A Systematic Review of the Usefulness of Glial Fibrillary Acidic Protein for Predicting Acute Intracranial Lesions following Head Trauma
Bibliographic record
Abstract
BACKGROUND: The extensive use of computed tomography (CT) after acute head injury is costly and carries potential iatrogenic risk. This systematic review examined the usefulness of blood-based glial fibrillary acidic protein (GFAP) for predicting acute trauma-related CT-positive intracranial lesions following head trauma. The main objective was to summarize the current evidence on blood-based GFAP as a potential screening test for acute CT-positive intracranial lesions following head trauma. METHODS: We screened MEDLINE, EMBASE, PsychInfo, CINAHL, Web of Science, the Cochrane Database, Scopus, Clinical Trials, OpenGrey, ResearchGate, and the reference lists of eligible publications for original contributions published between January 1980 and January 2017. Eligibility criteria included: (i) population: human head and brain injuries of all severities and ages; (ii) intervention: blood-based GFAP measurement ≤24 h post-injury; and (iii) outcome: acute traumatic lesion on non-contrast head CT ≤24 h post-injury. Three authors completed the publication screening, data extraction, and quality assessment of eligible articles. RESULTS: The initial search identified 4,706 articles, with 51 eligible for subsequent full-text assessment. Twenty-seven articles were ultimately included. Twenty-four (89%) studies reported a positive association between GFAP level and acute trauma-related intracranial lesions on head CT. The area under the receiver operating characteristic curve for GFAP prediction of intracranial pathology ranged from 0.74 to 0.98 indicating good to excellent discrimination. GFAP seemed to discriminate mass lesions and diffuse injury, with mass lesions having significantly higher GFAP levels. There was considerable variability between the measured GFAP averages between studies and assays. No well-designed diagnostic studies with specific GFAP cutoff values predictive of acute traumatic intracranial lesions have been published. CONCLUSION: Intracranial CT-positive trauma lesions were associated with elevated GFAP levels in the majority of studies. Methodological heterogeneity in GFAP assessments and the lack of well-designed diagnostic studies with commercially validated GFAP platforms hinder the level of evidence, and variability in levels of GFAP with no clearly established cutoff for abnormality limit the clinical usefulness of the biomarker. However, blood-based GFAP holds promise as a means of screening for acute traumatic CT-positive lesion following head trauma.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".