Evidence map›Paper›PMID 38617048›Full record

ArticleResearch and practice in thrombosis and haemostasis2024

Electrical impedance measurements can identify red blood cell-rich content in acute ischemic stroke clots

Cansu Sahin, Alice Giraud, Duaa Jabrah, Smita Patil, Pierluca Messina, Franz Bozsak, Jean Darcourt, Federico Sacchetti, Anne-Christine Januel, Guillaume Bellanger and 13 more

Open access · goldAbstract read
In one paragraph

Article in Research and practice in thrombosis and haemostasis, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
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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

23 authors at 9 institutions in 6 countries.

Cansu SahinDepartment of Physiology, University of Galway, Galway, Ireland.
Alice GiraudSensome, Massy, France.
Duaa JabrahDepartment of Physiology, University of Galway, Galway, Ireland.
Smita PatilDepartment of Physiology, University of Galway, Galway, Ireland.
Pierluca MessinaSensome, Massy, France.
Franz BozsakSensome, Massy, France.
Jean DarcourtDepartment of Diagnostic and Therapeutic Neuroradiology, Centre Hospitalier Universitaire (CHU) de Toulouse, Toulouse, France.
Federico SacchettiDepartment of Diagnostic and Therapeutic Neuroradiology, Centre Hospitalier Universitaire (CHU) de Toulouse, Toulouse, France.
Anne-Christine JanuelDepartment of Diagnostic and Therapeutic Neuroradiology, Centre Hospitalier Universitaire (CHU) de Toulouse, Toulouse, France.
Guillaume BellangerDepartment of Diagnostic and Therapeutic Neuroradiology, Centre Hospitalier Universitaire (CHU) de Toulouse, Toulouse, France.
Jorge PagolaDepartment of Neurology, University Hospital Vall d'Hebron, Barcelona, Spain.
Jesus JuegaDepartment of Neurology, University Hospital Vall d'Hebron, Barcelona, Spain.
Hirotoshi ImamuraDepartment of Neurosurgery, Kobe City Medical Center General Hospital, Kobe, Japan.
Tsuyoshi OhtaDepartment of Neurosurgery, Kobe City Medical Center General Hospital, Kobe, Japan.
Laurent SpelleDepartment of Interventional Neuroradiology, Bicêtre Hospital, Le Kremlin-Bicêtre, France.
Vanessa ChalumeauDepartment of Interventional Neuroradiology, Bicêtre Hospital, Le Kremlin-Bicêtre, France.
Uros MircicDepartment of Neuroradiology, Centre for Radiology and Magnetic Resonance Imaging (MRI), University Clinical Center of Serbia, Belgrade, Serbia.
Predrag StanarčevićNeurology Clinic, University Clinical Center of Serbia, Belgrade, Serbia.
Ivan VukašinovićDepartment of Neuroradiology, Centre for Radiology and Magnetic Resonance Imaging (MRI), University Clinical Center of Serbia, Belgrade, Serbia.
Marc RiboDepartment of Neurology, University Hospital Vall d'Hebron, Barcelona, Spain.
Nobuyuki SakaiDepartment of Neurosurgery, Kobe City Medical Center General Hospital, Kobe, Japan.
Christophe CognardDepartment of Diagnostic and Therapeutic Neuroradiology, Centre Hospitalier Universitaire (CHU) de Toulouse, Toulouse, France.
Karen DoyleDepartment of Physiology, University of Galway, Galway, Ireland.
Centre Hospitalier Universitaire de Toulouse · FRKobe City Medical Center General Hospital · JPLaboratoire Ingénierie, Procédés, Aliments · FRScience Foundation Ireland · IEVall d'Hebron Hospital Universitari · ESBicêtre Hospital · FRCenter for Health, Exercise and Sport Sciences · RSCentar za Promociju Nauke · RSOllscoil na Gaillimhe – University of Galway · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Electrochemical impedance spectroscopy can determine characteristics such as cell density, size, and shape. The development of an electrical impedance-based medical device to estimate acute ischemic stroke (AIS) clot characteristics could improve stroke patient outcomes by informing clinical decision making. Objectives: To assess how well electrical impedance combined with machine learning identified red blood cell (RBC)-rich composition of AIS clots Methods: A total of 253 clots from 231 patients who underwent thrombectomy in 5 hospitals in France, Japan, Serbia, and Spain between February 2021 and October 2023 were analyzed in the Clotbase International Registry. Electrical impedance measurements were taken following clot retrieval by thrombectomy, followed by Martius Scarlet Blue staining. The clot components were quantified via Orbit Image Analysis, and RBC percentages were correlated with the RBC estimations made by the electrical impedance machine learning model. Results: Quantification by Martius Scarlet Blue staining identified RBCs as the major component in clots (RBCs, 37.6%; white blood cells, 5.7%; fibrin, 25.5%; platelets/other, 30.3%; and collagen, 1%). The impedance-based RBC estimation correlated well with the RBC content determined by histology, with a slope of 0.9 and Spearman's correlation of r = 0.7. Clots removed in 1 pass were significantly richer in RBCs and clots with successful recanalization in 1 pass (modified first-pass effect) were richer in RBCs as assessed using histology and impedance signature. Conclusion: Electrical impedance estimations of RBC content in AIS clots are consistent with histologic findings and may have potential for clinically relevant parameters.

Indexed as

acute ischemic strokeclot compositionelectrical impedancefirst-pass effectmechanical thrombectomy

Identifiers

PMID38617048
PMCPMC11015511
OpenAlexW4392859147

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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.