Evidence map›Paper›PMID 37333002›Full record

ArticleFrontiers in neurology2023

Diagnostic accuracy of telestroke consultation: a Louisiana based tele-network experience.

Mugilan Poongkunran, Robin D Ulep, Gage A Stuntz, Sara Mitchell, Kenneth J Gaines, Gabriel Vidal, Daniel Chehebar, Ifeanyi O Iwuchukwu, Harold McGrade, Alaa E Mohammed and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 35% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
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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 2 institutions in 1 country.

Mugilan PoongkunranOchsner Neuroscience Institute, Ochsner Health, New Orleans, LA, United States.
Robin D UlepOchsner Clinical School, New Orleans, LA, United States.
Gage A StuntzOchsner Clinical School, New Orleans, LA, United States.
Sara MitchellOchsner Clinical School, New Orleans, LA, United States.
Kenneth J GainesOchsner Neuroscience Institute, Ochsner Health, New Orleans, LA, United States.
Gabriel VidalOchsner Neuroscience Institute, Ochsner Health, New Orleans, LA, United States.
Daniel ChehebarOchsner Neuroscience Institute, Ochsner Health, New Orleans, LA, United States.
Ifeanyi O IwuchukwuOchsner Neuroscience Institute, Ochsner Health, New Orleans, LA, United States.
Harold McGradeOchsner Neuroscience Institute, Ochsner Health, New Orleans, LA, United States.
Alaa E MohammedOchsner Center for Outcomes Research, Office of Epidemiology and Biostatistical Collaborations, Ochsner Clinic Foundation, New Orleans, LA, United States.
Richard M ZweiflerOchsner Neuroscience Institute, Ochsner Health, New Orleans, LA, United States.
Ochsner Health System · USOchsner Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: Telestroke has grown significantly since its implementation. Despite growing utilization, there is a paucity of data regarding the diagnostic accuracy of telestroke to distinguish between stroke and its mimics. We aimed to evaluate diagnostic accuracy of telestroke consultations and explore the characteristics of misdiagnosed patients with a focus on stroke mimics. Methods: We conducted a retrospective study of all the consultations in our Ochsner Health's TeleStroke program seen between April 2015 and April 2016. Consultations were classified into one of three diagnostic categories: stroke/transient ischemic attack, mimic, and uncertain. Initial telestroke diagnosis was compared with the final diagnosis post review of all emergency department and hospital data. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+) and negative likelihood ratio (LR-) for diagnosis of stroke/TIA versus mimic were calculated. Area under receiver-operating characteristic curve (AUC) analysis to predict true stroke was performed. Bivariate analysis based on the diagnostic categories examined association with sex, age, NIHSS, stroke risk factors, tPA given, bleeding after tPA, symptom onset to last known normal, symptom onset to consult, timing in the day, and consult duration. Logistic regression was performed as indicated by bivariate analysis. Results: Eight hundred and seventy-four telestroke evaluations were included in our analysis. Accurate diagnosis through teleneurological consultation was seen in 85% of which 532 were strokes (true positives) and 170 were mimics (true negatives). Sensitivity, specificity, PPV, NPV were 97.8, 82.5, 93.7 and 93.4%, respectively. LR+ and LR- were 5.6 and 0.03. AUC (95% CI) was 0.9016 (0.8749-0.9283). Stroke mimics were more common with younger age and female gender and in those with less vascular risk factors. LR revealed OR (95% CI) of misdiagnosis for female gender of 1.9 (1.3-2.9). Lower age and lower NIHSS score were other predictors of misdiagnosis. Conclusion: We report high diagnostic accuracy of the Ochsner Telestroke Program in discriminating stroke/TIA and stroke mimics, with slight tendency towards over diagnosis of stroke. Female gender, younger age and lower NIHSS score were associated with misdiagnosis.

Indexed as

accuracyMIMICStelemedicineteleneurologytelestroke

Identifiers

PMID37333002
PMCPMC10273670
OpenAlexW4379230038

What OpenQuestion holds

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LicenceCC BY
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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.