Home Impact of routine S100B protein assay on CT scan use in children with mild traumatic brain injury
Article
Licensed
Unlicensed Requires Authentication

Impact of routine S100B protein assay on CT scan use in children with mild traumatic brain injury

  • Fleur Lorton ORCID logo EMAIL logo , Jeanne Simon-Pimmel , Damien Masson , Elise Launay , Christèle Gras-Le Guen and Pauline Scherdel
Published/Copyright: November 25, 2020

Abstract

Objectives

To evaluate the impact of implementing a modified Pediatric Emergency Care Applied Research Network (PECARN) rule including the S100B protein assay for managing mild traumatic brain injury (mTBI) in children.

Methods

A before-and-after study was conducted in a paediatric emergency department of a French University Hospital from 2013 to 2015. We retrospectively included all consecutive children aged 4 months to 15 years who presented mTBI and were at intermediate risk for clinically important traumatic brain injury (ciTBI). We compared the proportions of CT scans performed and of in-hospital observations before (2013–2014) and after (2014–2015) implementation of a modified PECARN rule including the S100B protein assay.

Results

We included 1,062 children with mTBI (median age 4.5 years, sex ratio [F/M] 0.73) who were at intermediate risk for ciTBI: 494 (46.5%) during 2013–2014 and 568 (53.5%) during 2014–2015. During 2014–2015, S100B protein was measured in 451 (79.4%) children within 6 h after mTBI. The proportion of CT scans and in-hospital observations significantly decreased between the two periods, from 14.4 to 9.5% (p=0.02) and 73.9–40.5% (p<0.01), respectively. The number of CT scans performed to identify a single ciTBI was reduced by two-thirds, from 18 to 6 CT scans, between 2013–2014 and 2014–2015. All children with ciTBI were identified by the rules.

Conclusions

The implementation of a modified PECARN rule including the S100B protein assay significantly decreased the proportion of CT scans and in-hospital observations for children with mTBI who were at intermediate risk for ciTBI.


Corresponding author: Fleur Lorton, MD, Service d’urgences pédiatriques, CHU de Nantes, Quai Moncousu, 44093 Nantes Cedex 01, France, Phone: +33 2 40 08 38 06, Fax: +33 2 40 08 46 45, E-mail:

Acknowledgments

The authors thank Drs. Baptiste Dumortier, Juliette Foucher and Maelle Lorvellec for participating in the data collection.

  1. Research funding: None declared.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interest: FL has received travel grants from Pfizer, JSP has received travel grants from Roche Diagnostics, DM has received travel grants from Roche Diagnostics, EL has received travel grants from GSK, CGL has received travel grants from GSK, AbbVie, Astellas Pharma, bioMérieux, Chiesi SAS and Pfizer, fees from Pfizer, AbbVie and Roche Diagnostics. No other relationships or activities could appear to have influenced the submitted work.

  4. Ethical approval: Research involving human subjects complied with all relevant national regulations, institutional policies and is in accordance with the tenets of the Helsinki Declaration.

References

1. Lumba-Brown, A, Yeates, KO, Sarmiento, K, Breiding, MJ, Haegerich, TM, Gioia, GA, et al.. Centers for disease control and prevention guideline on the diagnosis and management of mild traumatic brain injury among children. JAMA Pediatr 2018;172:e182853. https://doi.org/10.1001/jamapediatrics.2018.2853.Search in Google Scholar

2. Pandor, A, Goodacre, S, Harnan, S, Holmes, M, Pickering, A, Fitzgerald, P, et al.. Diagnostic management strategies for adults and children with minor head injury: a systematic review and an economic evaluation. Health Technol Assess 2011;15:1–202. https://doi.org/10.3310/hta15270.Search in Google Scholar

3. Atabaki, SM, Hoyle, JD, 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;23:566–75. https://doi.org/10.1111/acem.12923.Search in Google Scholar

4. Pearce, MS, Salotti, JA, Little, MP, McHugh, K, Lee, C, Kim, KP, et al.. Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study. Lancet 2012;380:499–505. https://doi.org/10.1016/s0140-6736(12)60815-0.Search in Google Scholar

5. Miglioretti, DL, Johnson, E, Williams, A, Greenlee, RT, Weinmann, S, Solberg, LI, et al.. The use of computed tomography in pediatrics and the associated radiation exposure and estimated cancer risk. JAMA Pediatr 2013;167:700–7. https://doi.org/10.1001/jamapediatrics.2013.311.Search in Google Scholar

6. Report to congress: the management of traumatic brain injury in children: opportunities for action. Available from: https://www.cdc.gov/traumaticbraininjury/pdf/reportstocongress/managementoftbiinchildren/TBI-ReporttoCongress-508.pdf [Accessed June 2020].Search in Google Scholar

7. Kuppermann, N, Holmes, JF, Dayan, PS, Hoyle, JD, 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;374:1160–70. https://doi.org/10.1016/s0140-6736(09)61558-0.Search in Google Scholar

8. 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. Arch Dis Child 2014;99:427–31. https://doi.org/10.1136/archdischild-2013-305004.Search in Google Scholar

9. Babl, FE, Borland, ML, Phillips, N, Kochar, A, Dalton, S, McCaskill, M, et al.. Accuracy of PECARN, CATCH, and CHALICE head injury decision rules in children: a prospective cohort study. Lancet 2017;389:2393–402. https://doi.org/10.1016/s0140-6736(17)30555-x.Search in Google Scholar

10. Lorton, F, Poullaouec, C, Legallais, E, Simon-Pimmel, J, Chêne, MA, Leroy, H, et al.. Validation of the PECARN clinical decision rule for children with minor head trauma: a French multicenter prospective study. Scand J Trauma Resuscitation Emerg Med 2016;24:98. https://doi.org/10.1186/s13049-016-0287-3.Search in Google Scholar PubMed PubMed Central

11. Pickering, A, Harnan, S, Fitzgerald, P, Pandor, A, Goodacre, S. Clinical decision rules for children with minor head injury: a systematic review. Arch Dis Child 2011;96:414–21. https://doi.org/10.1136/adc.2010.202820.Search in Google Scholar PubMed

12. Bressan, S, Romanato, S, Mion, T, Zanconato, S, Da Dalt, L. Implementation of adapted PECARN decision rule for children with minor head injury in the pediatric emergency department. Acad Emerg Med 2012;19:801–7. https://doi.org/10.1111/j.1553-2712.2012.01384.x.Search in Google Scholar

13. Hess, EP, Homme, JL, Kharbanda, AB, Tzimenatos, L, Louie, JP, Cohen, DM, et al.. Effect of the head computed tomography choice decision aid in parents of children with minor head trauma: a cluster randomized trial. JAMA Netw Open 2018;1:e182430. https://doi.org/10.1001/jamanetworkopen.2018.2430.Search in Google Scholar

14. Nigrovic, LE, Kuppermann, N. Children with minor blunt head trauma presenting to the emergency department. Pediatrics 2019;144. https://doi.org/10.1542/peds.2019-1495.Search in Google Scholar

15. Romner, B, Ingebrigtsen, T, Kongstad, P, Børgesen, SE. Traumatic brain damage: serum S-100 protein measurements related to neuroradiological findings. J Neurotrauma 2000;17:641–7. https://doi.org/10.1089/089771500415391.Search in Google Scholar

16. Peskind, ER, Griffin, WS, Akama, KT, Raskind, MA, Van Eldik, LJ. Cerebrospinal fluid S100B is elevated in the earlier stages of Alzheimer’s disease. Neurochem Int 2001;39:409–13. https://doi.org/10.1016/s0197-0186(01)00048-1.Search in Google Scholar

17. Herrmann, M, Vos, P, Wunderlich, MT, de Bruijn, CH, Lamers, KJ. Release of glial tissue-specific proteins after acute stroke: a comparative analysis of serum concentrations of protein S-100B and glial fibrillary acidic protein. Stroke 2000;31:2670–7. https://doi.org/10.1161/01.str.31.11.2670.Search in Google Scholar PubMed

18. Biberthaler, P, Linsenmeier, U, Pfeifer, K-J, Kroetz, M, Mussack, T, Kanz, K-G, et al.. Serum S-100B concentration provides additional information for the indication of computed tomography in patients after minor head injury: a prospective multicenter study. Shock 2006;25:446–53. https://doi.org/10.1097/01.shk.0000209534.61058.35.Search in Google Scholar PubMed

19. Müller, K, Townend, W, Biasca, N, Undén, J, Waterloo, K, Romner, B, et al.. S100B serum level predicts computed tomography findings after minor head injury. J Trauma 2007;62:1452–6. https://doi.org/10.1097/ta.0b013e318047bfaa.Search in Google Scholar PubMed

20. Undén, J, Romner, B. Can low serum levels of S100B predict normal CT findings after minor head injury in adults? an evidence-based review and meta-analysis. J Head Trauma Rehabil 2010;25:228–40. https://doi.org/10.1097/htr.0b013e3181e57e22.Search in Google Scholar PubMed

21. Bechtel, K, Frasure, S, Marshall, C, Dziura, J, Simpson, C. Relationship of serum S100B levels and intracranial injury in children with closed head trauma. Pediatrics 2009;124:e697–704. https://doi.org/10.1542/peds.2008-1493.Search in Google Scholar PubMed

22. Oris, C, Pereira, B, Durif, J, Simon-Pimmel, J, Castellani, C, Manzano, S, et al.. The biomarker S100B and mild traumatic brain injury: a meta-analysis. Pediatrics 2018;141. https://doi.org/10.1542/peds.2018-0037.Search in Google Scholar

23. Simon-Pimmel, J, Lorton, F, Guiziou, N, Levieux, K, Vrignaud, B, Masson, D, et al.. Serum S100β neuroprotein reduces use of cranial computed tomography in children after minor head trauma. Shock 2015;44:410–6. https://doi.org/10.1097/shk.0000000000000442.Search in Google Scholar

24. Bouvier, D, Fournier, M, Dauphin, J-B, Amat, F, Ughetto, S, Labbé, A, et al.. Serum S100B determination in the management of pediatric mild traumatic brain injury. Clin Chem 2012;58:1116–22. https://doi.org/10.1373/clinchem.2011.180828.Search in Google Scholar

25. Mannix, R, Levy, R, Zemek, R, Yeates, KO, Arbogast, K, Meehan, WP, et al.. Fluid biomarkers of pediatric mild traumatic brain injury: a systematic review. J Neurotrauma 2020. https://doi.org/10.1089/neu.2019.6956.Search in Google Scholar

26. International statistical classification of diseases and related health problems 10th revision. Available from: https://icd.who.int/browse10/2015/en#/ [Accessed June 2020].Search in Google Scholar

27. Bouvier, D, Castellani, C, Fournier, M, Dauphin, J-B, Ughetto, S, Breton, M, et al.. Reference ranges for serum S100B protein during the first three years of life. Clin Biochem 2011;44:927–9. https://doi.org/10.1016/j.clinbiochem.2011.05.004.Search in Google Scholar

28. Lorton, F, Levieux, K, Vrignaud, B, Hamel, O, Jehlé, E, Hamel, A, et al.. New recommendations for the management of children after minor head trauma. Arch Pediatr 2014;21:790–6. https://doi.org/10.1016/j.arcped.2014.04.015.Search in Google Scholar

29. Mower, WR. Paediatric head imaging decisions are not child’s play. Lancet 2017;389:2354–5. https://doi.org/10.1016/s0140-6736(17)30932-7.Search in Google Scholar

30. Kemp, A, Nickerson, E, Trefan, L, Houston, R, Hyde, P, Pearson, G, et al.. Selecting children for head CT following head injury. Arch Dis Child 2016;101:929–34. https://doi.org/10.1136/archdischild-2015-309078.Search in Google Scholar PubMed PubMed Central

31. Burstein, B, Upton, JEM, Terra, HF, Neuman, MI. Use of CT for head trauma: 2007-2015. Pediatrics 2018;142. https://doi.org/10.1542/peds.2018-0814.Search in Google Scholar PubMed

32. Ide, K, Uematsu, S, Hayano, S, Hagiwara, Y, Tetsuhara, K, Ito, T, et al.. Validation of the PECARN head trauma prediction rules in Japan: a multicenter prospective study. Am J Emerg Med 2019;S0735-6757:30588–1.10.1016/j.ajem.2019.158439Search in Google Scholar PubMed

33. `Ananthaharan, A, Kravdal, G, Straume-Naesheim, TM. Utility and effectiveness of the Scandinavian guidelines to exclude computerized tomography scanning in mild traumatic brain injury - a prospective cohort study. BMC Emerg Med 2018;18:44. https://doi.org/10.1186/s12873-018-0193-2.Search in Google Scholar

34. JJS, Rickard, Di-Pietro, V, Smith, DJ, Davies, DJ, Belli, A, Goldberg Oppenheimer, P. Rapid optofluidic detection of biomarkers for traumatic brain injury via surface-enhanced Raman spectroscopy. Nat Biomed Eng 2020. https://doi.org/10.1038/s41551-019-0510-4.Search in Google Scholar

35. Yue, JK, Yuh, EL, Korley, FK, Winkler, EA, Sun, X, Puffer, RC, et al.. Association between plasma GFAP concentrations and MRI abnormalities in patients with CT-negative traumatic brain injury in the TRACK-TBI cohort: a prospective multicentre study. Lancet Neurol 2019;18:953–61. https://doi.org/10.1016/s1474-4422(19)30282-0.Search in Google Scholar

36. Simon-Pimmel, J, Lorton, F, Masson, D, Bouvier, D, Hanf, M, Gras-Le Guen, C. Reference ranges for serum S100B neuroprotein specific to infants under four months of age. Clin Biochem 2017;50:1056–60. https://doi.org/10.1016/j.clinbiochem.2017.08.014.Search in Google Scholar PubMed


Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2020-1293).


Received: 2020-08-25
Accepted: 2020-11-05
Published Online: 2020-11-25
Published in Print: 2021-04-27

© 2020 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Home pregnancy tests: quality first
  4. Review
  5. Non-invasive determination of uric acid in human saliva in the diagnosis of serious disorders
  6. Opinion Papers
  7. Basophil counting in hematology analyzers: time to discontinue?
  8. The role of laboratory hematology between technology and professionalism: the paradigm of basophil counting
  9. Recommendations for validation testing of home pregnancy tests (HPTs) in Europe
  10. General Clinical Chemistry and Laboratory Medicine
  11. The use of preanalytical quality indicators: a Turkish preliminary survey study
  12. The Italian External Quality Assessment (EQA) program on urinary sediment by microscopy examination: a 20 years journey
  13. Non-HDL-C/TG ratio indicates significant underestimation of calculated low-density lipoprotein cholesterol (LDL-C) better than TG level: a study on the reliability of mathematical formulas used for LDL-C estimation
  14. Evaluation of the protein gap for detection of abnormal serum gammaglobulin level: an imperfect predictor
  15. Impact of routine S100B protein assay on CT scan use in children with mild traumatic brain injury
  16. Using machine learning to develop an autoverification system in a clinical biochemistry laboratory
  17. Effect of collection matrix, platelet depletion, and storage conditions on plasma extracellular vesicles and extracellular vesicle-associated miRNAs measurements
  18. Pneumatic tube transportation of urine samples
  19. Evaluation of the first immunosuppressive drug assay available on a fully automated LC-MS/MS-based clinical analyzer suggests a new era in laboratory medicine
  20. A validated LC-MS/MS method for the simultaneous quantification of the novel combination antibiotic, ceftolozane–tazobactam, in plasma (total and unbound), CSF, urine and renal replacement therapy effluent: application to pilot pharmacokinetic studies
  21. Immunosuppressant quantification in intravenous microdialysate – towards novel quasi-continuous therapeutic drug monitoring in transplanted patients
  22. Reference Values and Biological Variations
  23. Reference intervals for venous blood gas measurement in adults
  24. Cardiovascular Diseases
  25. Detection and functional characterization of a novel MEF2A variation responsible for familial dilated cardiomyopathy
  26. Diabetes
  27. Evaluation of the ARKRAY HA-8190V instrument for HbA1c
  28. Infectious Diseases
  29. An original multiplex method to assess five different SARS-CoV-2 antibodies
  30. Evaluation of dried blood spots as alternative sampling material for serological detection of anti-SARS-CoV-2 antibodies using established ELISAs
  31. Variability of cycle threshold values in an external quality assessment scheme for detection of the SARS-CoV-2 virus genome by RT-PCR
  32. The vasoactive peptide MR-pro-adrenomedullin in COVID-19 patients: an observational study
  33. Corrigenda
  34. Corrigendum to: Understanding and managing interferences in clinical laboratory assays: the role of laboratory professionals
  35. Corrigendum to: Age appropriate reference intervals for eight kidney function and injury markers in infants, children and adolescents
  36. Letters to the Editor
  37. A panhaemocytometric approach to COVID-19: a retrospective study on the importance of monocyte and neutrophil population data on Sysmex XN-series analysers
  38. Letter in reply to the letter to the editor of Harte JV and Mykytiv V with the title “A panhaemocytometric approach to COVID-19: a retrospective study on the importance of monocyte and neutrophil population data”
  39. SARS-CoV-2 serologic tests: do not forget the good laboratory practice
  40. Long-term kinetics of anti-SARS-CoV-2 antibodies in a cohort of 197 hospitalized and non-hospitalized COVID-19 patients
  41. Self-sampling at home using volumetric absorptive microsampling: coupling analytical evaluation to volunteers’ perception in the context of a large scale study
  42. Vortex mixing to alleviate pseudothrombocytopenia in a blood specimen with platelet satellitism and platelet clumps
  43. Comparative evaluation of the fully automated HemosIL® AcuStar ADAMTS13 activity assay vs. ELISA: possible interference by autoantibodies different from anti ADAMTS-13
  44. Significant interference on specific point-of-care glucose measurements due to high dose of intravenous vitamin C therapy in critically ill patients
  45. As time goes by, on that you can rely preservation of urine samples for morphological analysis of erythrocytes and casts
  46. Stability of control materials for α-thalassemia immunochromatographic strip test
  47. Reformulated Architect® cyclosporine CMIA assay: improved imprecision, worse comparability between methods
  48. Urine-to-plasma contamination mimicking acute kidney injury: small drops with major consequences
  49. Automated Mindray CL-1200i chemiluminescent assays of renin and aldosterone for the diagnosis of primary aldosteronism
  50. Use of common reference intervals does not necessarily allow inter-method numerical result trending
  51. Reply to Dr Hawkins regarding comparability of results for monitoring
Downloaded on 9.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/cclm-2020-1293/pdf
Scroll to top button