Trauma and Surgery Research CenterTehran University of Medical SciencesTehranIran
  2. 2.Physiology Research Center and Department of Physiology, Faculty of MedicineIran University of Medical SciencesTehranIran
  3. 3.Department of Emergency Medicine, Hafte Tir HospitalIran University of Medical SciencesTehranIran
  4. 4.Department of Medicine, School of MedicineTehran University of Medical SciencesTehranIran
  5. 5.Clinical Research Development Center, Amir-Almomenin HospitalIslamic Azad UniversityTehranIran
  6. 6.Department of Epidemiology and Biostatistics, School of Public HealthTehran University of Medical SciencesTehranIran

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