Evidence map›Paper›PMID 35989921›Full record

ArticleFrontiers in neurology2022

mG-FAST, a single pre-hospital stroke screen for evaluating large vessel and non-large vessel strokes.

Roy El Koussa, Sarah Linder, Alicia Quayson, Shawn Banash, James J MacNeal, Parshva Shah, Mariaelana Brenner, Ross Levine, Osama O Zaidat, Vibhav Bansal

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
0.8field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Prehospital stroke management and mobile stroke units.Current opinion in neurology · 2023
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Roy El KoussaDepartment of Internal Medicine, Mercy Health Javon Bea Hospital, Rockford, IL, United States.
Sarah LinderDepartment of Interventional Neurology, Mercy Health Javon Bea Hospital, Rockford, IL, United States.
Alicia QuaysonDepartment of Interventional Neurology, Mercy Health Javon Bea Hospital, Rockford, IL, United States.
Shawn BanashDepartment of Internal Medicine, Mercy Health Javon Bea Hospital, Rockford, IL, United States.
James J MacNealDepartment of Emergency Medicine, Mercy Health Javon Bea Hospital, Rockford, IL, United States.
Parshva ShahCollege of Medicine, University of Illinois Rockford, Rockford, IL, United States.
Mariaelana BrennerCollege of Medicine, University of Illinois Rockford, Rockford, IL, United States.
Ross LevineDepartment of Neurology, Mercy Health Hospital and Trauma Center, Janesville, WI, United States.
Osama O ZaidatDepartment of Neurology, Bon Secours Mercy Health St. Vincent Medical Center, Toledo, OH, United States.
Vibhav BansalDepartment of Interventional Neurology, Mercy Health Javon Bea Hospital, Rockford, IL, United States.
Mercy Health · USUniversity of Illinois Chicago, Rockford campus · USBon Secours Mercy Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Several stroke scales have been implemented to enhance early recognition of large vessel occlusion (LVO) in the field. These scales necessitate a tiered approach requiring emergency medical services (EMS) to utilize two scales, one for identifying stroke and another for differentiating LVO from non-LVO. Ideally, a single stroke scale should be utilized by EMS for triage. Methods: This is a prospective analysis of 150 consecutive patients presenting with stroke symptoms from the field. The stroke scale modified Gaze-Face-Arm-Speech-Time (mG-FAST) was used to simultaneously identify stroke and detect LVO in the pre-hospital setting. Imaging was used to confirm the presence of a LVO and determine the sensitivity and specificity of mG-FAST. The receiver operating curve (ROC) was plotted to calculate the area under the curve (AUC). Youden's index was used to determine the optimal cutoff score. Inter-rater reliability was obtained by comparing the EMS and stroke provider mG-FAST scores. EMS dispatch-to-thrombectomy-capable stroke center (mothership, MS) arrival time and groin puncture time were compared before and after the implementation of mG-FAST. Results: 33/150 patients had a confirmed LVO by imaging. 32/33 patients had an mG-FAST score ≥3. The AUC of mG-FAST was 0.899. An mG-FAST cut-off point of ≥3 yielded a sensitivity of 0.97 and specificity of 0.55 for LVO. The accuracy of this cut-off point was 64%. The EMS dispatch-to-MS time and groin puncture time decreased by 22 and 40 min after implementation of mG-FAST, respectively. With admission to the MS, the EMS dispatch-to-MS time decreased by 174.7 min compared to admission to a drip-and-ship (DS) hospital. Conclusions: Utilizing a single stroke scale in the field improves EMS dispatch-to-MS time, EMS dispatch-to-groin puncture time, and EMS door-to-intervention time. Implementation of mG-FAST as a pre-hospital screening tool is an effective method of triaging patients to the MS or DS hospitals.

Indexed as

G-FASTlarge vessel occlusionmG-FASTpre-hospital screeningstrokestroke scalestroke scoretriage

Identifiers

PMID35989921
PMCPMC9381732
OpenAlexW4289517262

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.