Evidence map›Paper›PMID 35647317›Full record

ArticleEuropean stroke journal2022

Analysis and modelling of mistriage in the Stockholm stroke triage system.

Boris Keselman, Annika Berglund, Niaz Ahmed, David Grannas, Mia von Euler, Staffan Holmin, Ann-Charlotte Laska, Jan M Mathé, Christina Sjöstrand, Einar E Eriksson and 1 more

Open access · bronzeAbstract read
In one paragraph

Article in European stroke journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 34% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. 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

11 authors at 4 institutions in 2 countries.

Boris KeselmanDepartment of Neurology, Karolinska University Hospital, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-1579-6983
Annika BerglundDepartment of Neurology, Karolinska University Hospital, Stockholm, Sweden.
Niaz AhmedDepartment of Neurology, Karolinska University Hospital, Stockholm, Sweden.
David GrannasUnit of Biostatistics, IMM, Karolinska Institutet, Stockholm, Sweden.
Mia von EulerDepartment of Clinical Science and Education, Karolinska Institutet Stroke Research Network at Södersjukhuset, Stockholm, Sweden.
Staffan HolminDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Ann-Charlotte LaskaDepartment of Clinical Sciences, Danderyd Hospital Karolinska Institutet, Stockholm, Sweden.
Jan M MathéDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Christina SjöstrandDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Einar E ErikssonDepartment of Neurology, Karolinska University Hospital, Stockholm, Sweden.
Michael V MazyaDepartment of Neurology, Karolinska University Hospital, Stockholm, Sweden.
Karolinska University Hospital · SEKarolinska Institutet · SEDanderyds sjukhus · SEÖrebro University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The Stockholm Stroke Triage System (SSTS) is a prehospital triage system for detection of patients eligible for endovascular thrombectomy (EVT). Assessment of hemiparesis combined with ambulance-hospital teleconsultation is used to route patients directly to the thrombectomy centre. Some patients are not identified and require secondary transport for EVT (undertriage) while others taken to the thrombectomy centre do not undergo EVT (overtriage). The aims of this study were to characterize mistriaged patients, model for and evaluate alternative triage algorithms. Patients and methods: Patients with suspected stroke transported by priority 1 ground ambulance between October 2017 and October 2018 (n = 2905) were included. Three triage algorithms were modelled using prehospital data. Decision curve analysis was performed to calculate net benefit (correctly routing patients for EVT without increasing mistriage) of alternative models vs SSTS. Results: Undertriage for EVT occurred in n = 35/2582 (1.4%) and overtriage in n = 239/323 (74.0%). Compared to correct thrombectomy triages, undertriaged patients were younger and had lower median NIHSS (10 vs 18), despite 62.9% with an M1 occlusion. In overtriaged patients, 77.0% had a stroke diagnosis (29.7% haemorrhagic). Hemiparesis and FAST items Discussion: Undertriaged patients had lower NIHSS, likely due to better compensated proximal occlusions. SSTS was superior to other models for identifying EVT candidates, but lacked information allowing comparison to other prehospital scales. Conclusion: Using prehospital data, alternative models did not outperform the SSTS in finding EVT candidates.

Indexed as

ambulancedecision curve analysisStrokethrombectomytriage

Identifiers

PMID35647317
PMCPMC9134772
OpenAlexW4213415587

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.