European Stroke Organisation (ESO) guidelines on mobile stroke units for prehospital stroke management
Bibliographic record
Abstract
The safety and efficacy of mobile stroke units (MSUs) in prehospital stroke management has recently been investigated in different clinical studies. MSUs are ambulances equipped with a CT scanner, point-of-care lab, telemedicine and are staffed with a stroke specialised medical team. This European Stroke Organisation (ESO) guideline provides an up-to-date evidence-based recommendation to assist decision-makers in their choice on using MSUs for prehospital management of suspected stroke, which includes patients with acute ischaemic stroke (AIS), intracranial haemorrhage (ICH) and stroke mimics. The guidelines were developed according to the ESO standard operating procedure and Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology. The working group identified relevant clinical questions, performed systematic reviews and aggregated data meta-analyses of the literature, assessed the quality of the available evidence and made specific recommendations. Expert consensus statements are provided where sufficient evidence was not available to provide recommendations based on the GRADE approach. We found moderate evidence for suggesting MSU management for patients with suspected stroke. The patient group diagnosed with AIS shows an improvement of functional outcomes at 90 days, reduced onset to treatment times and increased proportion receiving IVT within 60 min from onset. MSU management might be beneficial for patients with ICH as MSU management was associated with a higher proportion of ICH patients being primarily transported to tertiary care stroke centres. No safety concerns (all-cause mortality, proportion of stroke mimics treated with IVT, symptomatic intracranial bleeding and major extracranial bleeding) could be identified for all patients managed with a MSU compared to conventional care. We suggest MSU management to improve prehospital management of suspected stroke patients.
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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 | 0.022 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".