Evidence map›Paper›PMID 38514189›Full record

Observational studyJournal of neurointerventional surgery2025

Portable cerebral blood flow monitor to detect large vessel occlusion in patients with suspected stroke.

Christopher G Favilla, Grayson L Baird, Kedar Grama, Soren Konecky, Sarah Carter, Wendy Smith, Rebecca Gitlevich, Alexa Lebron-Cruz, Arjun G Yodh, Ryan A McTaggart

Open access · greenAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Journal of neurointerventional surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
5.4field-weighted citation impact, top 4% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Article
  3. Building and Sustaining Open-Source Medical Device Projects.IEEE transactions on bio-medical engineering · 2025
    Review
  4. Article
  5. Article
  6. Pre-Hospital Stroke Care beyond the MSU.Current neurology and neuroscience reports · 2024
    Review
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

10 authors at 3 institutions in 1 country.

Christopher G Favilla *Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA Christopher.favilla@pennmedicine.upenn.edu.ORCID http://orcid.org/0000-0003-0871-9549
Grayson L Baird *Department of Interventional Radiology, Brown University, Providence, Rhode Island, USA.
Kedar GramaOpenwater, San Francisco, California, USA.
Soren KoneckyOpenwater, San Francisco, California, USA.
Sarah CarterDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Wendy SmithDepartment of Diagnostic Imaging, Lifespan Health System, Providence, Rhode Island, USA.
Rebecca GitlevichDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Alexa Lebron-CruzDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Arjun G YodhDepartment of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Ryan A McTaggartDepartment of Interventional Radiology, Brown University, Providence, Rhode Island, USA.
University of Pennsylvania · USBrown University · USProvidence College · US

Funding

Optical Monitoring of Cerebral Hemodynamics during Mechanical ThrombectomyK23NS110993 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI FAVILLA, CHRISTOPHER G. · 2019 to 2023
$1.0M
NINDS NIH HHS K23 NS110993
6 · The paper itself

Abstract

backgroundEarly detection of large vessel occlusion (LVO) facilitates triage to an appropriate stroke center to reduce treatment times and improve outcomes. Prehospital stroke scales are not sufficiently sensitive, so we investigated the ability of the portable Openwater optical blood flow monitor to detect LVO.

methodsPatients were prospectively enrolled at two comprehensive stroke centers during stroke alert evaluation within 24 hours of onset with National Institutes of Health Stroke Scale (NIHSS) score ≥2. A 70 s bedside optical blood flow scan generated cerebral blood flow waveforms based on relative changes in speckle contrast. Anterior circulation LVO was determined by CT angiography. A deep learning model trained on all patient data using fivefold cross-validation and learned discriminative representations from the raw speckle contrast waveform data. Receiver operating characteristic (ROC) analysis compared the Openwater diagnostic performance (ie, LVO detection) with prehospital stroke scales.

resultsAmong 135 patients, 52 (39%) had an anterior circulation LVO. The median NIHSS score was 8 (IQR 4-14). The Openwater instrument had 79% sensitivity and 84% specificity for the detection of LVO. The rapid arterial occlusion evaluation (RACE) scale had 60% sensitivity and 81% specificity and the Los Angeles motor scale (LAMS) had 50% sensitivity and 81% specificity. The binary Openwater classification (high-likelihood vs low-likelihood) had an area under the ROC (AUROC) of 0.82 (95% CI 0.75 to 0.88), which outperformed RACE (AUC 0.70; 95% CI 0.62 to 0.78; P=0.04) and LAMS (AUC 0.65; 95% CI 0.57 to 0.73; P=0.002).

conclusionsThe Openwater optical blood flow monitor outperformed prehospital stroke scales for the detection of LVO in patients undergoing acute stroke evaluation in the emergency department. These encouraging findings need to be validated in an independent test set and the prehospital environment.

Indexed as

Cerebrovascular CirculationStrokeAgedAged, 80 and overFemaleHumansMaleMiddle AgedProspective StudiesBlood FlowDeviceStrokeTechnologyThrombectomy

Identifiers

PMID38514189
PMCPMC11415534
OpenAlexW4393032685

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.