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Record W4406992591 · doi:10.1161/str.56.suppl_1.tmp25

Abstract TMP25: Potential of Rapid GFAP Levels in Acute Undifferentiated Stroke <24 Hours from Onset Using A Point-Of-Care Platform: An Exploratory Analysis of a Prospective Study

2025· article· en· W4406992591 on OpenAlexaff
Julien F. Paul, Yasmine Bairi, Clara Margarido, Catherine Larochelle, Nathalie Arbour, Christian Stapf, Laura Gioia

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineStroke (engine)Point of careAcute strokeProspective cohort studyInternal medicinePathology

Abstract

fetched live from OpenAlex

Introduction: Glial fibrillary acidic protein (GFAP), highly brain-specific, is emerging as an attractive blood biomarker in acute stroke. GFAP can discriminate stroke type (ischemic stroke (IS), intracerebral hemorrhage (ICH), stroke mimics (SM) in the first hours after stroke onset. Rapid GFAP levels using novel point-of-care technology (results <15 minutes) may also offer insights in IS, particularly among those with unknown onset. In this study, we aim to evaluate the potential of rapid GFAP levels to distinguish among stroke types in acute undifferentiated stroke <24h from onset, as well as provide insights in IS of unknown onset. Methods: An exploratory analysis of an ongoing prospective study of patients with suspected undifferentiated stroke <24h from onset. Rapid plasma GFAP levels (pg/mL) are measured at hospital arrival using the i-STAT Alinity ® instrument and commercially-available cartridges. Study endpoints include quantitative GFAP levels according to final diagnosis (ICH, IS, SM), time from stroke onset/last seen well (<4.5h, 4.5-24h), and ASPECTS score (8-10 vs. <8). Results: Among the first 101 patients recruited (mean (±SD) 70.8±14.5 years, 48% female, median (IQR) NIHSS 9 (3-20), median ASPECTS (10 (8-10)), final diagnosis was IS (n=67 (33 LVO)), ICH (n=5), and SM (n=29). Median rapid GFAP levels were highest in ICH (3104 (2088-8622) pg/mL), and differed compared to IS (54 (30-100) pg/mL) and SM (29 (29-42) pg/mL), p<0.001. In IS, 58% patients presented <4.5h from onset, and 28% were wake-up strokes. Rapid GFAP levels were undetectable in 13/39 (33%) of IS <4.5h compared to 3/28 (11%) in IS >4.5h, p=0.03. Median GFAP levels was significantly higher in IS >4.5h (87 (42-134) pg/mL) compared to earlier presentations (44 (29-62) pg/mL, p=0.03). Lastly, median GFAP levels had fairly good discriminative ability to detect ASPECTS <8 (AUC 0.73 (95% CI: 0.55-0.91), p=0.003), with an optimal GFAP cutoff of 77 pg/mL (sensitivity 76.9%, specificity 76.9%). Conclusion: Rapid GFAP levels using novel point-of-care technology is feasible and show promise in acute stroke management. Beyond discrimination of stroke type, rapid GFAP levels appear to increase during the first 24 hours from IS onset and with extent of ischemic injury. These findings, although preliminary, suggest that rapid GFAP levels may inform treatment decisions in IS of unknown onset as well as optimize prehospital triage of acute undifferentiated stroke <24hours from onset.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.304
Teacher spread0.275 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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