Identification of an epidural hematoma using blood-based biomarkers
Malmi, Katja (2025-02-21)
Identification of an epidural hematoma using blood-based biomarkers
(21.02.2025)
Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.
suljettu
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2025030315151
https://urn.fi/URN:NBN:fi-fe2025030315151
Tiivistelmä
Background: Blood-based biomarkers have shown promise in identifying head injury patients with acute traumatic intracranial findings. However their capacity in detecting patients with isolated extra-axial hematomas remains unknown. The objective of this study was to assess the potential S100 calcium-binding protein B (S100B), glial fibrillary acid protein (GFAP), total tau (t-tau), neurofilament light (NfL), ubiquitin C-terminal hydrolase L1 (UCH-L1), and neuron specific enolase (NSE) to identify mild traumatic brain injury (mTBI) patients with epidural hematoma (EDH).
Methodology: This prospective study included 1048 patients (median age 46 years, interquartile range 28-63) with mTBI (GCS ≥13) with 1) all six serum blood biomarker levels measured and 2) acute head computed tomography (CT) scan within 24 hours of injury. The main outcome measure was the area under the curve of the receiver operating characteristic (AUC) for each biomarker in distinguishing between patients with CT-negative findings and those with EDH with no other potentially surgical findings, i.e. subdural or intraparenchymal hemorrhage (EDHsolo). An AUC≥0.7 was considered clinically adequate. In patients with EDHsolo, a distinction was made between i) isolated epidural hematoma, meaning EDH as an only CT finding (iEDH) and ii) EDH occuring concomitantly with non-surgical findings (e.g. subarachnoid hemorrhage, intraventricular hemorrhage, and/or signs of axonal injury) (EDHns). We also assessed the impact of major extracranial injury (MEI) and EDH volume as well as biomarker intercorrelations.
Results: Of the included patients, 38 (3,6%) patients had an iEDH, 28 (2,7%) patients had EDHns, and 982 patients had CT-negative findings (94%). GFAP displayed the highest AUC for identifying an EDHsolo (0.82, 95% CI 0.78-0.87), iEDH (0.77, 95% CI 0.71-0.83), and a clinically significant EDH (0.82, 95% CI 0.78-0.87). When excluding patients with MEI, overall discrimination slightly increased for all six biomarkers. The GFAP cut-off with the highest NPV for identifying an EDHsolo or an iEDH was 0.19 ng/ml regardless of the presence of MEI. Combination of GFAP and UCH-L1 did not improve the identification of the patients in any subgroup. No significant correlation was found between EDH volume and biomarker levels.
Conclusion: Blood levels of GFAP adequately discriminated mTBI patients with EDH.
Methodology: This prospective study included 1048 patients (median age 46 years, interquartile range 28-63) with mTBI (GCS ≥13) with 1) all six serum blood biomarker levels measured and 2) acute head computed tomography (CT) scan within 24 hours of injury. The main outcome measure was the area under the curve of the receiver operating characteristic (AUC) for each biomarker in distinguishing between patients with CT-negative findings and those with EDH with no other potentially surgical findings, i.e. subdural or intraparenchymal hemorrhage (EDHsolo). An AUC≥0.7 was considered clinically adequate. In patients with EDHsolo, a distinction was made between i) isolated epidural hematoma, meaning EDH as an only CT finding (iEDH) and ii) EDH occuring concomitantly with non-surgical findings (e.g. subarachnoid hemorrhage, intraventricular hemorrhage, and/or signs of axonal injury) (EDHns). We also assessed the impact of major extracranial injury (MEI) and EDH volume as well as biomarker intercorrelations.
Results: Of the included patients, 38 (3,6%) patients had an iEDH, 28 (2,7%) patients had EDHns, and 982 patients had CT-negative findings (94%). GFAP displayed the highest AUC for identifying an EDHsolo (0.82, 95% CI 0.78-0.87), iEDH (0.77, 95% CI 0.71-0.83), and a clinically significant EDH (0.82, 95% CI 0.78-0.87). When excluding patients with MEI, overall discrimination slightly increased for all six biomarkers. The GFAP cut-off with the highest NPV for identifying an EDHsolo or an iEDH was 0.19 ng/ml regardless of the presence of MEI. Combination of GFAP and UCH-L1 did not improve the identification of the patients in any subgroup. No significant correlation was found between EDH volume and biomarker levels.
Conclusion: Blood levels of GFAP adequately discriminated mTBI patients with EDH.