Evidence map›Paper›PMID 37840869›Full record

ReviewArchives of academic emergency medicine2023

Recognition of Stroke in the Emergency Room (ROSIER) Scale in Identifying Strokes and Transient Ischemic Attacks (TIAs); a Systematic Review and Meta-Analysis.

Iman Chehregani Rad, Amir Azimi

Open access · greenAbstract readReview
In one paragraph

Review in Archives of academic emergency medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 24% 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, 4 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
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

2 authors.

Iman Chehregani Rad
Amir Azimi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: A range of screening tools has been developed to assist emergency healthcare providers in rapidly and accurately diagnosing strokes. In this study, we investigated the diagnostic value of the Recognition of Stroke in the Emergency Room (ROSIER) scale in identifying individuals with stroke and transient ischemic attack (TIA). Methods: We conducted a systematic search across online databases of PubMed, Embase, Scopus, and Web of Science until June 12th, 2023, aiming to identify studies that assessed the diagnostic performance of the ROSIER scale in detecting strokes and TIAs among individuals with suspected stroke symptoms. Results: Data extracted from 34 studies were analyzed, demonstrating that the ROSIER score, with a cut-off value of ≥ 1, has sensitivity of 0.89 (95% confidence interval (CI): 0.86-0.92), specificity of 0.76 (95% CI: 0.69-0.81), diagnostic odds ratio (DOR) of 25.41 (95% CI: 17.2-37.54), and area under the curve (AUC) of 0.91 (95% CI: 0.85-0.90) in detection of strokes and TIAs. Meta-regression subgroup analysis revealed variations in sensitivity and specificity based on different settings and assessors. Sensitivity was higher in pre-hospital settings when the test was administered by emergency medical services (EMS) and emergency department (ED) paramedic staff, whereas specificity was higher in emergency department settings and when physicians and neurologists conducted the test. Conclusion: A moderate level of evidence shows that the ROSIER scale is considered an excellent tool for identifying strokes and TIAs. As a valid method for identifying strokes, it holds applicability across diverse settings and can be effectively used by assessors with different specialties.

Indexed as

DiagnosisDiagnostic techniques and proceduresMeta-analysisStrokeSystematic review

Identifiers

PMID37840869
PMCPMC10568950
OpenAlexW4387661274

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.