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S100B, GFAP, UCH-L1 and NSE as predictors of abnormalities on CT imaging following mild traumatic brain injury: a systematic review and meta-analysis of diagnostic test accuracy

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Abstract

Biomarkers such as calcium channel binding protein S100 subunit beta (S100B), glial fibrillary acidic protein (GFAP), ubiquitin c-terminal hydrolase L1 (UCH-L1) and neuron-specific enolase (NSE) have been proposed to aid in screening patients presenting with mild traumatic brain injury (mTBI). As such, we aimed to characterise their accuracy at various thresholds. MEDLINE, SCOPUS and EMBASE were searched, and articles reporting the diagnostic performance of included biomarkers were eligible for inclusion. Risk of bias was assessed using the QUADAS-II criteria. A meta-analysis was performed to assess the predictive value of biomarkers for imaging abnormalities on CT. A total of 2939 citations were identified, and 38 studies were included. Thirty-two studies reported data for S100B. At its conventional threshold of 0.1 μg/L, S100B had a pooled sensitivity of 91% (95%CI 87–94) and a specificity of 30% (95%CI 26–34). The optimal threshold for S100B was 0.72 μg/L, with a sensitivity of 61% (95% CI 50–72) and a specificity of 69% (95% CI 64–74). Nine studies reported data for GFAP. The optimal threshold for GFAP was 626 pg/mL, at which the sensitivity was 71% (95%CI 41–91) and specificity was 71% (95%CI 43–90). Sensitivity of GFAP was maximised at a threshold of 22 pg/mL, which had a sensitivity of 93% (95%CI 73–99) and a specificity of 36% (95%CI 12–68%). Three studies reported data for NSE and two studies for UCH-L1, which precluded meta-analysis. There is evidence to support the use of S100B as a screening tool in mild TBI, and potential advantages to the use of GFAP, which requires further investigation.

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Availability of data and material

The dataset used to generate the results is available upon reasonable request to the corresponding author.

Code availability

The statistical code used to generate the results is available upon reasonable request to the corresponding author.

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Funding

Michael Amoo received funding through the Royal College of Surgeons/Beacon Hospital StAR MD scholarship programme.

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Authors and Affiliations

  1. Department of Neurosurgery, Royal College of Surgeons in Ireland, Dublin, Ireland

    Michael Amoo, Philip J. O’Halloran, Paul Brennan, Mohammed Ben Husien, John Caird, Mohsen Javadpour & Gerard F. Curley

  2. National Neurosurgical Centre, Beaumont Hospital, Dublin 9, Ireland

    Michael Amoo, Jack Henry, Mohammed Ben Husien, John Caird & Mohsen Javadpour

  3. Beacon Academy, Beacon Hospital, Sandyford, Dublin 18, Ireland

    Michael Amoo

  4. School of Medicine, University College Dublin, Dublin, Ireland

    Jack Henry

  5. Department of Radiology, Beaumont Hospital, Dublin 9, Ireland

    Paul Brennan

  6. Department of Genetics, Trinity College Dublin, Dublin 2, Ireland

    Matthew Campbell

  7. Department of Academic Neurology, Trinity College Dublin, Dublin 2, Ireland

    Mohsen Javadpour

  8. Department of Anaesthesia and Critical Care, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland

    Gerard F. Curley

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Contributions

Concept and design: MA, JH, PB, MBH, MC, JC, MJ, GFC.

Data acquisition: MA, JH.

Statistical analysis: MA, JH.

Interpretation of data: MA, JH, PJOH, PB, MBH, MC, JC, MJ, GFC.

Writing: MA, JH.

Review and revision of manuscript: MA, JH, PJOH, PB, MBH, MC, JC, MJ, GFC.

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Correspondence to Michael Amoo.

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Amoo, M., Henry, J., O’Halloran, P.J. et al. S100B, GFAP, UCH-L1 and NSE as predictors of abnormalities on CT imaging following mild traumatic brain injury: a systematic review and meta-analysis of diagnostic test accuracy. Neurosurg Rev 45, 1171–1193 (2022). https://doi.org/10.1007/s10143-021-01678-z

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