Evidence map›Paper›PMID 33023425›Full record

ArticleStroke2020

Prehospital Triage Strategies for the Transportation of Suspected Stroke Patients in the United States.

Esmee Venema, James F Burke, Bob Roozenbeek, Jason Nelson, Hester F Lingsma, Diederik W J Dippel, David M Kent

Open access · hybridAbstract read
In one paragraph

Article in Stroke, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
3.1field-weighted citation impact, top 7% 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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 35 citations in OpenAlex.

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  18. Large Vessel Occlusion Stroke Detection in the Prehospital Environment.Current emergency and hospital medicine reports · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Esmee VenemaDepartment of Neurology (E.V., B.R., D.W.J.D.), Erasmus MC, University Medical Center, Rotterdam, the Netherlands.
James F BurkeDepartment of Neurology, University of Michigan, Ann Arbor, MI (J.F.B.).
Bob RoozenbeekDepartment of Neurology (E.V., B.R., D.W.J.D.), Erasmus MC, University Medical Center, Rotterdam, the Netherlands.
Jason NelsonPredictive Analytics and Comparative Effectiveness Center, Tufts Medical Center, Boston, MA (J.N., D.M.K.).
Hester F LingsmaDepartment of Public Health (E.V., H.F.L.), Erasmus MC, University Medical Center, Rotterdam, the Netherlands.
Diederik W J DippelDepartment of Neurology (E.V., B.R., D.W.J.D.), Erasmus MC, University Medical Center, Rotterdam, the Netherlands.
David M KentPredictive Analytics and Comparative Effectiveness Center, Tufts Medical Center, Boston, MA (J.N., D.M.K.).
Erasmus MC · NLPredictive Science (United States) · USUniversity of Michigan · US

Funding

Enabling Comparative Effectiveness Research in Silent Brain Infarction Through Natural Language Processing and Big DataR01NS102233 · NINDS · TUFTS MEDICAL CENTER · PI DAVID M KENT · 2017 to 2026
$3.4M
NINDS NIH HHS R01 NS102233Patient-Centered Outcomes Research Institute ME-1606-35555
6 · The paper itself

Abstract

background and purposeIschemic stroke patients with large vessel occlusion (LVO) could benefit from direct transportation to an intervention center for endovascular treatment, but non-LVO patients need rapid IV thrombolysis in the nearest center. Our aim was to evaluate prehospital triage strategies for suspected stroke patients in the United States.

methodsWe used a decision tree model and geographic information system to estimate outcome of suspected stroke patients transported by ambulance within 4.5 hours after symptom onset. We compared the following strategies: (1) Always to nearest center, (2) American Heart Association algorithm (ie, directly to intervention center if a prehospital stroke scale suggests LVO and total driving time from scene to intervention center is <30 minutes, provided that the delay would not exclude from thrombolysis), (3) modified algorithms with a maximum additional driving time to the intervention center of <30 minutes, <60 minutes, or without time limit, and (4) always to intervention center. Primary outcome was the annual number of good outcomes, defined as modified Rankin Scale score of 0-2. The preferred strategy was the one that resulted in the best outcomes with an incremental number needed to transport to intervention center (NNTI) <100 to prevent one death or severe disability (modified Rankin Scale score of >2).

resultsNationwide implementation of the American Heart Association algorithm increased the number of good outcomes by 594 (+1.0%) compared with transportation to the nearest center. The associated number of non-LVO patients transported to the intervention center was 16 714 (NNTI 28). The modified algorithms yielded an increase of 1013 (+1.8%) to 1369 (+2.4%) good outcomes, with a NNTI varying between 28 and 32. The algorithm without time limit was preferred in the majority of states (n=32 [65%]), followed by the algorithm with <60 minutes delay (n=10 [20%]). Tailoring policies at county-level slightly reduced the total number of transportations to the intervention center (NNTI 31).

conclusionsPrehospital triage strategies can greatly improve outcomes of the ischemic stroke population in the United States, but increase the number of non-LVO stroke patients transported to an intervention center. The current American Heart Association algorithm is suboptimal as a nationwide policy and should be modified to allow more delay when directly transporting LVO-suspected patients to an intervention center.

Indexed as

Time-to-TreatmentAlgorithmsAmbulancesAmerican Heart AssociationDecision TreesEmergency Medical ServicesEndovascular ProceduresGeographic Information SystemsHealth PolicyHumansIschemic StrokePatient TransferSeverity of Illness IndexThrombectomyThrombolytic TherapyTransportation of PatientsambulancesAmerican Heart Associationemergency medical servicesthrombectomytriage

Identifiers

PMID33023425
PMCPMC7587242
OpenAlexW3092578171

What OpenQuestion holds

Textmetadata
LicenceTDM
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.