Evidence map›Paper›PMID 39398987›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Prevalence and Determinants of Prehospital Impression of Stroke in Ischemic Stroke Patients.

Mauro Caffarelli, Andrew J Wood, Remle P Crowe, Edilberto Amorim, Hooman Kamel, Anthony S Kim, Elan L Guterman

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Mauro CaffarelliDepartment of Pediatrics, University of California, San Francisco. San Francisco, CA.ORCID 0000-0003-4075-6278
Andrew J WoodDepartment of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco. San Francisco, CA.
Remle P CroweESO, Inc., Austin, Tx.ORCID 0000-0001-9733-9294
Edilberto AmorimDepartment of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco. San Francisco, CA.
Hooman KamelDepartment of Neurology, Weill Cornell Medicine, New York, NY.ORCID 0000-0002-5745-0307
Anthony S KimDepartment of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco. San Francisco, CA.ORCID 0000-0002-8095-6517
Elan L GutermanDepartment of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco. San Francisco, CA.

Funding

The Care Ecosystem Response to COVID-19: Accelerating Research on Dementia Care that Meets the Needs of Caregivers and Persons with Dementia during COVID-19R01AG074710 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI POSSIN, KATHERINE LAUREL · 2022 to 2024
$9.1M
The Care Ecosystem: Navigating patients and caregivers through stages of dementia careR01AG056715 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI POSSIN, KATHERINE LAUREL · 2017 to 2021
$6.0M
Physiology-driven seizure management post-cardiac arrestK23NS119794 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI AMORIM, EDILBERTO · 2021 to 2025
$1.1M
Prehospital Management of Status EpilepticusK23NS116128 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GUTERMAN, ELAN · 2020 to 2024
$1.1M
NIA NIH HHS R01 AG056715NIA NIH HHS R01 AG074710NINDS NIH HHS K23 NS116128NINDS NIH HHS K23 NS119794
6 · The paper itself

Abstract

backgroundEmergency Medical Services (EMS) clinicians are front-line in evaluating patients with stroke in the community. Their ability to correctly identify stroke influences downstream management decisions. We sought to use a large national database of prehospital clinical data to determine risk factors associated with missed EMS stroke identification.

methodsRetrospective study examining EMS evaluation of adults with Emergency Department (ED) stroke diagnosis. We leveraged the ESO Data Collaborative research dataset containing EHR data from 2019-2022 that has a subset of encounters with linked hospital diagnostic codes. Our primary outcome was the presence of an EMS diagnosis of stroke. We evaluated the association between demographic and clinical variables with EMS stroke identification using Pearson χ2 test for demographic variables and multivariable GLM for clinical variables with adjustment for demographic variables.

resultsWe identified 34,504 EMS encounters for patients with ED stroke diagnosis. Of these, 11,077 (32.1%) strokes had missed EMS stroke identification and instead had an EMS impression of "Generalized Weakness" (25.9%), "Altered Level of Consciousness" (24.9%), and "Dizziness" (7.2%). Patients more likely to have missed prehospital stroke identification were of Black race (p=0.0001) and Hispanic ethnicity (p=0.0001). Clinical variables associated with higher risk of missed EMS stroke identification were suspected alcohol or drug use (RR 1.48, 95% CI 1.37-1.59), low GCS (RR 1.17, 95% CI 1.10-1.24), tachycardia (RR 1.05, 95% CI 1.01-1.09), and hypotension (RR 1.47, 95% CI 1.34-1.61).

conclusionsApproximately 1-in-3 patients transported by EMS did not have their stroke identified in the prehospital setting. Factors associated with lower odds of missed EMS stroke identification provide a starting point for future performance improvement initiatives.

Identifiers

PMID39398987
PMCPMC11469348

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.