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Record W4406995406 · doi:10.1161/str.56.suppl_1.144

Abstract 144: Mobile Stroke Unit Management and Outcomes in Undifferentiated Patients with Stroke-Like Symptoms in the Prehospital Setting: A Nationwide Cohort Study

2025· article· en· W4406995406 on OpenAlexaff
Brian Mac Grory, Jie‐Lena Sun, Brooke Alhanti, Jay B. Lusk, Li Fan, Opeolu Adeoye, Karen L. Furie, David Hasan, Steven R. Messé, Kevin N. Sheth, Lee H. Schwamm, Eric E. Smith, Deepak L. Bhatt, Gregg C. Fonarow, Jeffrey L. Saver, Ying Xian, James C. Grotta

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineStroke (engine)CohortEmergency medicineAcute strokeCohort studyInternal medicineTissue plasminogen activator

Abstract

fetched live from OpenAlex

Introduction: Prospective, controlled clinical trials have suggested that prehospital management in a mobile stroke unit (MSU) improves functional outcomes in intravenous (IV) thrombolysis-eligible patients. However, because MSUs are dispatched prior to knowledge of the diagnosis, an examination of their real-world effectiveness must include all patients for whom stroke is suspected. The objective of this study was to determine the association between MSU management vs. EMS management and outcomes in all patients with suspected stroke in the prehospital setting. Methods: We performed a retrospective, observational, cohort study from the American Heart Association’s Get With The Guidelines®-Stroke (GWTG-Stroke) Program between August 1 st 2018 and January 31 st 2023. At participating hospitals receiving both MSU-managed and standard EMS-managed patients, all patients with stroke-like symptoms in the prehospital setting were analyzed. The primary efficacy end point was the level of global disability assessed with the utility-weighted modified Rankin Scale (UW-mRS; rage 0.00 – 1.00). The secondary efficacy end point was ambulatory status. The co-primary safety end points were symptomatic intracranial hemorrhage (sICH) and in-hospital mortality. Results: Of 108,684 patients (median age 73 [Q1,Q3: 62,83]; 51.2% female), 4,218 (3.9%) received prehospital management in an MSU. Prehospital management in an MSU was associated with a better score on the UW-mRS at discharge (adjusted mean difference 0.05 [95% CI: 0.03 – 0.06]) and a higher likelihood of independent ambulation at discharge (51.0% [1,521/2,985] vs. 47.8% [31,450/79,699]; aRR 1.11 [95% CI: 1.08 – 1.15]; adjusted risk difference 5.2% [95% CI: 3.7 to 6.8]). There was no statistically significant difference in sICH (4.0% vs. 4.1%; aRR 1.02 [95% CI: 0.82 – 1.25]). There was a lower rate of in-hospital mortality (6.4% vs. 8.7%; aRR: 0.78 [95% CI: 0.71 to 0.87]) in MSU-treated patients. Conclusions: Among patients with stroke-like symptoms in the prehospital setting, prehospital management in an MSU compared with EMS management was associated with a significantly lower level of global disability. These findings support policy efforts to expand access to MSU care in the United States.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.005
GPT teacher head0.258
Teacher spread0.254 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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