Prospective Validation of Glial Fibrillary Acidic Protein, <scp>d</scp> ‐Dimer, and Clinical Scales for Acute Large‐Vessel Occlusion Ischemic Stroke Detection
Bibliographic record
Abstract
Background: Large-vessel occlusion (LVO) ischemic stroke is responsible for significant morbidity and mortality. We have previously described a novel tool for acute LVO detection that combines blood-based biomarkers (glial fibrillary acidic protein and d-dimer) with stroke severity scales to achieve high accuracy. Accordingly, the present study sought to prospectively validate cutoff values that we had previously established for biomarkers and scales. Methods: The TIME (Testing for Identification Markers of Stroke) trial was designed as a prospective observational diagnostic accuracy study. All ambulance-identified stroke code activations <18 hours from symptom onset were recruited at Brandon Regional Hospital (Brandon, FL) between May 2021 and August 2022. Previously determined cutoff concentrations of plasma glial fibrillary acidic protein (213 pg/mL) and d-dimer (600 ng/mL) were used in combination with prehospital stroke scales to detect LVO. We compared rates of LVO detection against a reference standard using computed tomography/magnetic resonance angiography. Results: A total of 382 patients with suspected stroke were recruited. The final cohort was composed of 323 patients with suspected stroke with the following distribution: LVO ischemic stroke (n = 29, 9%), non-LVO ischemic stroke (n = 48, 15%), hemorrhagic stroke (n = 13, 4%), transient ischemic attack (n = 12, 3.9%), and stroke mimics (n = 220, 68.1%). Combining blood-based biomarkers (glial fibrillary acidic protein and d-dimer) with the scale field assessment stroke triage for emergency destination yielded the best performance for LVO detection, with specificity of 94% and sensitivity of 71%. Performance was found to be higher in a subanalysis focusing on patients presenting <6 hours from symptom onset, with 93% specificity and 81% sensitivity. Critically, application of the biomarker and stroke scale algorithms ruled out all patients with hemorrhage. Conclusion: The present work prospectively validated the potential utility of previously defined glial fibrillary acidic protein and d-dimer cutoff levels (ie, 213 pg/mL and 600 ng/mL, respectively), demonstrating their value for discrimination of LVO stroke from differential diagnoses during code stroke workups. (ClinicalTrials.gov number, NCT04292600.).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".