Evidence map›Paper›PMID 37249761›Full record

ArticleTranslational stroke research2024

Tissue Outcome Prediction in Patients with Proximal Vessel Occlusion and Mechanical Thrombectomy Using Logistic Models.

Florian Welle, Kristin Stoll, Christina Gillmann, Jeanette Henkelmann, Gordian Prasse, Daniel P O Kaiser, Elias Kellner, Marco Reisert, Hans R Schneider, Julian Klingbeil and 5 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational stroke research, 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
1.1field-weighted citation impact, top 22% 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

0 citing papers in PubMed, 5 citations in OpenAlex.

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

15 authors at 3 institutions in 1 country.

Florian Welle *Neuroimaging Laboratory, Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany.
Kristin Stoll *Neuroimaging Laboratory, Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany.
Christina GillmannSignal and Image Processing Group, Institute for Informatics, University of Leipzig, Leipzig, Germany.
Jeanette HenkelmannDepartment of Radiology, University of Leipzig Medical Center, Leipzig, Germany.
Gordian PrasseDepartment of Neuroradiology, University of Leipzig Medical Center, Leipzig, Germany.
Daniel P O KaiserInstitute of Neuroradiology, University Hospital Carl Gustav Carus, Dresden, Germany.
Elias KellnerMedical Physics, Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany.
Marco ReisertMedical Physics, Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany.
Hans R SchneiderNeuroimaging Laboratory, Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany.
Julian KlingbeilNeuroimaging Laboratory, Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany.
Anika StockertNeuroimaging Laboratory, Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany.
Donald LobsienDepartment of Neuroradiology, University of Leipzig Medical Center, Leipzig, Germany.
Karl-Titus HoffmannDepartment of Neuroradiology, University of Leipzig Medical Center, Leipzig, Germany.
Dorothee SaurNeuroimaging Laboratory, Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany.
Max WawrzyniakNeuroimaging Laboratory, Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany. max.wawrzyniak@medizin.uni-leipzig.de.
Leipzig University · DEUniversity of Freiburg · DEUniversity Hospital Carl Gustav Carus · DE

Funding

Deutsche Forschungsgemeinschaft SA 1723/5-1
6 · The paper itself

Abstract

Perfusion CT is established to aid selection of patients with proximal intracranial vessel occlusion for thrombectomy in the extended time window. Selection is mostly based on simple thresholding of perfusion parameter maps, which, however, does not exploit the full information hidden in the high-dimensional perfusion data. We implemented a multiparametric mass-univariate logistic model to predict tissue outcome based on data from 405 stroke patients with acute proximal vessel occlusion in the anterior circulation who underwent mechanical thrombectomy. Input parameters were acute multimodal CT imaging (perfusion, angiography, and non-contrast) as well as basic demographic and clinical parameters. The model was trained with the knowledge of recanalization status and final infarct localization. We found that perfusion parameter maps (CBF, CBV, and T

Indexed as

ThrombectomyAgedAged, 80 and overCerebral AngiographyFemaleHumansLogistic ModelsMaleMiddle AgedStrokeTomography, X-Ray ComputedTreatment OutcomeComputed tomographyPerfusionPredictionStrokeTissue outcome

Identifiers

PMID37249761
PMCPMC11226467
OpenAlexW4378746166

What OpenQuestion holds

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LicenceCC BY
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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.