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. 2022 Jun 16;22(1):111.
doi: 10.1186/s12873-022-00663-z.

Portable stroke detection devices: a systematic scoping review of prehospital applications

Susmita Chennareddy #  1 , Roshini Kalagara #  2 , Colton Smith  2 , Stavros Matsoukas  2 , Abhiraj Bhimani  2 , John Liang  2 , Steven Shapiro  2 , Reade De Leacy  2 , Maxim Mokin  3 , Johanna T Fifi  2 , J Mocco  2 , Christopher P Kellner  2
Affiliations

Portable stroke detection devices: a systematic scoping review of prehospital applications

Susmita Chennareddy et al. BMC Emerg Med. .

Abstract

Background: The worldwide burden of stroke remains high, with increasing time-to-treatment correlated with worse outcomes. Yet stroke subtype determination, most importantly between stroke/non-stroke and ischemic/hemorrhagic stroke, is not confirmed until hospital CT diagnosis, resulting in suboptimal prehospital triage and delayed treatment. In this study, we survey portable, non-invasive diagnostic technologies that could streamline triage by making this initial determination of stroke type, thereby reducing time-to-treatment.

Methods: Following PRISMA guidelines, we performed a scoping review of portable stroke diagnostic devices. The search was executed in PubMed and Scopus, and all studies testing technology for the detection of stroke or intracranial hemorrhage were eligible for inclusion. Extracted data included type of technology, location, feasibility, time to results, and diagnostic accuracy.

Results: After a screening of 296 studies, 16 papers were selected for inclusion. Studied devices utilized various types of diagnostic technology, including near-infrared spectroscopy (6), ultrasound (4), electroencephalography (4), microwave technology (1), and volumetric impedance spectroscopy (1). Three devices were tested prior to hospital arrival, 6 were tested in the emergency department, and 7 were tested in unspecified hospital settings. Median measurement time was 3 minutes (IQR: 3 minutes to 5.6 minutes). Several technologies showed high diagnostic accuracy in severe stroke and intracranial hematoma detection.

Conclusion: Numerous emerging portable technologies have been reported to detect and stratify stroke to potentially improve prehospital triage. However, the majority of these current technologies are still in development and utilize a variety of accuracy metrics, making inter-technology comparisons difficult. Standardizing evaluation of diagnostic accuracy may be helpful in further optimizing portable stroke detection technology for clinical use.

Keywords: Diagnosis; Emergency medical services; Prehospital; Stroke; Technology.

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Conflict of interest statement

Dr. De Leacy is a consultant for Stryker, Penumbra, Siemens, and Cerenovus. Dr. Mokin is supported by a grant from the NIH (NIH R21NS109575) and is a consultant for Medtronic and Cerenovus. Additionally, Dr. Mokin is an investor in BrainQ, Endostream, Serenity medical, Synchron. Dr. Fifi is a stockholder in Cerebrotech. Dr. Mocco is the PI on research trials funded by: Stryker Neurovascular, Microvention, and Penumbra and he is an investor in: Cerebrotech, Imperative Care, Endostream, Viseon, BlinkTBI, Myra Medical, Serenity, Vastrax, NTI, RIST, Viz.ai, Synchron, Radical, and Truvic. He serves, or has recently served, as a consultant for: Cerebrotech, Viseon, Endostream, Vastrax, RIST, Synchron, Viz.ai, Perflow, and CVAid. Dr. Kellner has received research grant support from Cerebrotech, Siemens, Penumbra, Minnetronix, Viz.AI, Integra, Longeviti, and Irras and has ownership in Metis Innovative and Precision Recovery. The remaining authors have no conflicts of interest to declare.

Figures

Fig. 1
Fig. 1
PRISMA flow diagram for study inclusion
See this image and copyright information in PMC

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