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Record W4414740589 · doi:10.1093/clinchem/hvaf086.388

A-404 Evaluating the need for head CT in mild TBI patients using a whole blood point-of-care test within 24 hours of suspected head injury

2025· article· en· W4414740589 on OpenAlexaff
J. D. Smith, Swati Pradhan-Bhatt, Raj Chandran, Ksenia Musaelyan, Paula Bernander, J A Marino, Susan Brophy, Manish Gupta, Beth McQuiston, Adam Moss

Bibliographic record

VenueClinical Chemistry · 2025
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsAbbott (Canada)
Fundersnot available
KeywordsTraumatic brain injuryHead injuryWhole bloodEmergency departmentVenous bloodHead traumaGlial fibrillary acidic proteinBlood test

Abstract

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Abstract Background Approximately 69 million people worldwide experience a traumatic brain injury (TBI) annually. In the Emergency Department, over 80% of patients evaluated for TBI undergo head CT scans, but fewer than 10% of these scans reveal acute traumatic abnormalities. This highlights the need for objective, rapid, and accurate tools to help clinicians evaluate patients with suspected TBI, significantly improving patient care by reducing unnecessary radiation exposure, minimizing wait times, and optimizing resource utilization. The i-STAT® TBI test represents a significant advancement in TBI diagnostics. This point-of-care test measures two key brain injury biomarkers, glial fibrillary acidic protein (GFAP) and ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1). Its recent regulatory clearance for clinical use with venous whole blood enhances its utility and accessibility in various environments, including bedside use. This study demonstrates the analytical and clinical performance of the whole blood TBI test. Methods The i-STAT TBI test is a panel of in vitro diagnostic immunoassays for the quantitative measurements of GFAP and UCH-L1 in 20 µL of venous whole blood. Performance characteristics such as detection limits, imprecision, linearity, measuring interval, and potential interference due to drugs of abuse were established following CLSI guidance. Clinical performance was evaluated in a prospective study across 20 U.S. sites. The study enrolled 970 adult patients with suspected mild TBI who presented with initial GCS scores of 13-15 within 24 hours of injury and had a head CT scan ordered as part of standard care. Results The reportable range of the GFAP assay extended from 47 pg/mL to 10,000 pg/mL. For UCH-L1, the range extended from 87 pg/mL to 3,200 pg/mL. Within-laboratory imprecision ranged from 3.98% to 24.62% CV for GFAP and 4.81% to 11.64% CV for UCH-L1. The linearity of GFAP and UCH-L1 assays was established using venous whole blood samples of varying antigen levels. Deviations from linearity were =15% for GFAP and =10% for UCH-L1. Additionally, drugs of abuse were tested and no interference was observed with TBI assays at concentrations up to 2.25 times the highest therapeutic drug concentration. In the clinical performance study, 283 had positive CT imaging showing acute traumatic intracranial lesions, while 687 had negative scans (no acute trauma-related findings). The TBI test correctly identified 273 of the 283 CT-positive patients as “Elevated,” resulting in a clinical sensitivity of 96.5%. All patients requiring neurosurgical intervention were classified as “Elevated.” Among the 687 patients with negative CT scans, 277 were identified as “Not Elevated,” reflecting a specificity of 40.3%. These metrics translated into an overall negative predictive value of 96.5%, indicating that most patients testing “Not Elevated” had no lesions on head CT. Conclusion The i-STAT TBI test allows for expanded utility and easier accessibility of TBI biomarkers for bedside evaluation. This test demonstrated high clinical performance in ruling out intracranial lesions visible on CT imaging in adult mild TBI patients seen within 24 hours of trauma. The TBI test provides an objective tool to reduce unnecessary neuroimaging in mild TBI cases and potentially alleviate the associated resource and radiation burdens.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.085
GPT teacher head0.418
Teacher spread0.333 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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